CN104149643B - For controlling the method and system of the energy requirement that network is got on the bus - Google Patents

Abstract

One method involves monitoring the amount of electrical energy available on a grid simultaneously powering one or more loads. The available amount of electrical energy represents the amount of electrical energy that can be consumed at the same time without exceeding the capacity of the grid. The method also includes monitoring electrical energy requirements of a plurality of electric vehicles traveling on a network of routes, the network of routes including one or more conductive paths extending along the routes for transferring electrical energy from the grid to the electric vehicles. The method further includes controlling the movement of the electric vehicle such that the electrical energy demand of the electric vehicle does not exceed the amount of electrical energy available on the grid.

Description

Method and system for controlling energy demand of vehicles on a network

Cross References to Related Applications

This application claims priority to US Provisional Patent Application No. 61/819,823, entitled "Method and System for Controlling Energy Demand of Vehicles on a Network," filed May 6, 2013 (the '823 application). The entire contents of the '823 application are hereby incorporated by reference.

technical field

Embodiments of the subject matter described herein relate to electric vehicle systems. Other embodiments relate to electric vehicle systems traveling on a network of routes.

Background technique

Known vehicle systems include one or more motorized cars or units, and in some cases, one or more non-motorized cars or units, which are interconnected for travel along a route. The motor vehicle provides traction to drive the motor vehicle and the non-motor vehicle to travel along the route.

The motor vehicle may be propelled by supplying current to the vehicle from an off-board power source through one or more conductive paths extending along the route of travel. For example, a route (or at least a portion thereof) may include a conductive path that is a portion of or extends along the route and that provides electrical current to a moving vehicle to drive said vehicle. The conductive paths may include electrical tracks, overhead catenaries, and the like.

The tractive effort required to drive the motor vehicles and non-motor vehicles along a route may vary from trip to trip, as various parameters vary with location and/or time during a trip. These varying parameters may include curvature and/or grade of the route, speed limits and/or requirements of vehicle systems, and the like. For an electric drive vehicle, it is driven by electric energy (such as current), and the electric energy comes from a part of the power route provided by the grid, and the amount of electricity required by the electric drive vehicle (such as traction) varies with the change of the required traction force.

Currently, all electrically driven vehicles can be operated on routes where the electrical energy provided to these vehicles is limited by the capacity of the power source. Each train needs power from the same power source or power station at the same time, for example, may require combined power, and there is a risk of exceeding or possibly exceeding the capacity of the power source. Exceeding this capacity may result in insufficient electrical power being supplied to one or more motor vehicles, causing one or more vehicles to stop. This stalling can cause delivery delays.

Additionally, other external loads relative to the vehicle may require power from the same source that also powers the motor vehicle. For example, cities, towns, etc. may have many electrical loads that are powered by the same power source that simultaneously powers motor vehicles. If the capacity of the power source exceeds the energy available to tow the vehicle and other loads, insufficient power is available to the other loads, which can result in a blackout.

A possible solution to the above-mentioned problems is to increase the capacity of the power sources, increase the capacity of the conductive paths that supply the electrical energy, and/or increase the number of power sources. However, these solutions involve significant financial costs and these solutions can be very expensive.

Contents of the invention

In an embodiment, a method (eg, controlling energy demand of a plurality of motor vehicles on a network) is provided that includes monitoring the amount of electrical energy available on a grid simultaneously powering one or more loads. The available amount of electrical energy represents the electrical energy that can be consumed at the same time without exceeding the capacity of the grid. The method also includes monitoring electrical energy requirements of a plurality of electric vehicles traveling on a network of routes, the network including one or more conductive paths extending along the routes for delivering electrical energy from the grid to the electric vehicles. The method further includes controlling the movement of the electric vehicle such that the electrical energy demand of the electric vehicle does not exceed the amount of electrical energy available on the grid.

In an embodiment, a network planner system is provided that includes a grid monitoring device and one or more processors. The grid monitoring device is configured to monitor the availability of electrical energy on a grid simultaneously powering one or more loads. The available amount of electrical energy represents the amount of electrical energy that can be consumed at the same time without exceeding the capacity of the grid. The grid is configured to transfer electrical energy through one or more conductive paths extending along a network of routes on which a plurality of electric vehicles travel for transferring electrical energy to the electric vehicles for powering the electric vehicles. The one or more processors are configured to communicate with the grid monitoring device and the trip planner system on the electric vehicle to control the movement of the vehicle so that the electrical energy demand of the electric vehicle does not exceed the amount of electrical energy available on the grid.

In an embodiment, a network planner system is provided, comprising a grid monitoring device, an energy demand monitoring device and one or more processors. The grid monitoring device is configured to monitor the availability of electrical energy on a grid simultaneously powering one or more loads. The available amount of electrical energy represents the amount of electrical energy that can be consumed at the same time without exceeding the capacity of the grid. The energy demand monitoring device is configured to monitor electrical energy requirements of a plurality of electric vehicles traveling on a network of routes, the network of routes including one or more conductive paths extending along the routes for delivering electrical energy from a power grid to the electric vehicles for the purpose of powering the electric vehicles. car power supply. The one or more processors are configured to control the movement of the electric vehicle so that the electrical energy demand of the electric vehicle does not exceed the amount of electrical energy available on the grid. The one or more processors are configured to control the electric vehicles by at least one of modifying energy usage plans submitted by the electric vehicles traveling on the network, or delivering to the electric vehicles a vehicle-specific maximum electrical energy demanded by each electric vehicle from the grid. The movement of the car.

A method is provided which includes:

monitoring the availability of electrical energy on the grid for simultaneously powering one or more loads, said availability of electrical energy representing the amount of electrical energy that can be consumed simultaneously without exceeding the capacity of the grid;

monitoring electrical energy requirements of a plurality of electric vehicles traveling on a network of routes, the network of routes including one or more conductive paths extending along the routes for transferring the electrical energy from an electrical grid to the electric vehicles; and

The movement of the electric vehicle is controlled such that the electric energy demand of the electric vehicle does not exceed the available amount of electric energy on a grid.

In one embodiment, monitoring said electrical energy demand comprises monitoring an energy usage plan for each electric vehicle, the energy usage plan detailing the electrical energy demand of each electric vehicle along a route, and by aggregating the electrical energy demand from the energy usage plan at a future time Instead, a projected energy demand at a future time is determined.

In one embodiment, controlling the movement of the electric vehicle includes modifying the energy usage plan based on at least one of trip replanning, additional electric vehicles traveling on the network, or projected energy demand exceeding the available amount of electrical energy at a future time; and The modified energy usage plan is communicated to electric vehicles traveling on the network.

In one embodiment, the energy usage plan provides instructions for at least one of routing, schedule, vehicle configuration, or mobility characteristics to be performed by electric vehicles traveling on the network.

In one embodiment, controlling the movement of the electric vehicles includes allocating a vehicle-specific maximum electrical energy demanded from the grid by each electric vehicle to the electric vehicles traveling on the network.

In one embodiment, based on the maximum electric energy allocated to each electric vehicle, the electric vehicle generates an energy usage plan for the travel route of each electric vehicle.

In one embodiment, monitoring the availability of electrical energy includes monitoring changes in the availability of electrical energy on the grid with respect to time.

In one embodiment, monitoring the availability of electrical energy includes monitoring the availability of electrical energy on a portion of the grid, and controlling the movement of electric vehicles traveling on sub-networks of the route powered by the portion of the grid so that the demand for electrical energy does not exceed the portion The available amount of electrical energy.

In one embodiment, controlling the movement of the electric vehicles includes creating a network energy consumption plan that assigns energy consumption parameters to electric vehicles traveling on the network to prevent the electric vehicles from exceeding the amount of electrical energy available on the grid.

A network planner system is provided, comprising:

a grid monitoring device configured to monitor the availability of electrical energy on a grid for simultaneously powering one or more loads, said available amount of electrical energy representing the amount of electrical energy that can be consumed simultaneously without exceeding grid capacity; said grid configured to transmit electrical energy for delivery to the electric vehicle for powering the electric vehicle through one or more conductive paths extending along a network of routes traveled by the plurality of electric vehicles, the electric vehicle having an on-board trip planner system;

and one or more processors configured to communicate with the grid monitoring device and a trip planner system on the electric vehicle to control movement of the electric vehicle such that the electric vehicle's electrical energy demand does not exceed the amount of electrical energy available on the grid.

In one embodiment, the one or more processors are configured to create a network energy consumption plan that allocates a vehicle-specific maximum electrical energy that can be demanded by individual electric vehicles traveling on the network to prevent the electric vehicle's electrical energy demand from exceeding the The amount of electrical energy available on the grid.

In one embodiment, the one or more processors are configured to create a network energy consumption plan that modifies at least one of a route, schedule, vehicle configuration, or mobility characteristics of one or more electric vehicles traveling on the network, In order to prevent the electric energy demand of electric vehicles from exceeding the available amount of electric energy on the grid.

In one embodiment, the movement characteristics include at least one of: speed, acceleration, position, direction of travel, use of regenerative braking to provide power to the grid, or use of an alternative energy source instead of drawing power from the grid for immediate consumption.

In one embodiment, one or more electric vehicles that receive modifications to at least one of routes, schedules, vehicle configurations, or mobility characteristics automatically perform the modifications.

In one embodiment, the one or more processors are configured to receive from the trip planner system a vehicle-specific energy usage plan created by the trip planner system detailing the vehicle-specific energy requirements for each electric vehicle traveling along the route .

In one embodiment, the one or more processors are configured to re-plan trips based on one or more electric vehicles traveling on the network, additional electric vehicles traveling on the network, or projected electric vehicle energy demands in the future The time exceeds at least one of the available amounts of electrical energy at future times to modify the one or more energy usage plans.

