CN112937303A - Real-time online early warning method and system after battery overheating - Google Patents
Real-time online early warning method and system after battery overheating Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L3/00—Electric devices on electrically-propelled vehicles for safety purposes; Monitoring operating variables, e.g. speed, deceleration or energy consumption
- B60L3/0023—Detecting, eliminating, remedying or compensating for drive train abnormalities, e.g. failures within the drive train
- B60L3/0046—Detecting, eliminating, remedying or compensating for drive train abnormalities, e.g. failures within the drive train relating to electric energy storage systems, e.g. batteries or capacitors
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L58/00—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles
- B60L58/10—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries
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Abstract
The invention discloses a real-time online early warning method and a real-time online early warning system after a battery is overheated, wherein the method comprises the following steps of S1: acquiring signal data of a vehicle battery in real time; s2: preprocessing data; s3: calculating and finding out the variation difference of the signal data through a distributed real-time calculation engine; s4: judging the battery overheating abnormal condition; s5: finding out a vehicle with an overheated battery according to the battery overheating strategy engine; s6: and according to the result of S5, carrying out overheating real-time alarm on the overheated vehicle. The method utilizes a big data distributed real-time computing technology, processes and analyzes signal data in multiple angles and parameters, and quickly finds out internal factors influencing battery overheating; the battery overheating abnormity of the vehicle is monitored in real time through the constructed battery overheating judgment strategy, the vehicle which is about to occur or is in the battery overheating state is found in time, and the vehicle is directionally reported in real time, so that the safety accidents of battery life decline, vehicle fire and the like caused by battery overheating are avoided.
Description
Technical Field
The invention relates to a battery overheating monitoring technology, in particular to a real-time early warning technology after battery overheating.
Background
The battery is the core power of the new energy electric automobile and becomes the main research object of each large manufacturer. Lithium ion batteries are widely used in new energy electric vehicles due to their high energy density, high power density, and low self-discharge characteristics. With the rapid development of science and technology, lithium ion batteries have basically met the daily requirements of people for battery energy density. However, there are still many bottlenecks to the life and safety of the battery, which also limits the performance of the new energy electric vehicle.
Based on the characteristics of lithium ion batteries, the main reaction and the side reaction of various reaction rates inside the battery are related to temperature, which is one of important factors affecting the life and safety of the battery. The higher the temperature, the faster the rate of side reactions. If the battery exceeds a certain temperature, battery aging is accelerated and further self-heating may be triggered, resulting in thermal runaway of the battery and serious dangerous conditions that may result in battery fire or explosion. This is a serious threat to new energy electric vehicle users and people around them. Therefore, the battery overheating monitoring and early warning device has great significance for effective monitoring and early warning of battery overheating.
However, in the existing monitoring scheme for battery overheating, the battery temperature is monitored only through a battery temperature sensor, and an alarm is given when the temperature continuously rises or exceeds a certain threshold value. However, overheating of the battery is generally associated with a number of factors and is complex and varied. The scheme for monitoring the battery overheating is only used for monitoring the battery temperature, is too single, cannot reflect the internal reason of the battery overheating, and is low in accuracy. And the battery overheating cannot be predicted in advance, so that the time for corresponding personnel to process the battery overheating is influenced.
Disclosure of Invention
The invention aims to establish a real-time online early warning method and a real-time online early warning system after battery overheating, which utilize a big data distributed real-time computing technology and an autonomously constructed battery overheating judgment strategy to monitor the vehicle battery overheating abnormity in real time and send out an alarm in time when the vehicle battery is overheated, thereby avoiding safety accidents and serious loss caused by battery overheating.
In order to achieve the above object, the present invention proposes the following technical solutions.
One of the purposes of the invention is to provide a real-time online early warning method after a battery is overheated, which comprises the following steps:
s1: and acquiring signal data of the vehicle battery in real time.
The signal data specifically comprises a frame number, a single battery voltage, a temperature, a total voltage, a total current, an insulation resistance, a charging state, a fault grade and a fault code.
