TW201445159A - A method for vehicle's battery size estimation - Google Patents

Abstract

A method for vehicle's battery size estimation comprises a consumption estimating step, a cost estimating step and a battery's size searching step. The method of the steps computes a cost data for a vehicle with a fixed path, a fixed time and a fixed running number. The optimal battery's size computed by cost data can be reducing the total cost.

Description

Vehicle battery capacity estimation method

The present invention relates to a method for estimating the capacity of a vehicle battery, and more particularly to an estimation method for estimating the cost of a vehicle having different battery capacities to determine the battery capacity of the vehicle.

In response to the trend of environmental protection, the world is not committed to energy conservation and carbon reduction research. Because electric vehicles have the advantages of low noise and no carbon emissions during operation, they have become the focus of global research in recent years. Among them, electric vehicles are promoted to mass transportation, and electric buses are used to replace traditional diesel buses. In many countries, There are years to go.

For the implementation of electric buses, operating costs have always been the primary consideration, especially the cost of battery purchase, charging and replacement. In general, the electric power source of the electric bus is provided by the battery to be mounted, and in order to cope with the long-term operation of the electric bus, the battery mounted on the electric bus is generally a large-capacity battery. However, the size of the battery capacity directly reflects the initial purchase cost, that is, the larger the battery capacity, the higher the purchase cost.

If a small-capacity battery is selected in order to reduce the purchase cost, if the small-capacity battery cannot afford the power consumed by a complete driving, and must be charged multiple times in one full driving, the charging cost will increase. In addition, excessive charging and discharging of the small-capacity battery tends to affect the cycle life of the small-capacity battery, so that the cycle life of the small-capacity battery is reduced, and the replacement cost is also increased.

Therefore, for an electric bus with a fixed driving route, a better battery capacity estimation method must be provided to estimate the relative cost of each battery of different capacity and find the battery capacity corresponding to the lowest cost.

The main object of the present invention is to provide a method for estimating the capacity of a vehicle battery, which can estimate the relative cost of a vehicle carrying different batteries of different capacities, and find the battery capacity corresponding to the lowest cost, thereby reducing the overall cost.

In order to achieve the foregoing object, the present invention provides a method for estimating a capacity of a vehicle battery, comprising: an energy estimating step, which is an energy algorithm of a processor, estimating that a vehicle body travels once on a fixed route, and the number of loadings is A plurality of batteries of different capacities are used as a power consumption data; a cost estimating step is performed by the processor to input the power consumption data into a cost equation, and within a battery capacity interval, Estimating the plurality of integrated cost values of the plurality of batteries of different capacities under the fixed route, a fixed time and a fixed number of operations as a cost data; and a battery capacity searching step One of the processors searches for an algorithm, and searches for an output battery capacity based on the cost data, the output battery capacity is located in the battery capacity interval, and the vehicle body is in the fixed route, the fixed time, and the fixed number of operations The battery capacity corresponding to the lowest overall cost value.

The method for estimating the capacity of a vehicle battery according to the present invention, wherein the battery capacity interval is between a low boundary value and a high boundary value, and before performing the cost estimation step, a low boundary value determining step is performed first. The processor selects the low boundary value according to the energy consumption data, and the low boundary value is greater than the total power consumption of the vehicle body when the vehicle body completes one driving on the fixed route.

The method for estimating the capacity of a vehicle battery according to the present invention, wherein the energy algorithm performs an energy equation by a Monte Carlo loop, the energy equation is as follows: E _avg = 0.064. E _bat + E _o where E _{avg is} the combined power consumption, E _{bat is} the battery capacity, and E _o is a basic power consumption.

The method for estimating the capacity of a vehicle battery according to the present invention, wherein the cost equation is as follows: f ( E _bat )= C ^I + C ^M + C ^O

C ^I = E _bat . C _bat

among them, Where f ( E _bat ) represents the combined cost value, C ^I represents an additional purchase cost, C ^M represents a replacement cost, C ^O represents a charging cost, C _bat represents a unit cell capacity, and N _bus represents The number of vehicles, T represents an estimated total time, η represents a discount rate, N _run represents the number of times the vehicle is operated annually, and C _e represents an electricity bill.