In one embodiment, the one or more processors are configured to receive an energy usage plan for at least one planned route from a trip planner system on board an electric vehicle, a proposed route for each electric vehicle, current energy demand, current operating feature, or the current route feature.

In one embodiment, the electric vehicle is a rail vehicle and the route is a track.

In one embodiment, the amount of electrical energy available on the grid for powering the one or more loads is less during peak energy usage times than during off-peak energy usage times.

A network planner system is provided, comprising:

a grid monitoring device configured to monitor the availability of electrical energy on a grid simultaneously supplying one or more loads, the availability of electrical energy being the amount of electrical energy that can be consumed simultaneously without exceeding the capacity of the grid;

An energy demand monitoring device configured to monitor electrical energy demand of a plurality of electric vehicles traveling on a network of routes, the network of routes including one or more conductive paths extending along the routes for transferring electrical energy from an electrical grid to the electric vehicles to power electric vehicles; and

one or more processors configured to control the movement of the electric vehicle so that the electrical energy demand of the electric vehicle does not exceed the amount of electrical energy available on the grid, wherein the one or more processors are configured to modify the The energy usage plan submitted by the vehicle, or the vehicle-specific maximum electric energy demanded by each electric vehicle from the grid is transmitted to at least one of the electric vehicles to control the movement of the electric vehicle.

Description of drawings

The subject matter described herein may be better understood by reading the ensuing detailed description of non-limiting embodiments, with reference to the accompanying drawings, in which:

1 is a schematic diagram of a vehicle network according to an embodiment;

Figure 2 shows an electrically driven vehicle according to an embodiment;

Figure 3 is a network planner system according to an embodiment;

Figure 4 is a graph showing the energy usage schedule of electric vehicles on the network over a period of time;

5 is a graph illustrating the energy usage plan of FIG. 4 over a period of time, according to an embodiment;

FIG. 6 is a diagram of the energy usage plan of FIG. 4 modified according to an embodiment;

FIG. 7 is a diagram of the energy usage plan of FIG. 5 modified according to an embodiment;

8 is a flowchart of one embodiment of a method of controlling electrical energy demand of vehicles on a network.

detailed description

The foregoing summary, and the following detailed description of specific embodiments of the inventive subject matter, may be better understood when read in conjunction with the accompanying drawings. Concerning the scope, the figures show program diagrams of the functional blocks of various embodiments, which do not necessarily represent distinctions between hardware and/or circuits. Thus, for example, one or more functional modules (eg, a processor or memory) may be implemented in a single piece of hardware (eg, a general-purpose single processor, microprocessor, RAM, hard disk, etc.). Similarly, the program may be an independent program, combined with a subroutine in the operating system, or a function in an installed software package, and the like. The various embodiments are not limited to the devices and instrumentalities shown in the drawings.

Herein, the use of the singular to describe an element or step followed by "a" or "an" should be understood as not excluding plural elements or steps, unless such exclusion is expressly stated. In addition, the mention of "one embodiment" in the present invention is not intended to exclude other embodiments that also include the cited technical features. And, conversely, unless expressly stated, an embodiment "comprises," "comprises," or "has" (and various forms thereof) an element or elements that have a specified property and may include other elements that do not have that property. This energy-generating element.

The system described herein may include or represent hardware and related instructions (such as software stored on a tangible and non-transitory computer-readable storage medium such as a computer hard disk, ROM, RAM, etc.), which execute the instructions described herein. operate. Hardware may include circuitry that includes and/or interfaces with one or more logic devices, such as microprocessors, processors, controllers, and the like. These devices may be off-the-shelf devices that perform the operations described herein in accordance with the instructions above. Additionally or alternatively, one or more of these devices may be hardwired with logic circuitry for performing these operations.

As used herein, the term "vehicle system" includes one or more vehicles that generate tractive effort to travel along a route. Unless otherwise specified (eg, used as a non-motorized vehicle), the term "vehicle" refers only to a motorized vehicle that provides traction to propel a vehicle system along a route. The term "consisting of" may refer to a group of one or more vehicles that may be mechanically and/or logically linked together to travel along a route. Vehicle systems may consist of one group or two or more groups connected together. According to various aspects of the inventive subject matter herein, a group may be defined based on one or more of the following: mechanical connection, where the vehicles are mechanically connected in the group and at least adjacent to other vehicles in the group; electrical connection, where the vehicles Electrical connections may transfer electrical energy between vehicles; and/or operational/functional connections where multiple vehicles are controlled in a coordinated manner, such as distributing certain modes of powered operation. As one embodiment, in the context of a rail vehicle, a locomotive consist includes a plurality of locomotives that are mechanically (and possibly electrically) connected together, where each locomotive is connected to and adjacent to at least one other locomotive in the consist. For example, a group of vehicles, or a group of vehicles, may include two vehicles that are mechanically linked to each other and/or communicate through one or more wired and/or wireless connections to collectively control the traction and/or braking forces of the vehicles in the group. one or more vehicles.

Although one or more embodiments are described and illustrated with reference to rail vehicle systems, including trains, locomotives, and other rail vehicles, not all embodiments are so limited. For example, one or more embodiments may also be used with conventional vehicles, such as off-highway vehicles (such as vehicles that are not intended and/or permitted to travel on public roads), agricultural vehicles, motorcycles and other transport vehicles, and/or Ships at sea.

In distributed power operation, the term "lead vehicle" refers to the control operation of one or more vehicles in a vehicle system, not necessarily referring to a vehicle at the front end of the vehicle system or at the lead end of the vehicle system. For example, the lead locomotive in a train may not be located at the front end of the train. The term "remote vehicle" relates to a vehicle in the vehicle system other than the lead vehicle. For example, a remote vehicle may include a locomotive in a train controlled by a lead locomotive. The term "remote" does not require a predetermined spacing or distance between. For example, a remote vehicle may be directly connected to the lead vehicle. The vehicle system may have a lead group comprising a lead vehicle mechanically connected to one or more remote vehicles, and may also have one or more remote groups forming the ensemble of remote vehicles, located at various locations in the vehicle system. Some vehicle systems may have individual vehicles in a train separated from other vehicles by one or more non-propelled vehicles (eg, freight cars or passenger cars in a rail vehicle system). Groups of vehicles may also be separated by non-propelled vehicles.

FIG. 1 is a schematic diagram of a vehicle network 100 according to an embodiment of the present invention. The illustrated vehicle network 100 may be part of a larger vehicle network. Vehicle network 100 includes a plurality of routes 102 consisting of routes 103 , 104 , 105 , 106 , and 107 . Preferably, the vehicle network 100 may include more or less than five routes 103-107, as shown in FIG. 1 . Certain routes 102 may intersect other routes 102 in network 100 . For example, route 103 intersects routes 106 and 107 , route 104 intersects routes 105 and 106 , and route 105 intersects routes 104 , 106 and 107 . Multiple vehicle systems 108 may be traveling on network 100 of routes 102 at the same time. For example, as shown in FIG. 1 , vehicle system 109 travels along route 103 , vehicle system 110 travels along route 106 , vehicle system 111 travels along route 104 , and vehicle system 112 travels along route 105 . Although four vehicle systems 108 are shown in FIG. 1 , the network 100 may include any number of vehicle systems 108 . Each vehicle system 108 may include one or more motor vehicles connected to other motor vehicles and/or non-motor vehicles or load vehicles (eg, vehicles that do not provide power but consume electrical energy for one or more purposes). Non-Motor Vehicles may be configured to carry goods and/or people along route 102 . Each vehicle system 108 travels along one or more routes 102 in the vehicle network 100 on a trip between a start/origin location and a destination/end location.

Route 102 may include one or more conductive paths 114 extending along route 102 . Conductive path 114 may transfer electrical energy from power source 116 . Power source 116 may be one or more power plants, such as coal power plants, nuclear power plants, and/or natural gas power plants. Preferably, power source 116 may represent one or more other energy sources, such as renewable energy sources (eg, wind, hydro, solar, geothermal, and other sources for generating electric current). The term "electrical energy" as used herein may refer to current, voltage, electrical power (eg, wattage), and the like. The term "current" as used herein relates to the rate at which electrical energy is transferred, and includes direct current (eg, constant voltage) and/or alternating current (eg, voltage that varies over time). Electrical energy transmitted along conductive path 114 by power source 116 may form at least a portion of grid 118 . Grid 118 distributes electrical energy from source 116 to one or more loads through conductive paths 114 . Preferably, grid 118 may be powered by more than one power source 116 .

The grid 118 has a grid capacity, which represents the amount of electrical energy available on the grid 118 for simultaneously powering one or more loads. Grid capacity is limited by delivery hardware, such as the available amount of electrical energy that can be delivered by the conductive path 114 and/or the one or more power sources 116 that provide the electrical power, the one or more power sources 116 having a production capacity limited by fuel, plant size, etc. ability. The term "capacity" relates to the available rate of energy transfer (eg, current), available power (eg, wattage), available voltage, and the like.

In one embodiment, the only loads that require electrical energy from the grid 118 are loads placed on the vehicle system 108 . As such, grid capacity represents the available amount of electrical energy to power one or more loads on vehicle systems 108 traveling on network 100 . Alternatively, grid 118 may provide electrical energy to power vehicle system 108 as well as other loads, such as residential loads, commercial loads, etc. in cities, towns, and/or rural areas. In this manner, the amount of electrical energy available on the grid 118 for powering loads on the vehicle system 108 may be reduced due to varying amounts of power demanded by other loads at different times. For example, during peak usage times of the day, such as the afternoon or early evening, the amount of electrical energy available to power the vehicle system 108 may potentially be less due to greater non-vehicle (eg, residential) load demand.