S2: and (4) preprocessing data.
The purpose of the step is that abnormal data exists in the signal data acquired in real time, and the preprocessing mainly includes rejection and noise reduction of the acquired signal data.
S3: and calculating and finding out the variation difference of the signal data through a distributed real-time calculation engine.
The purpose of this step is to use big data distributed real-time computing technology, and the signal data is processed and analyzed in multiple angles and multiple parameters, and internal factors influencing battery overheating are quickly found out.
S4: and judging the battery overheating abnormal condition.
S5: and finding out the vehicle with the overheated battery according to the battery overheating judgment strategy.
S6: and according to the result of S5, carrying out overheating real-time alarm on the overheated vehicle.
Further, the data preprocessing of step S2 includes the following steps:
s2-1: checking the acquired cell signal data such as cell voltage, temperature, total voltage, total current, insulation resistance and the like, and whether abnormal data such as null values, exceeding normal intervals and the like exist;
s2-2: carrying out validity check on the vehicle VIN, the terminal time, the rechargeable energy storage subsystem voltage information list, the monomer voltage list and the highest temperature value data;
s2-3: and cleaning and filtering abnormal data detected in S2-1 and S2-2.
Through the data preprocessing, abnormal data are eliminated while the data integrity is guaranteed, and the data quality is improved. Further, the step S3 specifically includes the following steps:
s3-1: the processed data is consumed in real time by the S2 process using a distributed real-time computing engine.
The distributed real-time computing engine can adopt a Flink, Storm, Spark Streaming and other distributed real-time computing engines.
S3-2: and detecting whether the received signal data is within t seconds continuously, wherein t is more than or equal to 20 and less than or equal to 40.
S3-3: calculating the difference value of the temperature of the battery at different moments in ntThe temperature difference value at each continuous moment and the maximum temperature value of the battery, wherein n is more than or equal to 3t≤10。
S3-4: calculating the voltage difference value of the single cell voltage at different moments, the last moment voltage value of the single cell voltage in t seconds continuously, and the single cell voltage nu1Difference value of each continuous time and monomer voltage of nu2Difference value of each successive time, wherein n is more than or equal to 1u1≤6、8≤nu2≤10。
The difference values of the battery temperature and the single voltage at different continuous moments can represent the abnormal conditions such as internal short circuit and the like in the single battery. The larger the difference value is, the larger the probability of abnormality occurring inside the battery cell is. Variables t, nt、nu2Values are taken within respective value ranges according to the performance of actual data statistics.
Since battery overheating can be determined by various factors including ambient temperature, battery heat capacity, battery thermal conductivity, battery heat generation, TMS heating system, etc., the reasons for this are complex and varied. In the step, BMS signals such as real-time voltage, temperature and resistance of the battery are acquired by utilizing a big data real-time stream data processing technology, and signal data are processed and analyzed in multiple angles and parameters by utilizing a big data distributed real-time computing technology, so that internal factors influencing battery overheating can be quickly found.
Further, the step S4 specifically includes the following steps:
s4-1: judging whether signal data of the battery BMS are received in real time within t seconds, wherein t is more than or equal to 20 and less than or equal to 40;
s4-2: judging whether the vehicle is in the running, charging or standing process according to the charging state signal;
s4-3: judging the temperature of the battery and continuously nt1Continuous rising value of the maximum temperature of the battery at each moment and continuous nt2Maximum value and consecutive n of temperature difference at each momentu1Whether the voltage difference value of the single battery at each moment exceeds or is lower than a corresponding threshold value or not; wherein 2 is not more than nt1、nt2≤10、1≤nu1≤5；
S4-4: judging n is continuousu2The voltage difference value of the single battery at each moment, the last moment voltage value of the single battery and n continuousu3The voltage difference value of the previous moment when the voltage continuously drops at each moment is continuously nt3Whether the maximum value of the battery temperature difference at each moment exceeds or is lower than a corresponding threshold value, wherein n is more than or equal to 2u2、nu3≤10、5≤nt3≤10；
In the above steps, the parameters t and nt1、nt2、nt2And nu1、nu2、nu3Values are taken within respective value ranges according to the performance of actual data statistics.