The method for estimating the capacity of a vehicle battery according to the present invention, wherein the search algorithm is a golden ratio search method.

S1‧‧‧ Energy Estimation Steps

S2‧‧‧ low boundary value decision step

S3‧‧‧ Cost Estimation Steps

S4‧‧‧Battery capacity search procedure

L1~L4‧‧‧ Curve

Fig. 1 is a flow chart showing the method for estimating the capacity of the vehicle battery of the present invention.

Figure 2: Experimental data plot of the cost data of the present invention.

The above and other objects, features and advantages of the present invention will become more <RTIgt; And "battery capacity" refers to the maximum amount of stored electricity that a battery can contain according to its own size, and the unit of that amount of electricity is kilowatt-hours (KWH).

Please refer to FIG. 1 , which is a flow chart of the vehicle battery capacity estimation method of the present invention. The diagram includes an energy estimation step S1, a low boundary value decision step S2, a cost estimation step S3, and a battery capacity search step S4.

The energy estimation step S1 is estimated by an energy algorithm of a processor. A vehicle body travels once on a fixed route, and a plurality of integrated power consumptions of a plurality of batteries of different capacities are used as a power consumption data. The processor can be a computer or any computing processor, and can execute an operation equation or a simulation software to perform related operations and statistics. In this embodiment, the processor is provided with a Matlab. Software computer.

More specifically, for the vehicle body having a fixed route, the comprehensive power consumption consumed during the driving process includes, in addition to one of the basic power consumption consumed by the vehicle body running on the fixed route, One of the additional power consumption consumed by transporting the battery, and the larger the capacity of the battery, the heavier the battery itself, and the relative power consumption is relatively increased. Therefore, when the capacity of the battery mounted on the vehicle body is larger, the overall power consumption consumed by the vehicle body to travel once on the fixed route is higher. The battery capacity is a function of the overall power consumption and has an energy equation which can be derived from statistical data in conjunction with linear regression and is expressed as follows: E _avg =0.064. E _bat + E _o (1)

Among them, E _{avg is} the comprehensive power consumption, E _{bat is} the battery capacity, and E _{o is} the basic power consumption, and the unit is kilowatt hour (KWH).

In this embodiment, the energy algorithm performs the energy equation by a Monte Carlo loop, and thereby estimating that the vehicle body travels once on the fixed route, and each of the batteries with different capacities is separately consumed. A plurality of comprehensive power consumptions, and the plurality of comprehensive power consumptions are used as the power consumption data. Accordingly, through the energy estimating step S1, it is possible to more accurately estimate the respective power consumption of the vehicle body in which the batteries of different capacities are mounted, and thereby accurately estimate the cost required to load the batteries of different capacities.

Before performing the cost estimation step S3, it is preferred to perform the low boundary value first. Decision step S2. The low boundary value determining step S2 is performed by the processor to select a low boundary value according to the energy consumption data, and the low boundary value is greater than the total power consumption of the vehicle body when the vehicle body completes a driving on the fixed route. .

In more detail, in order to estimate the cost of batteries with different capacities, it is necessary to First define a battery capacity interval and perform related operations within the battery capacity interval. And the battery capacity interval is between the low boundary value and a high boundary value, wherein the low boundary value and the high boundary value are one positive integer greater than 0, and the high boundary value is greater than the low boundary value. In addition, in the cost estimating step S3 of the present invention, the battery that cannot provide the power consumption required for a complete driving is regarded as the battery to be replaced, and the replacement cost represented by the battery capacity is increased, so when the battery is used When the capacity is too small and can never provide the power consumption required for a complete drive, the overall cost of the battery will increase, and will be greater than other larger capacity batteries. Accordingly, the low boundary value determining step S2 is such that the low boundary value is greater than the minimum consumed power consumption to remove unnecessary estimation intervals, thereby reducing computation time and complexity.