As used herein, exceeding or overdrawing the availability of electrical energy on the grid is synonymous with exceeding grid capacity, since the availability of electrical energy is defined in part by grid capacity. For example, if the grid capacity is 50 megawatts (MW) and the demand at time t _x is 30 MW, then the amount of electrical energy available on the grid at time t _x is 20 MW. If the vehicle system requires 25MW at time _tx , this demand will exceed the amount of electricity available (eg 25MW is greater than 20MW) and the grid capacity (eg 25MW plus 30MW equals 55MW which is greater than 50MW). Therefore, exceeding the amount of electrical energy available on the grid means exceeding the grid capacity. Thus, the expressions "exceeding the amount of electrical energy available on the grid" and "exceeding the capacity of the grid" are used interchangeably herein. Also, "monitoring the availability of electrical energy on the grid" and "monitoring the capacity of the grid" are also used interchangeably herein.

In an embodiment, electrically driven vehicles in vehicle system 108 draw electrical power from electrical grid 118 through conductive path 114 . The term "drawing" as used herein relates to the act of dissipating electrical energy provided by a conductive path. The term "demand" as used herein relates more specifically to the amount or rate of use of electric energy that electric vehicles require (eg demand) at present or in the future. For example, the rate at which electrical energy is demanded by an electric vehicle and the rate actually drawn through the conductive path may be the same or slightly different.

The drawn electrical energy is used to power one or more loads on the vehicle system 108 , such as drive generating loads, compressor loads, passenger loads, and the like. All vehicle systems traveling on network 100, such as vehicle systems 109-112, may require power from grid 118 at the same time, which, minus the amount of power available on grid 118, is approximately equal to the cumulative draw of vehicle systems 108 at that time electricity. If power source 116 is unable to meet the power requirements of vehicle systems 108, one or more vehicle systems 108 may be stopped along route 102 due to insufficient power, which will delay multiple other vehicle systems 108 on or around the affected route . In addition, if the demand for electrical energy exceeds the grid capacity at the same time, multiple routes 102 on the network 100 may experience outages, which may also cause delays.

In an embodiment, vehicle systems 108 traveling on the network of routes 102 include rail vehicles traveling on the network of trajectories. For example, a rail vehicle may include one or more electric locomotives or locomotives coupled with one or more non-electric (e.g., diesel, gasoline, etc.) locomotives and/or one or more non-propelled rail vehicles, such as passenger cars and/or or wagons attached. Additionally, the conductive pathway 114 may include electrical tracks (eg, three or four track systems) and/or cable slings.

The electrical energy demand of each vehicle system 108 traveling on the network 100 represents the amount of electrical energy drawn (and converted into power) to allow the vehicle system 108 to travel along the route 102 during the trip. For example, electric locomotives may require over 6MW of power or more. The electrical energy required at all times during a trip is not constant, nor are two different vehicle systems 108 traveling on the same route 102 requiring the same amount of electrical energy.

The energy requirements of the vehicle systems 108 vary according to many factors, such as route selection, vehicle configuration, and mobility characteristics. Route characteristics that may affect energy requirements include route gradient, route curvature, weather conditions (eg, wind speed and direction), number of stops and starts (eg, number of stops in the trip), and the like. For example, vehicle system 112 traveling on route 105 may travel along sloped or mountainous terrain, and it requires more power to enter mountainous terrain than vehicle system 109 traveling on flat ground. Vehicle structural features include the number and form of motor vehicles and non-motor vehicles in the vehicle system 108, the type and quantity of cargo (such as coal, passengers, cargo, etc.), the presence or absence rate on the vehicle system 108, the length of the vehicle system 108, The arrangement of moving cars relative to non-moving cars, and so on. Several of the listed features affect weight, as well as the weight distribution of vehicle systems. Generally, as the weight of the vehicle system 108 increases, the amount of electrical power required also increases. Mobility characteristics include the velocity and acceleration of the vehicle system 108, the number of actively powered electric vehicles, and the use of regenerative braking and/or alternative energy sources (e.g., diesel vehicles, solar panels, etc.) . In general, vehicle systems 108 require more electrical power as they operate at higher speeds, greater acceleration, and use more electric vehicles, although regenerative braking and/or alternative energy sources may reduce electrical power requirements.

Network 100 may further include network planner system 120 . The network planner system 120 may not be onboard the vehicle system 108, such as at a sending station. In an alternative embodiment, the network planner system 120 may be on one of the vehicle systems 108 in the network 100 . Network planner system 120 includes communication system 122 . The communication system 122 may include antennas for wirelessly communicating with the vehicle systems 108 traveling on the network 100 . In an embodiment, the network planner system 120 may be configured to monitor the energy demand of the vehicle systems 108 on the network 100 . Additionally, the network planner system 120 may be configured to control the energy demand of the vehicle systems 108 on the network 100 to prevent electric vehicles from drawing beyond the grid capacity.

FIG. 2 shows an electrically driven vehicle 200 according to an embodiment of the present invention. Electric drive vehicle 200 , also referred to herein as electric vehicle 200 , may be part of vehicle system 108 , as shown in FIG. 1 . Electric vehicle 200 travels along route 202 . Although shown alone, electric vehicle 200 may be connected before and/or behind other powered and/or non-powered vehicles to define vehicle system 108 . Electric vehicle 200 may be configured to draw electrical energy from conductive path 204 along route 202 to power one or more loads on electric vehicle 200 to provide traction to propel vehicle 200 and other vehicles in the same vehicle system. Electric vehicle 200 includes drive subsystem 224, which includes one or more electric motors that provide traction for drive. Conductive path 204 may be similar to conductive path 114 (shown in FIG. 1 ). As shown in FIG. 2, the conductive path 204 may be a three track or four track system known in the art. Optionally, the conductive path 204 may act as a cable sling over and/or alongside the motor 200 .

The electric vehicle 200 may include a locator element 206 to determine the location of the electric vehicle 200 . The locator element 206 may be a GPS sensor, or a sensor system including, for example, a GPS sensor, video determination, line set, radio frequency automatic equipment identification (RF AEI) tag, or the like. A wireless communication system 208 is provided to allow communication between trains and/or remote locations such as sending stations. Wireless communication system 208 may include transceiver equipment (not shown), antenna 210, and associated circuitry to allow transmission and reception of off-board communications. Communications may include information about travel plans and stops. The electric vehicle 200 may also include a route feature element 212 to provide information about the route, including slope, altitude, and curvature information. The route feature element 212 may include an onboard route database 214 . Database 214 stores information regarding previously traveled routes, current routes taken, and planned future routes, including options to route differently. Additionally, sensors 216 may be installed on the electric vehicle 200 to detect the current energy draw of the vehicle 200 from the grid. Additionally, the sensors 216 may detect the weight of the vehicle system 108 (shown in FIG. 1 ), throttle adjustment of the electric vehicle 200 , the speed of the vehicle 200 , and the power of the electric vehicle 200 , among others.

In an embodiment, the electric vehicle 200 includes a trip planner system 218 . The trip planner system 218 is configured to interpret various input signals regarding a current and/or planned trip and generate a trip plan. The trip plan may indicate or determine that the individual tractive and/or braking forces of different electric vehicles 200 in the vehicle system are used for different portions or different parts of the vehicle system's trip. For example, in a split power vehicle system, the trip plan may include different throttle adjustments and/or brake adjustments for the lead vehicle and the remote vehicle of the vehicle system at various portions of the trip. For example, generating a trip plan can reduce energy consumption (such as power drawn from the grid) and establish a desired trip time while adhering to it through safety and regulatory constraints. The trip plan may also result in the vehicle 200 consuming less fuel/generating fewer emissions than in a relatively small time buffer, such as one percent of the entire trip time, at the same time (or over the same period of time, Three percent, five percent, or other relatively small percentage) of the same vehicles traveling along the same route to the same destination, but at the speed limit of the route (eg, track speed).

Trip planning is based on a trip profile, which includes information related to the electric vehicle 200, vehicle systems, route, geography including route extension, and various goals in the trip, such as time constraints and limited energy draw/consumption. Information about the trip profile may be collected by the locator element 206 , the route feature element 212 , the route database 214 , and/or the sensors 216 . Other information may be collected from external sources, such as sensors on different electric vehicles in the same or different vehicle systems, and messages transmitted from sending points and/or wiring devices.

The trip profile may be based on or include vehicle data, route data, trip data, and/or updated vehicle data, route data, and/or trip data. The vehicle data includes information about the electric vehicle 200 and/or information about cargo loaded on the vehicle system. For example, vehicle data may represent cargo content (such as information about the cargo being shipped) and/or vehicle information (such as model number, fuel efficiency, manufacturer, power, etc.) about electric vehicles and/or other powered vehicles in the vehicle system and non-powered vehicles). Route data includes information about routes currently traveled and/or future traveled by the vehicle system. For example, route data may include information regarding the location of damaged portions of the route, which are being repaired or under construction, the curvature and/or slope of the route, GPS coordinates of the route, and the like. Trip data includes information about upcoming trips for the vehicle system. Based on an itinerary selected from an origin to an end point, the itinerary data may include, for example, station information at the departure station at the beginning of the trip and/or at the final station at the end of the trip, restriction information (such as determined work areas and/or route fixes), and/or Or operational/mobility information (eg speed/throttle limits for various congested areas, slow sequences, working areas, etc.).

In alternative embodiments, the trip planner system 218 may not be located on the electric vehicle 200, such as at the departure point. In the case of this option, input information about the trip profile from the sensors 216, locator elements 206, route feature elements 212, route database 214, etc., may be communicated via the wireless communication system 208 to the off-board trip planner system, Wherein the information is interpreted to generate a trip plan and then transmitted back to the electric vehicle 200 .