Further, the step S5 is to find the vehicle about to be or in which the battery overheat occurs in time through the battery overheat judging strategy constructed in the step S4, and includes the following steps:
s5-1: checking S4-1, S4-2 and S4-3 in the process of S4 to judge whether the conditions are simultaneously satisfied;
s5-2: checking S4-1, S4-2 and S4-4 in the process of S4 to judge whether the conditions are simultaneously satisfied;
s5-3: if one of the processes S5-1 and S5-2 is established at the same time, the vehicle is in an overheating abnormality.
The invention further aims to provide a real-time online early warning system after the battery is overheated, which is used for realizing the method and comprises the following steps:
the data acquisition module is used for acquiring signal data of the vehicle battery in real time;
a preprocessing module: preprocessing the data;
the calculation module calculates and finds out the change difference of the signal data through a distributed real-time calculation engine;
the judging module is used for judging the battery overheating abnormal condition;
the identification module identifies a vehicle with an overheated battery according to the battery overheating strategy engine;
and the alarm module is used for giving an alarm for overheating of the overheated vehicle in real time.
According to the technical scheme, the large data distributed real-time computing technology is utilized, the signal data are processed and analyzed in multiple angles and parameters, and the internal factors influencing battery overheating are quickly found out; the battery overheating abnormity of the vehicle is monitored in real time through the constructed battery overheating judgment strategy, the vehicle which is about to occur or is in the process of battery overheating is found in time, and the vehicle is directionally reported in real time, so that corresponding personnel can rapidly conduct actions, and safety accidents such as battery service life decline, vehicle fire and the like and even more serious loss caused by battery overheating are avoided.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the embodiments of the invention without limiting the embodiments of the invention. In the drawings:
FIG. 1 is a schematic diagram of a real-time online early warning method after a battery is overheated according to an embodiment of the invention.
Detailed Description
The invention is further described with reference to the accompanying drawings in which:
referring to fig. 1, the embodiment provides a real-time online early warning method after a battery is overheated, and the method includes the following specific steps:
s1: and acquiring signal data of the vehicle battery in real time.
The collected signals include, but are not limited to, cell signal data such as cell voltage, temperature, total voltage, total current, insulation resistance, etc.
S2: preprocessing data;
in a further embodiment, step S2 may include the steps of:
s2-1: and checking the acquired cell signal data such as cell voltage, temperature, total voltage, total current, insulation resistance and the like, and whether abnormal data such as null values, exceeding normal intervals and the like exist.
S2-2: and carrying out validity check on the vehicle VIN, the terminal time, the rechargeable energy storage subsystem voltage information list, the single voltage list and the highest temperature value data.
S2-3: and cleaning and filtering abnormal data detected in S2-1 and S2-2.
S3: and calculating and finding out the variation difference of the signal data through a Flink distributed real-time calculation engine.
In a further embodiment, step S3 may include the steps of:
s3-1: consuming the processed data of the S2 process in real time by using the Flink;
s3-2: detecting whether the received signal data is within 30 seconds;
s3-3: and calculating the difference value of the temperature of the battery at different moments, the difference value of the temperature at 5 continuous moments and the maximum temperature value of the battery.
Wherein the temperature difference value (temp delta) is equal to the temperature value (temp) at the current momentt) Subtract the temperature value (temp) at the previous momentt-1)：
tempΔ＝tempt-tempt-1
Wherein t represents the current time and t-1 represents the last time.
S3-4: and calculating the voltage difference value of the single battery at different moments, the voltage value of the single battery at the last moment, the voltage difference value of the single battery at 2 continuous moments and the voltage difference value of the single battery at 5 continuous moments.