The cost estimating step S3 is performed by the processor to input the power consumption data a cost equation, and estimating, within the battery capacity interval, a plurality of integrated cost values of the plurality of batteries of different capacities under the fixed route, a fixed time, and a fixed number of operations, as a Cost information.

In a preferred embodiment of the invention, the integrated cost value includes a purchase cost, a replacement cost, and a charging cost. The purchase cost is the cost required to initially purchase the battery; the replacement cost is the cost of purchasing the next battery to replace the initially purchased battery; the charging cost is the cost required to charge the battery. The integrated cost value can be obtained by combining the power consumption data with the cost equation, wherein the cost equation is expressed as follows: f ( E _bat )= C ^I + C ^M + C ^O (2)

C ^I = E _bat . C _bat (3)

among them,

Where f ( E _bat ) represents the combined cost value, C ^I represents the purchase cost, C ^M represents the replacement cost, C ^O represents the charging cost, and C _bat represents the cost per unit battery capacity (yuan/KWH) N _bus represents the number of vehicles, T represents the estimated total time (year), η represents the discount rate (%), that is, the current cost and the rate of change after the year t, and N _run represents the annual operation of the body. The number of times, C _e represents the electricity fee (yuan / KWH).

To more clearly explain the cost estimation step S3, the following details are explained in an embodiment with experimental data. In this embodiment, if the number of the vehicle body (N _bus =1) is to be calculated on the fixed route for ten years (T=10), the cost of the battery with different capacities is assumed, and the body is assumed to be daily. It is necessary to travel six times on the fixed route. The number of fixed operations is 365×6×10=21900 (N _run =21900). If the basic power consumption consumed on the fixed route is 45.6KWH ( E _o = 45.6), with the energy equation (1 the amount) is calculated from the consumption data, and as to the lower limit value 110KWH to 500KWH high as the boundary value at which η = 3, C _bat = 14000 and C Under the condition of _e = 3.5, several comprehensive cost values can be obtained as the cost data, as shown in Fig. 2.

The curve L1 of the second figure is a plurality of purchase costs relative to a plurality of battery capacities between the low boundary value and the high boundary value, and when the battery capacity increases, the purchase cost is also Rise. The curve L2 of FIG. 2 is a plurality of replacement costs corresponding to a plurality of battery capacities between the low boundary value and the high boundary value, and when the battery capacity is about 320 KWH, during driving within ten years, Even if the maximum storage power is attenuated due to continuous charge and discharge, It can provide the power consumption required for a complete driving, so the replacement cost is 0 when the battery capacity is above 320KWH. The curve L3 of FIG. 2 is a plurality of charging costs relative to a plurality of battery capacities between the low boundary value and the high boundary value, and when the battery capacity increases, the overall power consumption increases slightly. The charging cost also increased slightly. The curve L4 of the second figure is a plurality of integrated cost values corresponding to the plurality of battery capacities between the low boundary value and the high boundary value, and the plurality of integrated cost values are relative to the purchase cost, The sum of the replacement cost and the charging cost is taken as the cost data. In addition, the cost data may be any data display type, such as a data data or a relationship curve as disclosed in the embodiment, and is not limited herein. Accordingly, the cost estimating step S3 can separately calculate the purchase cost, the replacement cost, and the charging cost, and accurately estimate the number of batteries of the vehicle body under the fixed route, the fixed time, and the fixed number of operations. A number of integrated cost values relative to capacity.

The battery capacity searching step S4 is to search for an algorithm by one of the processors, and search for an output battery capacity according to the cost data, the output battery capacity is located in the battery capacity interval, and the vehicle body is in the fixed route, The battery capacity corresponding to the fixed time and the lowest integrated cost value under the fixed number of operations.