The trip planner system 218 further includes a processor 220 operable to receive trip profile information. Generally, in various embodiments, processor 220 may include processing circuitry such as one or more field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), or microprocessors. Processor 220 may, in various embodiments, be configured to execute one or more algorithms to implement the described functions. One or more algorithms may comprise aspects of the described embodiments, either detailed in a flowchart or as steps of a method. For example, processor 220 may execute algorithms to interpret received information and calculate a trip plan. The trip plan may be based on a model of vehicle behavior for electric vehicle 200 traveling along a route, which is a solution of non-linear difference equations obtained from a simplified assumed physical model. In an embodiment, the trip planner system 218 includes a software application, such as the Trip Optimization software application provided by General Electric Company, to control the driving operation of the electric vehicle 200 in the vehicle system on the trip.

The electric vehicle 200 may further include a controller element 222 . The controller 222 is configured to control the electric vehicle 200 to travel according to its travel plan. Controller element 222 may preferably be an integral element of trip planner system 218 , as shown in FIG. 2 . In an embodiment, the controller 222 enables the vehicle to operate the decision automatically. For example, the controller 222 generates control signals based on the operating adjustments specified by the trip plan, which communicates with one or more drive subsystems 224 of the electric vehicle 200 of the vehicle system, so that the electric vehicle 200 automatically follows the operating adjustments of the trip plan. Alternatively, or in addition, the control signal may be communicated to one or more on-board output devices of the electric vehicle 200, where the output device is configured to notify an operator of the one or more vehicles 200 of the designated operational adjustments. The operator can then manually perform specified operational adjustments to follow the trip plan.

In an embodiment, the trip plan includes an energy usage plan. The energy usage plan details the electrical energy required by the electric vehicle 200 to travel along the route. Energy usage planning can be an extension of trip planning. For example, when the trip plan instructs the controller 222 and/or the operator, such as what route to choose and/or what speed to travel based on the results determined in the trip profile, the energy usage plan calculates that the electric vehicle 200 will perform the trip plan in the vehicle system. The electricity required from the grid. Like the trip plan, the energy usage plan is generated in the trip planner system 218 by the processor 220, such as by using an algorithm in software. Also like trip planning, energy usage planning is a calculated estimate of a planned trip because many variables affect the actual energy drawn from the grid during the trip.

FIG. 3 is a network planner system 300 according to an embodiment. The network planner system 300 may be the network planner system 120 shown in FIG. 1 . Network planner system 300 includes communication system 302 . Communication system 302 may include a transceiver (not shown), antenna 304, and associated circuitry that allow communication to be communicated to electric vehicles on vehicle system 108 (shown in FIG. 1 ) traveling in network 100 (shown in FIG. 1 ). or receive communications from it. Communications may be transmitted wirelessly using radio communications, WI-FI, microwave signals, and the like. Preferably, a wired connection such as a broadband network (WAN) may be used, additionally, or alternatively, wireless communication via antenna 304 may be used. In an embodiment, the wireless communication system 302 is configured to receive trip plans, including energy usage plans, from the vehicle systems 108 in the network 100 . For example, once the trip planner system 218 (shown in FIG. 2 ) of the electric vehicle 200 (shown in FIG. 2 ) calculates the trip plan for the planned next trip, the trip plan is sent from the communication system 208 (shown in FIG. ) is communicated to the network planner system 300 through the communication system 302. Preferably, communication system 302 may be used to communicate with off-board locations, such as remote transmission locations, line devices, and/or various stations within network 100 . Additionally, communication system 302 may allow network planner system 300 to remotely communicate with network planner systems of a network of adjacent routes or a sub-network of adjacent routes.

Network planner system 300 also includes grid monitoring device 306 . Grid monitoring device 306 is configured to monitor the availability of electrical energy on grid 118 (shown in FIG. 1 ). Grid monitoring equipment 306 may include sensors and/or other devices to detect voltage and/or current on a real-time basis. For example, devices such as multimeters, transformers, converters, and the like may be used to monitor grid 118 operation. The grid monitoring device 306 can detect the grid capacity in real time, so that the network planner system 300 can track the available amount of electric energy on the grid 118, which is the amount of electricity required by the vehicle system 108 to travel on the network 100 (both shown in FIG. 1 ), rather than Will cause overdraft. Alternatively, or in addition, grid monitoring device 306 may receive real-time updates regarding current grid capacity measurements from sources supplying electrical energy to grid 118, such as source 116 (shown in FIG. 1 ), or other continuous monitoring A power source for the grid 118 . The grid monitoring device 306 records updates or logs, such as logs, of the available electrical energy to determine future projected electrical energy availability. For example, if the available amount of electrical energy on the grid is plus or minus 2MW at 30MW at noon every day of the week, then the estimated available amount of electrical energy at noon the next day is expected to be at least 28MW.

Preferably, monitoring the availability of electrical energy comprises monitoring the availability of electrical energy of a specific part of the grid, alternatively or additionally, monitoring the entire grid. The movement of an electric vehicle traveling on a sub-network of routes driven by a section of the grid is controlled so that the demand for electrical energy does not exceed the amount of electrical energy available in that section. Preferably, grid monitoring device 306 may store a record of measured and/or received operating conditions of grid 118 in memory (not shown) and/or in memory 308 of network planner system 300 . The memory 308 may be a hard disk, server, CD, DVD, flash memory (such as USB flash memory), floppy disk, random access memory (RAM), read only memory (ROM), and the like. Preferably, network planner system 300 may store data on an external storage device (not shown), additionally, or alternatively, to memory 308 .

The network planner system 300 further includes an energy demand monitoring device 310 . The energy demand monitoring device 310 is configured to monitor the energy demand of the vehicle systems 108 (both shown in FIG. 1 ) on the network 100 . In an embodiment, energy demand monitoring device 310 monitors energy demand by analyzing energy usage plans received from electric vehicles 200 (shown in FIG. 2 ) of vehicle systems 108 on network 100 . For example, an energy usage plan received via the communication system 302 , either as part of a trip plan or as an extension of a separate trip plan, is transmitted to the energy demand monitoring device 310 . The energy demand monitoring device 310 may be configured to sum or aggregate the energy usage plans to calculate the electrical energy demand on the network 100 at a particular time and/or time period. As used herein, power demand may refer to the power demand of a single electric vehicle on the network and/or the cumulative power demand of a plurality of electric vehicles. The cumulative energy demand represents the total electrical energy required from the grid by the vehicle system 108 traveling on the network 100 at a particular time.

Because the energy usage plan can be calculated prior to traveling the planned trip, the energy demand calculated by summing the energy usage plan can represent the projected energy demand at a particular future time instant. For example, at time X, energy demand monitoring device 310 may have an energy usage plan detailing projected energy consumption for an individual vehicle system 108 between times X+1 and X+10. Thus, the energy demand monitoring device 310 may be configured to calculate the projected energy demand at time X+5, eg by summing the individual energy demands in the energy demand plan received at time X+5. Further, the projected energy demand between the ranges X+1 and X+10 can be calculated and preferably plotted against time. The predicted energy demand is then compared with the scheduled grid capacity at the same time or over the same time frame to determine whether there is a possibility of exceeding the grid capacity.

Additionally, energy demand monitoring device 310 may be configured to monitor the current energy demand of electric vehicles 200 (shown in FIG. 2 ) in vehicle system 108 (shown in FIG. 1 ) traveling on network 100 (shown in FIG. 1 ). For example, electric vehicle 200 may also send real-time data to network planner system 300, collected by sensors 216 (shown in FIG. 2), detecting current energy demand and/or current energy drawn from the grid at operating times. For example, the electric vehicle 200 can be configured to transmit real-time energy demand data to the network planner system 300 periodically, such as every 10 seconds, every minute, or every 5 minutes. The energy demand monitoring device 310 may be configured to receive the current energy demand from all electric vehicles 200 currently traveling on the network 100, and aggregate the data to determine the current or actual electrical energy demand. Actual electrical energy demand exceeding grid capacity may cause one or more electric vehicles 200 to stop, causing delays for electric vehicles 200 along route 202 (shown in FIG. 2 ) and/or guiding path 204 (shown in FIG. 2 ) for potential electrical components to fail. damage. To avoid this situation, network planner system 300 is configured to control the movement of electric vehicles 200 to prevent cumulative energy demand from exceeding the amount of electricity available on grid 118 (shown in FIG. 1 ), which is described in detail below.

In an embodiment, the energy demand monitoring device 310 is configured to compare the actual electrical energy demand measured at a time with the predicted energy demand at the same time, thereby determining whether the predicted energy demand based on the received energy usage plan is future energy demand at the same time The exact expectations used. For example, assuming the above, based on the energy usage plan received at the current time X with respect to the projected energy used by each vehicle 200 (shown in FIG. 2 ) between time X+1 and X+10 in the future, energy The demand monitoring device 310 may calculate the projected energy demand at a specific future time X+5. The assumed time unit can be seconds, minutes, or hours. After time X+5, based on real-time information received from sensors 216 (shown in FIG. 2 ) on individual vehicles 200 , energy demand monitoring device 310 may calculate the actual electrical energy demand at time X+5. The actual electrical energy demand at time X+5 should be fairly close to the projected energy demand at that moment, so that the network planner system 300 can use the projected energy demand to make decisions about energy consumption on the network 100 at future times.

Such determinations may include, for example, whether to reduce future energy consumption to prevent cumulative energy demand from exceeding grid capacity. If the actual electrical energy demand is substantially greater or less than the projected energy demand, the network planner system 300 can make adjustments. Additionally, to compare cumulative energy demand, the energy demand monitoring device 310 may be configured to compare projected energy demand against actual energy demand on a vehicle-by-vehicle basis to determine if the energy usage plan for one or more electric vehicles is inaccurate And the trip planner system 218 (shown in FIG. 2 ) needs adjustment. Adjusting may include calibrating one or more sensors 216, one or more trip planner systems 218 calculating individual energy usage plans, and/or network planner system 300 determining a cumulative energy usage plan.