Wherein the cell voltage difference value (vol delta) is equal to the cell voltage value (vol delta) at the current momentt) Subtract the cell voltage value (vol) at the previous timet-1)：
volΔ＝volt-volt-1
Wherein t represents the current time and t-1 represents the last time.
S4: and judging the battery overheating abnormal condition.
In a further embodiment, step S4 may include the steps of:
s4-1: judging whether signal data of the battery BMS is received in real time within 30 seconds;
s4-2: judging whether the vehicle is in the running, charging or standing process according to the charging state signal;
the charging signal is used for judging the vehicle state, and the specific steps are as follows:
vehicle running or standing state: charging is 3.
Vehicle charging or rest state: charging 1 or charging 4.
S4-3: judging whether the battery temperature, the continuous rising value of the highest battery temperature at 5 continuous moments, the maximum value of the temperature difference at 5 continuous moments and the voltage difference value of the battery monomer at 2 continuous moments exceed or are lower than corresponding threshold values;
further, the specific steps of the determination rule in step S4-3 are as follows:
s4-3-1: checking whether the temperature of the battery is more than 55 ℃;
s4-3-2: checking whether the continuous rising value of the battery temperature is more than or equal to 1 ℃ at 5 continuous moments;
s4-3-3: checking whether the maximum value of the battery temperature difference at 5 continuous moments is greater than or equal to 1 ℃;
s4-3-4: checking whether the voltage difference value of the battery monomer is less than or equal to-1 mV at 2 continuous moments;
s4-3-5: the judgment condition of the S4-3 process is shown to be satisfied when the conditions of S4-3-1, S4-3-2, S4-3-4, S4-3-1, S4-3-3 and S4-3-4 are combined to be satisfied at the same time.
S4-4: and judging whether the voltage difference value of the battery monomer at 5 continuous moments, the voltage value of the battery monomer at the last moment, the voltage difference value before the voltage continuously drops at 5 continuous moments, and the maximum value of the battery temperature difference at 4 continuous moments exceed or are lower than corresponding threshold values.
Further, the specific steps of the determination rule in step S4-4 are as follows:
s4-4-1: checking whether the voltage difference value of the battery monomer is less than or equal to-1 mV at 5 continuous moments;
s4-4-2: checking whether the last voltage of the single battery is more than or equal to 150 mV;
s4-4-3: checking whether the voltage difference value of the previous moment is more than or equal to 150mV when the voltage continuously drops at 5 continuous moments;
s4-4-4: checking whether the maximum value of the battery temperature difference at 4 continuous moments is greater than or equal to 1 ℃;
s4-4-5: if the conditions of combination of S4-4-1, S4-4-2, S4-4-3, S4-4-1, S4-4-2 and S4-4-4 are simultaneously satisfied, the judgment condition of the S4-4 process is satisfied.
S5: and finding out the vehicle with the overheated battery according to the battery overheating judgment strategy.
S5-1: checking S4-1, S4-2 and S4-3 in the process of S4 to judge whether the conditions are simultaneously satisfied;
s5-2: checking S4-1, S4-2 and S4-4 in the process of S4 to judge whether the conditions are simultaneously satisfied;
s5-3: if one of the processes S5-1 and S5-2 is established at the same time, the vehicle is in an overheating abnormality.
S6: and according to the result of S5, carrying out overheating real-time alarm on the overheated vehicle.
The further embodiment of the invention is a real-time online early warning system after battery overheating, which comprises the following module units:
1. and the data acquisition module is used for acquiring the signal data of the vehicle battery in real time.
2. A preprocessing module: the data is pre-processed.
The preprocessing module is specifically configured to perform the specific method of step S2 in the above method.
3. And the calculation module calculates and finds out the change difference of the signal data through a distributed real-time calculation engine.
The calculation module implements the specific process of step S3 in the above method.
4. And the judging module is used for judging the battery overheating abnormal condition.
The determination module is configured to implement the specific process of S4 in the above method.
5. The identification module identifies a vehicle with an overheated battery according to the battery overheating strategy engine.