The search algorithm can be any known algorithm for searching for the minimum value, and is not limited herein. Please refer to FIG. 2 again. In this embodiment, a golden section search method is used. The search process of the golden ratio search method is a conventional technique, and will not be described here. The golden ratio search method can search the relationship curve of the cost data, and find that the lowest comprehensive cost value is 6493900 yuan, and the battery capacity corresponding to the lowest integrated cost value is 133KWH, therefore, the The output battery capacity is 133KWH. Therefore, it can be seen that in the battery capacity interval defined in this embodiment, and in the fixed route ( E _o = 45.6), the fixed time (T=10), and the fixed number of operations (N _run = 21900), When the battery capacity of the vehicle body is 133 KWH, the combined cost is the lowest. Therefore, the battery with a battery capacity of 133 KWH is the most suitable for the above-mentioned operating conditions. According to this, the battery capacity searching step S4 can accurately output the battery capacity corresponding to the lowest comprehensive cost value of the vehicle body under the fixed route, the fixed time and the fixed operation number, to estimate the most suitable for the vehicle body. battery capacity.

In summary, the present invention is directed to the vehicle body having a fixed route, estimating the purchase cost, the replacement cost, and the charging cost generated by the battery of different capacities, and using the sum of the above costs as the comprehensive cost value. And find the battery capacity corresponding to the lowest integrated cost value to estimate the battery capacity that is most suitable for the vehicle body, thereby achieving the overall cost reduction effect.

While the invention has been described in connection with the preferred embodiments described above, it is not intended to limit the scope of the invention. The technical scope of the invention is protected, and therefore the scope of the invention is defined by the scope of the appended claims.

S1‧‧‧ Energy Estimation Steps

S2‧‧‧ low boundary value decision step

S3‧‧‧ Cost Estimation Steps

S4‧‧‧Battery capacity search procedure

Claims (5)

A method for estimating the capacity of a vehicle battery includes: an energy estimation step, which is an energy algorithm of a processor, which estimates that a vehicle body travels once on a fixed route, and a plurality of batteries of different capacities are mounted. The integrated power consumption is used as a power consumption data; a cost estimating step is performed by the processor inputting the power consumption data into a cost equation, and estimating the vehicle body in the fixed route within a battery capacity interval A fixed time and a fixed number of operations, a plurality of integrated cost values of a plurality of batteries of different capacities are used as a cost data; and a battery capacity searching step is performed by one of the processors searching for an algorithm according to The cost data searches for an output battery capacity, and the output battery capacity is located in the battery capacity interval, and is a battery corresponding to the lowest integrated cost value of the vehicle body under the fixed route, the fixed time, and the fixed operation number. capacity. The method according to claim 1, wherein the battery capacity interval is between a low boundary value and a high boundary value, and a low boundary value decision is performed before the cost estimating step is performed. In the step, the processor selects the low boundary value according to the energy consumption data, and the low boundary value is greater than the total power consumption of the vehicle body when the vehicle body completes a driving on the fixed route. According to the method for estimating the capacity of a vehicle battery according to claim 1, wherein the energy algorithm performs an energy equation by a Monte Carlo loop, the energy equation is as follows: E _avg =0.064. E _bat + E _o where E _{avg is} the combined power consumption, E _{bat is} the battery capacity, and E _o is a basic power consumption. According to the method for estimating the capacity of the vehicle battery according to item 1 of the patent application scope, the cost equation is as follows: f ( E _bat ) = C ^I + C ^M + C ^O C ^I = E _bat . C _bat among them, Where f ( E _bat ) represents the combined cost value, C ^I represents an additional purchase cost, C ^M represents a replacement cost, C ^O represents a charging cost, C _bat represents a unit cell capacity, and N _bus represents The number of vehicles, T represents an estimated total time, η represents a discount rate, N _run represents the number of times the vehicle is operated annually, and C _e represents an electricity bill. According to the method for estimating the capacity of a vehicle battery according to item 1 of the patent application scope, the search algorithm is a golden ratio search method.