Network planner system 300 further includes at least one processor 312 . Processor 312 processes data received through various inputs of network planner system 300 , such as communication system 302 and various inputs operatively connected to input/output (I/O) devices 314 . For example, I/O devices 314 may receive input from user devices such as keyboards, mice, handheld devices (telephones, tablets, PDAs, etc.), and/or graphical user interfaces on display devices. Processor 312 , which may include or be an element of a microprocessor, controls the functions of network planner system 300 . Algorithms can be run within processor 312 to interpret received information and provide results as output. For example, the result may be an output as an operation command that communicates with the electric vehicle 200 (shown in FIG. 2 ) using the communication system 302 . Additionally, the results may be presented as charts, graphs, and/or other indications on a user display for an operator of the network planner system 300 . Preferably, the results may be stored in memory 308 or sent to an external storage device.

In an embodiment, the processor 312 of the network planner system 300 is configured to communicate with the trip planner system 218 (shown in FIG. 2 ) on one or more electric vehicles 200 (shown in FIG. 2 ) to control the electric vehicles. 200 so that the electric energy demand of the electric vehicle 200 does not exceed the available electric energy on the grid. On the one hand, the processor 312 of the network control system 300 controls the movement of the electric vehicles 200 by allocating the maximum amount of electric energy that each electric vehicle 200 can consume one or more times along the trip on the network 100 (shown in FIG. 1 ). The movement of the electric vehicle 200 can be controlled because the trip planner system 218 must set a trip plan that does not need to be greater than the maximum electrical energy allocated. The maximum electrical energy allocated to each electric vehicle 200 may be based on the amount of electricity available on the grid monitored at that moment, the number of electric vehicles 200 traveling on the network 100 at that moment, and/or received through the network planner system 300, Individual trip plans and energy usage plans for each vehicle 200 are determined by one or more processors 312 . The maximum electric energy is determined so that all electric vehicles 200 consuming the specified maximum electric energy will not exceed the grid capacity at this moment.

For example, processor 312 controls communication system 302 during planning of a trip on network 100 (shown in FIG. 1 ) by vehicle system 108 (shown in FIG. 1 ) having one or more electric vehicles 200 (shown in FIG. 2 ). The available energy of the vehicle systems 108 is sent for the trip. Available energy may be determined based on the number of vehicle systems 108 traveling on the network 100 and/or their energy usage plans. In an embodiment, all vehicle systems 108 are allocated the same amount of electrical energy at the same time. Thus, if the grid capacity is 100 MW, and there are 25 vehicle systems 108 traveling on the network 100, the maximum electrical energy each vehicle system will distribute is no greater than 4 MW.

Alternatively, in another embodiment, the processor 312 of the network planner system 300 dynamically assigns a maximum electrical energy consumption, which may vary based on the received trip plan/energy usage plan of the vehicle 200 . For example, if at time X+5 the first vehicle system's trip plan has the first vehicle carrying 10,000 tons of coal climbing a slope, the electric vehicles of the first vehicle system will generally be at time X+5 more flat or downhill than it is along the slope. A second vehicle system traveling on a slope or possibly even stopping at a transfer station requires more power at the same time. Thus, the processor 312 of the network planner system 300 will dynamically allocate that the first vehicle system has a greater amount of electrical energy than the second vehicle system at time X+5. Therefore, the electric energy allocated to each electric vehicle 200 may not be equal to the amount of all electric vehicles 200 traveling on the network. Additionally, the amount of electrical energy allocated may vary based on time, for example, at time X+10, the second vehicle system may be allocated more electrical energy than the first vehicle system. Thus, by monitoring the trip plan and the energy usage plan, the network planner system 300 can provide an allocation of electrical energy to the vehicle 200 that is tailored to the specific trip conditions of the vehicle 200 .

In an embodiment, the power allocated by electric vehicles traveling on the network 100 at a specific time can be proposed in the network energy consumption plan by the processor 312 of the network planner system 300 . A network energy consumption plan may provide the above-mentioned allocated energy information. For example, the energy consumption plan may communicate energy consumption parameters with individual electric vehicles 200 on the network 100 to inform each vehicle 200 (e.g., the control of the vehicle 200) of the maximum amount of power allocated to each vehicle 200 at various times during the trip. device or operator). Preferably, the network energy consumption plan may also include information on the estimated grid capacity for the entire time period, as well as the projected energy demand of the vehicle 200 during the time period. The processor 312 of the network planner system 300 may be configured to display the network energy consumption plan as a report or various charts and graphs to users near the network planner system 300 or to remote users via a network such as the Internet. Because the network planner system 300 can be configured to receive real-time updates of monitoring information, the network energy consumption plan can also be configured to be continuously or periodically updated automatically to show the latest information such as about network capacity and actual energy demand.

In an embodiment, a new electric vehicle 200 will travel on a trip on the network 100 , communicate these with the network planner system 300 , and the processor 312 controls the communication system 302 to responsively transmit the energy allocated for the trip. The energy allocated for a trip may be determined by subtracting the accumulated known energy demand of electric vehicles 200 on trips on the network 100 at the same time from the available electrical energy on the grid. For example, by determining that the allocated electrical energy cannot provide enough energy to the new electric vehicle 200 to meet its approximate trip goal in the trip plan, the processor 312 may recalculate the allocated electrical energy to all vehicles 200 to reduce Accumulated energy demand to accommodate additional new electric vehicles 200 that will travel on the network 100 . Replanned allocations can be documented in an updated network energy consumption plan. Thus, in embodiments, each period network planner system 300 receives one or more new trip plans, processor 312 may modify the electrical energy previously allocated to other vehicles 200 traveling on network 100 to accommodate the additional Electric vehicles 200, thereby preventing the demand for electrical energy from exceeding the capacity of the grid.

Additionally, the processor 312 of the network planner system 300 may be configured to make similar modifications to the vehicle 200 each period to complete its journey on the network and/or to form Trip pre-planning. A trip pre-plan is an updated trip plan, which may be based on various conditions, such as trips that need to be re-planned or erroneous calculations that result in inaccurate trip plans and/or energy usage plans. Furthermore, the processor 312 may modify the allocated energy of the vehicle 200 whenever the calculated projected energy requirement exceeds the threshold amount of electricity available on the grid. For example, a vehicle 200 currently traveling on the network 100 may receive real-time updates to limit power consumption to avoid overdrawing the grid capacity. Various modifications that may be made to network planner system 300 and/or trip planner system 218 (shown in FIG. 2 ) are described in detail below.

FIG. 4 is a graph 400 showing the energy usage plan of electric vehicles on the network over a period of time. The electric vehicle may be electric vehicle 200 (shown in FIG. 2 ), and the network may be network 100 of route 102 (both shown in FIG. 2 ). The graph is plotted as energy versus time, showing the power consumption of the vehicle 200 (eg, P=E/t, where the amount of power consumed is equal to the area of the curve). The time axis is labeled _t1 , _t2 , _t3 , etc., although the coordinates are symbolic, such as minutes or hours, including groups of minutes or hours (eg, _t2 could be 30 minutes after _t1 ). The energy axes are labeled E ₁ , E ₂ , E ₃ , etc., although the coordinates are symbolic, such as kilojoules or megajoules, including groups of kilojoules or megajoules (e.g. E ₁ could be 10 megajoules and E ₂ could be 20 MJ). In graph 400 , four energy usage plans are plotted as 402 , 404 , 406 , and 408 . Each energy usage plan represents the expected energy usage for a time period for an individual vehicle system including one or more electric vehicles 200 traveling on the network in a trip during the indicated time period. For example, each energy usage plan 402-408 may correspond to one of the vehicle systems 109, 110, 111, and 112 shown in FIG. 1, respectively. Energy usage plans can be calculated as part of trip planning.

As shown in graph 400, the energy usage plan is not uniform, it is the amount of electrical energy required at different times with travel schedules, vehicle configurations, routes, mobility characteristics and similar influences. For example, at time t ₁ , only the vehicle systems represented by energy usage plans 402 and 406 are actively requiring energy from the grid, which may indicate that the vehicles represented by energy usage plans 404 and 408 have not started their planned trip yet. At time t ₃ , energy usage plan 402 anticipates the highest energy demand, followed by plan 404 , plan 408 , and finally plan 406 . Energy usage plan 402 may be higher energy usage than other plans because, for example, the vehicle system configuration includes electric vehicle 200 towing a load with the greatest weight, which requires more power to propel. For example, energy usage plan 402 may be a coal train with a length of more than one mile, and energy usage plan 408 may be a passenger train with 15 or fewer passenger cars. In other embodiments, the route position of the vehicle system represented by plan 402 around time _t3 may have the vehicle system, which is climbing an incline, which may account for the need for more power. Additionally, the higher energy demand of schedule 402 may indicate that the vehicle system is traveling at a higher speed than other vehicle systems for a tighter schedule. Even along an energy usage plan, the energy requirements can be adjusted over time. For example, energy requirements may be reduced based on slowing down to a lower speed, traveling downhill (or on a flat road after a slope) and/or using alternative energy sources such as regenerative braking or a diesel-powered vehicle to replace at least some of the required drive The electrical energy of the vehicle system.