The identification module is configured to embody a specific procedure of S5 in the above method.
6. And the alarm module is used for giving an alarm for overheating of the overheated vehicle in real time.
The real-time online early warning system after the battery is overheated has the same technical effect as the method, and the detailed description is omitted.
Although the embodiments of the present invention have been described in detail with reference to the accompanying drawings, the embodiments of the present invention are not limited to the details of the above embodiments, and various simple modifications can be made to the technical solutions of the embodiments of the present invention within the technical idea of the embodiments of the present invention, and the simple modifications all belong to the protection scope of the embodiments of the present invention.
Claims (10)
1. A real-time online early warning method after battery overheating is characterized by comprising the following steps:
s1: acquiring signal data of a vehicle battery in real time;
s2: preprocessing data;
s3: calculating and finding out the variation difference of the signal data through a distributed real-time calculation engine;
s4: judging the battery overheating abnormal condition;
s5: finding out a vehicle with an overheated battery according to the battery overheating strategy engine;
s6: and according to the result of S5, carrying out overheating real-time alarm on the overheated vehicle.
2. The real-time online early warning method for the overheated battery of claim 1, wherein the signal data of step S1 includes a frame number, a cell voltage, a temperature, a total voltage, a total current, an insulation resistance, a charging state, a fault level and a fault code;
the step S2 includes the following steps:
s2-1: checking whether acquired cell signal data such as cell voltage, temperature, total voltage, total current, insulation resistance and the like have abnormal data such as null values, exceeding normal intervals and the like;
s2-2: carrying out validity check on the vehicle VIN, the terminal time, the rechargeable energy storage subsystem voltage information list, the monomer voltage list and the highest temperature value data;
s2-3: and cleaning and filtering abnormal data detected in S2-1 and S2-2.
3. The real-time online early warning method for the overheated battery according to claim 1, wherein the step S3 comprises the following steps:
s3-1: consuming the processed data of the S2 process in real time by using a distributed real-time computing engine;
s3-2: detecting whether the received signal data are within t seconds continuously, wherein t is more than or equal to 20 and less than or equal to 40;
s3-3: calculating the difference value of the temperature of the battery at different moments in ntThe temperature difference value at each continuous moment and the maximum temperature value of the battery, wherein n is more than or equal to 3t≤10；
S3-4: calculating the voltage difference value of the single cell voltage at different moments, the last moment voltage value of the single cell voltage in t seconds continuously, and the single cell voltage nu1Difference value of each continuous time and monomer voltage of nu2Difference value of each successive time, wherein n is more than or equal to 1u1≤6、8≤nu2≤10。
4. The method as claimed in claim 3, wherein the distributed real-time computing engine is a Flink, Storm, Spark Streaming distributed real-time computing engine.
5. The real-time on-line early warning method for the overheated battery according to any one of claims 1 to 3, wherein the step S4 comprises the following steps:
s4-1: judging whether signal data of the battery BMS are received in real time within t seconds, wherein t is more than or equal to 20 and less than or equal to 40;
s4-2: judging whether the vehicle is in the running, charging or standing process according to the charging state signal;
s4-3: judging the temperature of the battery and continuously nt1Continuous rising value of the maximum temperature of the battery at each moment and continuous nt2Maximum value and consecutive n of temperature difference at each momentu1Whether the voltage difference value of the single battery at each moment exceeds or is lower than a corresponding threshold value or not; wherein 2 is not more than nt1、nt2≤10、1≤nu1≤5；
S4-4: judging n is continuousu2The voltage difference value of the single battery at each moment, the last moment voltage value of the single battery and n continuousu3The voltage difference value of the previous moment when the voltage continuously drops at each moment is continuously nt3Whether the maximum value of the battery temperature difference at each moment exceeds or is lower than a corresponding threshold value, wherein n is more than or equal to 2u2、nu3≤10、5≤nt3≤10。
6. The real-time online early warning method for the overheated battery according to claim 5, wherein the step S5 comprises the following steps:
s5-1: checking S4-1, S4-2 and S4-3 in the process of S4 to judge whether the conditions are simultaneously satisfied;
s5-2: checking S4-1, S4-2 and S4-4 in the process of S4 to judge whether the conditions are simultaneously satisfied;
s5-3: if one of the processes S5-1 and S5-2 is established at the same time, the vehicle is in an overheating abnormality.