In an embodiment, the energy usage plan is in communication with network planner system 300 (shown in FIG. 3 ), and processor 312 of network planner system 300 interprets the energy usage plan and determines projected energy demand 410 for vehicle systems on the network. Projected energy demand 410 may be calculated by aggregating or summing the energy demand of each electric vehicle each time, as described in the energy usage plan. Projected energy demand 410 is plotted on graph 400 and also the availability 412 of electrical energy on the grid. The available power 412 can be detected by the grid monitoring device 306 of the network planner system 300 . If the detected amount of electrical energy available on the grid 412 is relatively constant, the processor 312 of the network planner system 300 can appropriately plot that it will remain constant for the time period shown in the future diagram 400 (e.g. energy line E ₁₀ ) . Figure 4 shows the processing steps performed by the processor 312 of the network planner system 300, but a diagram 400 or the like may preferably be displayed on a display of an operator of the network planner system 300 for viewing.

As shown in graph 400 of FIG. 4 , between times t ₂ to t ₄ , and after t ₆ , projected energy demand 410 exceeds the amount of electrical energy available on the grid 412 . If electric vehicles on the network actually draw these power levels at these times, there is a danger of overdrawing the grid, causing underpower and/or vehicle stalls.

FIG. 5 is a graph 500 showing an energy usage plan 402 408 for electric vehicles on the network over a period of time, according to an embodiment. Graph 500 shows the same energy usage plan 402 408 and projected energy usage 410 as graph 400 . In an embodiment, the available amount of electrical energy 502 on the grid may not be a fixed value, but fluctuate over time. For example, energy sources do not generate a fixed and identical supply of electricity to the grid. In other embodiments, the grid is not a closed grid that only supplies electrical energy to electric vehicles on the grid. Electric energy on the grid can be used to drive other loads, such as households, commercial and industrial uses, etc. In addition, driving electric vehicles and other loads may require more electric energy at certain times than other times. For example, the amount of electrical energy available 502 on the grid may decrease during peak energy usage times of the day and then increase during off-peak energy usage times. Thus, as shown in graph 500, the available amount of electrical energy 502 may fluctuate above and below E10 _over the course of time. Therefore, compared with the graph 400 of FIG. ₄ , the projected energy usage in the graph 500 exceeds the available amount of electric energy 502 very quickly (such as before _{t2 )} , but there is also more available amount of electric energy at times t5 and t6 .

FIG. 6 is a diagram 600 illustrating the energy usage plans 402-408 of FIG. 4 modified according to an embodiment. Referring again to FIG. 4 , from time t ₂ to t ₄ , and after t ₆ , projected energy demand 410 exceeds available electrical energy 412 on the grid, which may overdraw grid capacity. Accordingly, the processor 312 of the network planner system 300 (shown in FIG. 3 ) may be configured to modify the energy usage plan of one or more electric vehicles traveling on the network to reduce the projected power demand to the available power threshold 412 under. The processor 312 of the network planner system 300 may modify the energy usage plan for the planned trip by changing at least one of the route selected, the schedule of the trip, the vehicle configuration, and the mobility characteristics. It should be noted that the listed trip characteristics are typically described in a trip plan. Thus, the energy usage plan may be modified by modifying the trip plan, affecting the manner in which energy is used during the trip.

For example, in FIG. 6 the energy usage plan is modified 408 by changing the schedule of the trip. More specifically, instead of starting the trip at time t ₂ , the trip is moved forward to start at t ₀ and end at an earlier t ₄ instead of t ₆ . Apart from changing the departure time, the profile of the energy usage plan 408 is not modified, meaning that the energy usage remains the same during the trip. One reason for changing the trip start time represented by schedule 408 is to take advantage of the energy available that is not used on the grid between times _t0 and _t2 (such as the area below curve 412 and above curve 410), as As shown in graph 400 of FIG. 4 , while reducing the electrical energy that will be used around time _t3 .

Energy usage plan 402 has been modified in diagram 600 of FIG. 6 . The revised energy usage plan 402 in the graph 600 requires less electrical energy from the grid from time t ₀ to t ₄ than the original plan 402 shown in the graph 400 of FIG. 4 . Reducing electrical energy requirements can be achieved in a number of ways. For example, at times t ₀ and t ₁ , the electric vehicle may travel at a lower speed using less energy according to the modified energy usage plan 402 . Alternatively, or in addition, the vehicle architecture may also be modified, the vehicle system may use smaller or more fuel-efficient electric vehicles, the number and type of cargo compartments may be changed to reduce weight, and/or the vehicle layout may be modified, such as Change the distance of the EV relative to other vehicles. At t ₁ , to accelerate or maintain the same speed on an incline without increasing power requirements, for example, the modified plan 402 may require less power by relying on other sources of power. A potential power source could drive one or more diesel-powered vehicles in the vehicle system to provide traction, replacing some or all of the energy needs of electric vehicles. Thus, at times t ₁ and t ₃ , for example, vehicle systems may actually consume the same or more net energy to meet operating demands, although electrical energy demands may be substantially reduced due to the use of other energy sources. Other alternative energy sources may be the use of stored electrical energy, such as electrical energy generated by regenerative braking, and electrical energy stored in electrical energy storage devices in vehicle systems. Using alternative energy sources to meet power demands can reduce projected energy demands 410 .

In the diagram 600 of FIG. 6, the energy usage plan 404 has also been revised, although the changes from the original plan 404 shown in the diagram 400 of FIG. 4 are minor. For example from time t ₃ to time t ₆ , the revised plan 404 predicts greater electrical energy demand than the original plan 404 , but immediately after time t ₆ less energy is required. Using the modified schedule 404, the electrical energy required can remain relatively constant throughout the time period (represented as the area below the curve 404 on the graph 600), but more work is performed (e.g., more energy is required) early in the trip, Vehicle systems implementing energy usage plan 404 will use less energy after time t ₆ , which is a position on graph 400 where energy demand 410 exceeds available energy 412 . One method of rearranging workload along a trip may be to change the route, such as by using a different route to get from the origin to the destination. For example, the modified plan 404 may instruct the vehicle system to follow a hilly and/or mountainous route for the first half of the trip, but generally cruise downhill for the second half of the trip, which requires less electrical energy than a different route.

Energy usage plan 406 in diagram 600 is unchanged from original plan 406 shown in diagram 400 of FIG. 4 . As mentioned, the processor 312 of the network planner system 300 (shown in FIG. 3 ) may modify one or more energy usage plans, but need not modify all plans for all vehicles traveling on the network, so long as the modified plans result in The projected energy demand 410 does not exceed a threshold representing energy 412 available on the electrical grid. An updated projected energy demand 410 , calculated by aggregating the individual electrical energy demands for each period, is shown in graph 600 . The updated projected energy demand 410 is below the available energy 412 during the aforementioned time period. Therefore, if vehicle systems traveling on the network implement the modified energy usage plans 402-408, there will be no danger of overdrawing the electrical grid.

FIG. 7 is a diagram 700 illustrating the energy usage plan 402408 of FIG. 5 modified according to an embodiment. Diagram 700 shows modified energy usage plans 402-408 that are modified to prevent projected energy demand 410 from exceeding the amount of electrical energy available on the grid 502, which fluctuates over time. Because the availability 502 of electrical energy fluctuates, the network planner system 300 (shown in FIG. 3 ) can be configured to monitor grid capacity over a time period, in order to calculate a reasonable predicted availability 502 for the next time period, as shown in FIG. 7 . time period shown. The amount of electrical energy available 502 on grid capacity may fluctuate daily over time in a manner similar to yesterday, eg peak energy usage times at particular times of the day. For example, the network planner system 300 may monitor the current or actual grid capacity on a daily basis, and if the available amount of energy 502 fluctuates in the same way every day within a certain percentage of error, then the network planner system 300 may make decisions about , a reasonable estimated availability 502 within the calculated error percentage. For example, if the monitored and recorded available electrical energy 502 fluctuates within 10 MW in the same way each day, then the network planner system 300 can be configured to prevent the projected energy demand of the vehicle systems on the network from sacrificing the electrical energy on the grid at any one time. It is estimated that the available capacity is within 10MW range of 502.

The projected energy demand 410 shown in graph 700 of FIG. 7 is similar to the projected energy demand 410 shown in graph 600 of FIG. 6 , both as a result of modifying the energy usage plan. However, in Exhibit ₇ , energy usage plan 404 requires less power between times _t3 and t4, and plan 402 requires less power between times _t4 and _t5 to prevent projected Energy demand 410 exceeds reduced electrical energy availability 502 . Additionally, between times _t5 and _t7 , both plans 404 and 402 may include instructions that more power is required, and each plan in graph 600 is intended to take advantage of the additional amount of power available 502 on the grid during that time period. The increased area under the curve of projected energy demand 410 between times t ₅ and t ₇ reflects revised plans 404 and 402 .

When the processor 312 of the network planner system 300 (shown in FIG. 3 ) modifies the energy usage plan, the revised energy usage plan and/or associated travel plans may form a network energy consumption plan. The network energy consumption plan details the electrical energy demand of electric vehicles traveling on the network and prevents the cumulative electrical energy demand from exceeding the available amount of electrical energy that may overdraw the grid capacity. Processor 312 (shown in FIG. 3 ) may control communication system 302 (shown in FIG. 3 ) to communicate the modified energy usage plan back to the corresponding electric vehicle, thereby implementing a trip planner system in the electric vehicle. The modified energy usage plan may be communicated wirelessly between communication system 302 on network planner system 300 and communication system 208 on individual electric vehicles 200 (both shown in FIG. 2 ). The revised energy usage plan may include an entire revised trip plan detailing trip instructions such as route, time, operating conditions, and the like. Once the revised energy usage plan is received, electric vehicle 200 may be configured to execute trip commands automatically, or through operator intervention.

The energy usage plan and modified energy usage plan described above detail the specific operating characteristics to be performed on future trips based on the projected energy usage efficiencies and projected electrical energy demands of other electric vehicles traveling on the network. In some cases, the processor 312 of the network planner system 300 cannot modify each energy usage plan, eg due to time constraints. Alternatively, the processor 312 of the network planner system 300 may be configured to transmit instructions to limit the power consumption of electric vehicles without detailing the corresponding plan that follows. For example, such instructions may be communicated to each electric vehicle traveling on the network, the maximum number of electric vehicles that may be required during one or more specific periods. For example, the aforementioned amounts may be allocated based on monitored grid capacity and the number of electric vehicles on the network. The instructions may preferably include allocated electrical energy, which is received by a trip planner system on board the electric vehicle, and the trip planner system may automatically calculate a modified energy usage plan that reduces the trip within the allocated energy demand limits and/or electrical energy required during the stay. The network planner system 300 can send instructions to limit power consumption, for example, when the energy usage plan has underestimated the actual power, which will be needed and require trip re-planning, when other vehicle systems have been attached to the network, in other vehicle systems After having started its journey, when updated data indicates that the demand for electrical energy will exceed the capacity of the grid, and so on.

FIG. 8 is a flowchart of one embodiment of a method 800 of controlling electrical energy demand of vehicles on a network. Method 800 may be performed at least in part by network planner system 300 shown in FIG. 3 and described herein. Method 800 is described in conjunction with network 100 of routes shown in FIG. 1 . At 802, the capacity of the grid 118 is detected. The grid capacity may represent the amount of electrical energy available on the grid 118 that is required by electric vehicles traveling within the vehicle system 108 on the network 100 . Grid capability is detected by measuring at least one of voltage and current on the grid 118 . Preferably, grid capacity may be detected through communication with a power source or other reference that tracks network capacity.

At 804 , the energy demand of the vehicle system 108 traveling on the grid 118 is detected. The energy demand may be the total electrical energy required by vehicle systems 108 traveling on grid 118 at one or more times. The electrical energy requirement may be determined by aggregating or summing the electrical energy requirements of the individual electric vehicles within the vehicle system 108 . For example, projected electrical energy requirements may be determined using various energy usage plans detailing projected energy usage by various vehicle systems 108 on trips traveling on network 100 . Additionally, the actual power required (eg, drawn) may be determined by receiving actual updates from vehicle systems detailing the current power requirements of the network 118 from vehicle to vehicle.

At 806, it is determined whether the energy demand exceeds grid capacity. Demanding electrical energy in excess of the electrical energy available on grid 188 can cause a power outage, or at least a partial outage, within grid 118 and/or cause electric vehicles in vehicle system 108 to stop, causing delays that can affect vehicle system 108 of the entire network. The energy demand may be a projected energy demand for a future time or period of time, and the grid capacity may be a projected grid capacity for the same time or period of time. Method 800 proceeds to 810 if the energy demand exceeds grid capacity.

At 810 , one or more energy usage plans are modified to reduce the electrical energy that is or will be required by the vehicle systems 108 traveling on the network 100 to stay within the level of the available amount of electrical energy on the grid 118 . The energy usage plan may be modified by one or more processors 312 in the network planner system 300 configured to control the movement of electric vehicles so that the energy demands of the electric vehicles do not exceed the amount of electrical energy available on the grid. The network planner system 300 may issue a network energy consumption plan that modifies individual energy usage plans for at least some electric vehicles on the network 100 . The modified energy usage plan may be in communication with the electric vehicle, which executes the energy usage plan while traveling on the trip. The revised energy usage plan may include revised routes, schedules, vehicle configurations, operating instructions, etc., which may form part of the trip plan. Alternatively, or in addition, to modifying the energy usage plan, the network energy consumption plan may allocate the maximum electrical energy, which may be the electrical energy required by the grid 118 by each electric vehicle on the network 100 at the same time or over specific periods of time. The allocated maximum amount can be communicated to the EV, and a trip planner system on the EV can modify the energy usage plan and/or the trip plan on a vehicle-to-vehicle basis to stay within the allocated energy parameters. After modifying the schedule, preventing energy demand from exceeding grid capacity, method 800 loops back to 802 and method 800 is repeated.

Referring again to 806 , if the determined energy demand does not exceed grid capacity, then proceed to 808 of method 800 . At 808, the energy plan is executed since it is determined that there is no risk of exceeding grid capacity. The energy plan may be an energy usage plan determined by a trip planner system on each electric vehicle and/or a network energy consumption plan determined by the network planner system 300 . Execution planning involves communicating with each electric vehicle to complete the trip according to the latest energy usage plan. For example, the executed plan may be a modified energy usage plan that was modified by the network planner system 300 in a loop preceding the method 800 . After the plan is executed, the process of method 800 returns to 802 and method 800 repeats.

One or more embodiments described herein may have the technical effect of the ability to manage the energy consumption of each vehicle system traveling on the network. Managing the energy consumption of each vehicle system may allow for increasing the number of vehicles (eg, vehicle capacity) and/or increasing the size of the vehicle systems based on the same power source. By managing energy consumption, the vehicle capacity on the network can be increased without incurring the high cost of added energy.

In an embodiment, a method (eg, controlling energy demand of a plurality of powered vehicles on a grid) includes monitoring the amount of electrical energy available on the grid to simultaneously power one or more loads. The available amount of electrical energy represents the electrical energy that can be consumed at the same time without exceeding the capacity of the grid. The method also includes monitoring electrical energy requirements of a plurality of electric vehicles traveling on a network of routes, including one or more conductive paths extending along the routes, the routes delivering electrical energy from the grid to the electric vehicles. The method further includes controlling the movement of the electric vehicle such that the electrical energy demand of the electric vehicle does not exceed the amount of electrical energy available on the grid.

In one aspect, monitoring electrical energy demand includes monitoring energy usage plans of individual electric vehicles. The energy usage plan details the electrical energy requirements of the individual electric vehicles along the travel route. Monitoring the electrical energy demand also includes determining a projected electrical energy demand at a future time by summing the electrical energy demand according to the energy usage plan at the future time.

In one aspect, controlling the movement of the electric vehicle includes modifying the energy usage plan based on at least one of trip replanning, additional electric vehicles traveling on the network, or projected energy demand exceeding an available amount of electrical energy at a future time. Controlling the movement of the electric vehicles also includes communicating the modified energy usage plan to the electric vehicles traveling on the network.

In one aspect, the energy usage plan provides instructions for at least one of routing, schedule, vehicle configuration, or mobility characteristics to be performed by the electric vehicles traveling on the network.

In one aspect, controlling the movement of the electric vehicles includes allocating the electric vehicles traveling on the network with a vehicle-specific maximum electrical energy demanded by each electric vehicle from the grid.

In one aspect, based on the maximum amount of electrical energy allocated to each electric vehicle, the electric vehicle generates an energy usage plan for each electric vehicle's travel route.

In one aspect, monitoring the availability of electrical energy includes monitoring the availability of electrical energy on the grid over time.

In one aspect, monitoring the availability of electrical energy includes monitoring the availability of electrical energy on a portion of the grid. Powered by a portion of the grid, the movement of electric vehicles traveling on a sub-network of routes is controlled so that the electrical energy demand does not exceed the amount of electrical energy available for this portion.

In one aspect, controlling the movement of the electric vehicle includes generating a network energy consumption plan. The network energy consumption plan assigns energy consumption parameters to electric vehicles traveling on the network to prevent electric vehicles from exceeding the amount of electric energy available on the grid.

In one embodiment, a network planner system is provided that includes a grid monitoring device and one or more processors. The grid monitoring device is configured to monitor the amount of electrical energy available on the grid simultaneously powering one or more loads. The available amount of electrical energy represents the total amount of electrical energy that can be consumed simultaneously without exceeding the grid capacity. The grid is configured to transfer electrical energy through one or more conductive paths extending along a network of routes on which a plurality of electric vehicles travel for transferring electrical energy to the electric vehicles for powering the electric vehicles. The one or more processors are configured to communicate with the grid monitoring device and the trip planner system on the electric vehicle to control the movement of the vehicle so that the electrical energy demand of the electric vehicle does not exceed the amount of electrical energy available on the grid.

In one aspect, the one or more processors are configured to generate a network energy consumption plan that allocates a specific vehicle's maximum electrical energy that can be demanded by individual electric vehicles traveling on the network to prevent the electric vehicle's electrical energy demand from exceeding that on the grid. The amount of electrical energy available.

In one aspect, the one or more processors are configured to generate a network energy consumption plan that modifies at least one of the route, schedule, vehicle configuration, or mobility characteristics of one or more electric vehicles traveling on the network to Prevent the electrical energy demand of electric vehicles from exceeding the amount of electrical energy available on the grid.

In one aspect, the movement characteristics include velocity, acceleration, position, direction of travel, use of regenerative braking to provide power to the grid, or for temporary consumption use alternative energy sources instead of drawing power from the grid.

In one aspect, one or more electric vehicles that receive modifications to at least one of routes, schedules, vehicle configurations, or mobility characteristics automatically perform the modifications.

In one aspect, the one or more processors are configured to receive a vehicle-specific energy usage plan from a trip planner system, generated by the trip planner system, detailing vehicle-specific energy along a route traveled by each electric vehicle need.

In one aspect, one or more processors are configured to modify one or more power usage plans, re-plan trips based on one or more electric vehicles traveling on the network, additional electric vehicles traveling on the network, or predict The energy demand at the future time exceeds at least one of the available amounts of electrical energy at the future time.

In one aspect, the one or more processors are configured to receive from a trip planner system of an electric vehicle, an energy usage plan of at least one planned route, current energy demand, current operating characteristics, or current route characteristics of each electric vehicle.