7. The utility model provides a real-time online early warning system after battery is overheated which characterized in that includes:
the data acquisition module is used for acquiring signal data of the vehicle battery in real time;
a preprocessing module: preprocessing the data;
the calculation module calculates and finds out the change difference of the signal data through a distributed real-time calculation engine;
the judging module is used for judging the battery overheating abnormal condition;
the identification module identifies a vehicle with an overheated battery according to the battery overheating strategy engine;
and the alarm module is used for giving an alarm for overheating of the overheated vehicle in real time.
8. The system of claim 7, wherein the computing module is configured to perform the following steps:
s3-1: consuming the preprocessed data in real time by using a distributed real-time computing engine;
s3-2: detecting whether the received signal data are within t seconds continuously, wherein t is more than or equal to 20 and less than or equal to 40;
s3-3: calculating the difference value of the temperature of the battery at different moments in ntThe temperature difference value at each continuous moment and the maximum temperature value of the battery, wherein n is more than or equal to 3t≤10；
S3-4: calculating the voltage difference value of the single cell voltage at different moments, the last moment voltage value of the single cell voltage in t seconds continuously, and the single cell voltage nu1Difference value of each continuous time and monomer voltage of nu2Difference value of each successive time, wherein n is more than or equal to 1u1≤6、8≤nu2≤10。
9. The system of claim 7, wherein the determining module is configured to perform the following steps:
s4-1: judging whether signal data of the battery BMS are received in real time within t seconds, wherein t is more than or equal to 20 and less than or equal to 40;
s4-2: judging whether the vehicle is in the running, charging or standing process according to the charging state signal;
s4-3: judging the temperature of the battery and continuously nt1Continuous rising value of the maximum temperature of the battery at each moment and continuous nt2Maximum value and consecutive n of temperature difference at each momentu1One time electricityWhether the voltage difference value of the pool monomer exceeds or is lower than a corresponding threshold value; wherein 2 is not more than nt1、nt2≤10、1≤nu1≤5；
S4-4: judging n is continuousu2The voltage difference value of the single battery at each moment, the last moment voltage value of the single battery and n continuousu3The voltage difference value of the previous moment when the voltage continuously drops at each moment is continuously nt3Whether the maximum value of the battery temperature difference at each moment exceeds or is lower than a corresponding threshold value, wherein n is more than or equal to 2u2、nu3≤10、5≤nt3≤10。
10. The system of claim 9, wherein the identification module is configured to perform the steps of:
s5-1: checking S4-1, S4-2 and S4-3 in the process of S4 to judge whether the conditions are simultaneously satisfied;
s5-2: checking S4-1, S4-2 and S4-4 in the process of S4 to judge whether the conditions are simultaneously satisfied;
s5-3: if one of the processes S5-1 and S5-2 is established at the same time, the vehicle is in an overheating abnormality.
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| CN114889433A (en) * | 2022-04-29 | 2022-08-12 | 奇瑞新能源汽车股份有限公司 | Thermal runaway alarm system and method for battery of electric vehicle |
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| CN115958957A (en) * | 2023-01-03 | 2023-04-14 | 重庆大学 | A method and system for predicting an electric vehicle power battery charging overheating fault |
| CN115958957B (en) * | 2023-01-03 | 2023-12-22 | 重庆大学 | Method and system for predicting charging overheat faults of power battery of electric automobile |
| CN117523809A (en) * | 2024-01-08 | 2024-02-06 | 四川千页科技股份有限公司 | A fire monitoring, evaluation and management method for lithium-ion battery energy storage stations |
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