In one aspect, the one or more processors instruct a first electric vehicle traveling on the network to enter a first incline at a first time, a second electric vehicle traveling on the network to enter a second incline at a second time, the second The time is different from the first time to distribute the energy demand on the grid according to the time.

In one aspect, an energy demand monitoring device monitors at least one current and projected energy demand of electric vehicles traveling on a network.

In one aspect, at least one electric vehicle is coupled to one or more load vehicles to define a system of vehicles traveling along a route in the network.

In one aspect, the one or more processors communicate wirelessly with the electric vehicle traveling on the network through the communication system.

In one aspect, the electric vehicle can be a rail vehicle and the route is a track.

In one aspect, the amount of electrical energy available on the grid to power the one or more loads is less during peak energy usage hours than during off-peak energy usage hours.

In one aspect, the electrical energy distributed by the one or more processors to each electric vehicle traveling on the network is not equal to the electrical energy of all electric vehicles.

In one embodiment, a network planner system is provided that includes a grid monitoring device, an energy demand monitoring device, and one or more processors. The grid monitoring device is configured to monitor the amount of electrical energy available on the grid simultaneously powering one or more loads. The available amount of electrical energy represents the total amount of electrical energy that can be consumed simultaneously without exceeding the grid capacity. The power demand monitoring device is configured to monitor the power demand of a plurality of electric vehicles traveling on a network of routes, which includes one or more conductive paths extending along the route for transferring power from a power grid to the electric vehicles for driving electric vehicles. car. The one or more processors are configured to control the movement of the vehicle so that the electrical energy demand of the electric vehicle does not exceed the amount of electrical energy available on the grid. The one or more processors are configured to control by at least one of modifying energy usage plans submitted by electric vehicles traveling on the network, or delivering to the electric vehicles the maximum amount of electrical energy each electric vehicle demands from the grid for a particular vehicle The movement of electric vehicles.

It should be understood that the foregoing description is illustrative and not restrictive. For example, the above-described embodiments (and/or aspects thereof) may be used in combination with each other. In addition, various modifications in location and materials of adaptation may be made in light of the teachings of the inventive subject matter without departing from its scope. The sizes and types of materials described herein are intended to define parameters of the inventive subject matter, are not intended to be limiting, and are exemplary embodiments. Many other embodiments will be apparent to those skilled in the art from the above description. The scope of the inventive subject matter should be defined with reference to the appended claims along with the full scope of equivalents to which such claims define. In the appended claims, the terms "comprising" and "in which" are used with the same clear English expression as the corresponding terms "comprising" and "in which". Moreover, in the following claims, the terms "first", "second", and "third", etc. are used for labels only and are not intended to denote numbers on their objects. Moreover, the following claim limitations are not written in a means-plus-function manner, and are not intended to be construed based on 35 U.S.C § 112, paragraph 6, unless the claim limitation employs a statement of function without further structure followed by The expression "means for"

This written description uses examples to describe various embodiments of the inventive subject matter and to enable any person skilled in the art to practice the embodiments of the inventive subject matter, including adopting and using any devices or systems and performing any related methods. The patentable scope of the invention is defined by the claims, and may include other examples that occur to persons of ordinary skill in the art. Such other examples are also within the scope of the claims if they have structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements with insubstantial differences from the literal expressions of the claims. The various embodiments are not limited to the devices and instrumentalities shown in the drawings.

While certain changes may be made in the above-described systems and methods without departing from the spirit and scope of the inventive subject matter encompassed, it is intended that all of the above-described subject matter or subject matter shown in the associated drawings are illustrative only and are not expressive of the scope of the invention. shall constitute a limitation on the subject matter of the present invention.

Claims (20)

1. for the method controlling electrical energy demands, including:

Monitoring is for simultaneously to the available quantity of electric energy on the electrical network of one or more load supplyings, and the described available quantity of electric energy represents Can be consumed simultaneously and be less than the amount of the electric energy of electrical network ability；

The electrical energy demands of multiple electric motor cars that monitoring is traveling on the network of route, the network of described route includes extending along route One or more conductive paths for described electric energy is sent to described electric motor car from electrical network；And

Control the movement of described electric motor car so that the described electrical energy demands of described electric motor car is less than the institute of electric energy on described electrical network State available quantity.

2. method as claimed in claim 1, wherein monitors described electrical energy demands and includes monitoring the energy application plan of each electric motor car, The electrical energy demands that each electric motor car is advanced along route is described in described energy application plan in detail, and by being summarised in future tense Between determine the expected energy demand at future time from the electrical energy demands of energy application plan.

3. method as claimed in claim 2, the movement wherein controlling electric motor car includes replanning based on stroke, adds other electronic Car enters at network uplink, or at least one that anticipated energy requirement is in future time exceedes the available quantity of electric energy is to revise energy Amount application plan；And the energy application plan of amendment is sent to the electric motor car being traveling on network.

4. method as claimed in claim 2, wherein, energy application plan provides and is used for route selection, timetable, vehicle structure, or The instruction of at least one of moving characteristic, to be performed by the electric motor car being traveling on network.

5. method as claimed in claim 1, the movement wherein controlling electric motor car includes each electric motor car to the vehicle of electrical network demand Specific maximum power distributes to the electric motor car entered at network uplink.

6. method as claimed in claim 5, wherein based on distributing to the maximum power of each electric motor car, electric motor car generates each electricity The energy application plan of motor-car course.

7. method as claimed in claim 1, wherein monitor the available quantity of electric energy include monitoring on electrical network the available quantity of electric energy relative to The change of time.

8. method as claimed in claim 1, wherein monitors the available quantity of electric energy and includes monitoring electric energy available on a part of electrical network Amount, and control the movement of electric motor car in the sub-network being traveling in route powered by this part electrical network so that electrical energy demands is not Exceed the available quantity of electric energy in this part.

9. method as claimed in claim 1, the movement wherein controlling electric motor car includes creating network energy consumption plan, network energy The electric motor car that energy expenditure parameter is distributed to be traveling on network by consumption plan is to prevent electric motor car from exceeding electric energy on electrical network Available quantity.

10. a network planner system, including:

Power network monitoring equipment, it is configured to monitor the available of on electrical network to one or more load supplyings simultaneously electric energy Amount, the described available quantity of electric energy represent can be consumed simultaneously and less than the amount of electric energy of electrical network ability；Described electrical network is configured to Electric energy is transmitted for passing by one or more conductive paths of the Network stretch of the route traveled over along multiple electric motor cars Giving electric motor car to power electric motor car, electric motor car has vehicle-mounted stroke planner system；And

One or more processors, it is configured to communicate with the stroke planner system in power network monitoring equipment and electric motor car To control the movement of electric motor car so that the electrical energy demands of electric motor car is less than the available quantity of electric energy on electrical network.

11. network planner systems as claimed in claim 10, wherein one or more processors are configured to create network energy Amount consumes plan, its distribution can the specific maximum power of vehicle of each electric motor car demand by being traveling on network, with The electrical energy demands preventing electric motor car exceedes the available quantity of electric energy on electrical network.

12. network planner systems as claimed in claim 10, wherein one or more processors are configured to create network energy Amount consumes plan, the route of one or more electric motor cars that its amendment is traveling on network, timetable, vehicle structure, or mobile At least one in feature, to prevent the electrical energy demands of electric motor car from exceeding the available quantity of electric energy on electrical network.

13. network planner systems as claimed in claim 12, at least one during wherein moving characteristic includes as follows: speed Degree, acceleration, position, direct of travel, use regenerative braking to provide electric energy for electrical network, or in order to consume use alternative energy source immediately Rather than draw electric energy from electrical network.

14. network planner systems as claimed in claim 12, wherein receive route, timetable, vehicle structure, or move One or more electric motor cars of the amendment of at least one in feature automatically carry out described amendment.

15. network planner systems as claimed in claim 10, wherein one or more processors are configured to reception to be come voluntarily Journey planner system by the vehicle specific energy application plan of stroke planner system creation, its describe in detail each electricity The specific energy requirement of vehicle that motor-car is advanced along route.

16. network planner systems as claimed in claim 15, wherein one or more processors are configured to based on being traveling in The stroke of the one or more electric motor cars on network is replanned, and other electric motor car additional enters at network uplink, or anticipated electricity The energy requirement of motor-car future time exceed at least one in the available quantity of the electric energy of future time revise one or Multiple energy application plans.

17. network planner systems as claimed in claim 10, wherein one or more processors are configured to receive from electricity The energy application plan of at least one plan route of stroke planner system on motor-car, for the proposition of each electric motor car Route, current energy demand, current operation feature, or current route feature.

18. network planner systems as claimed in claim 10, wherein electric motor car is rail vehicle, and route is track.

19. network planner systems as claimed in claim 10, wherein for one or more load supplyings on electrical network The available quantity of electric energy is fewer than during the non-peak energy use time during the peak energy use time.

20. 1 kinds of network planner systems, including:

Power network monitoring equipment, it is configured to monitor simultaneously for the available quantity of electric energy on the electrical network of one or more load supplyings, electricity Can available quantity represent can be consumed simultaneously and less than the amount of electric energy of electrical network ability；

Energy requirement monitoring device, its electrical energy demands being configured to monitor the multiple electric motor cars on the network being traveling in route, should The network of route includes one or more conductive path extended along route, for electric energy is sent to electric motor car with right from electrical network Electric motor car is powered；And

One or more processors, its movement being configured to control electric motor car so that the electrical energy demands of electric motor car is less than electrical network The available quantity of upper electric energy, wherein, one or more processors are configured through revising and are submitted to by the electric motor car being traveling on network Energy application plan, and/or send each electric motor car to electric motor car to the specific maximum power of vehicle of electrical network demand Control the movement of electric motor car.