CN112937303B - 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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- CN112937303B CN112937303B CN202110172738.6A CN202110172738A CN112937303B CN 112937303 B CN112937303 B CN 112937303B CN 202110172738 A CN202110172738 A CN 202110172738A CN 112937303 B CN112937303 B CN 112937303B
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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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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/70—Energy storage systems for electromobility, e.g. batteries
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 overheat abnormal condition; s5: finding out a vehicle with an overheated battery according to a battery overheating strategy engine; s6: and according to the result of S5, giving an alarm on overheating of the overheated vehicle in real time. 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; through the constructed battery overheating judgment strategy, the vehicle battery overheating abnormity is monitored in real time, vehicles about to occur or in the process of battery overheating are found in time, and directional alarm notification is carried out in real time, so that safety accidents such as battery life decline and vehicle fire 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 surrounding people. 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, generally, overheating of the battery is related to many factors and is complicated and various. 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 the step is to use a big data distributed real-time computing technology to process and analyze signal data in multiple angles and parameters, and to quickly find out internal factors influencing battery overheating.
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, giving an alarm on overheating of the overheated vehicle in real time.
Further, the data preprocessing of step S2 specifically 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 by the S2-1 and the 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: and (3) consuming the data processed by the S2 process in real time by 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 n t The temperature difference value at each continuous moment and the maximum temperature value of the battery, wherein n is more than or equal to 3 t ≤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 n u1 The difference value of each continuous time and the cell voltage are n u2 Difference value of each successive time, wherein n is more than or equal to 1 u1 ≤6、8≤n u2 ≤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, n t 、n u2 Values are taken within respective value ranges according to the performance of actual data statistics.
Since battery overheating can be determined by a variety of factors including ambient temperature, battery heat capacity, battery thermal conductivity, battery heat generation, TMS heating system, etc., the causes are complex and diverse. In the step, a big data real-time stream data processing technology is utilized to obtain BMS signals such as real-time voltage, temperature and resistance of the battery, a big data distributed real-time computing technology is utilized to process and analyze signal data in multiple angles and parameters, and 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: continuous n for judging battery temperature t1 Continuous rising value of the maximum temperature of the battery at each moment and continuous n t2 Maximum value and consecutive n of temperature difference at each moment u1 Whether the voltage difference value of the single battery at each moment exceeds or is lower than a corresponding threshold value or not; wherein n is more than or equal to 2 t1 、n t2 ≤10、1≤n u1 ≤5；
S4-4: judging n is continuous u2 The voltage difference value of the single battery at each moment, the last moment voltage value of the single battery and n continuous u3 The voltage difference value of the previous moment when the voltage continuously drops at each moment is continuously n t3 Whether 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 2 u2 、n u3 ≤10、5≤n t3 ≤10；
In the above steps, the parameters t and n t1 、n t2 、n t2 And n u1 、n u2 、n u3 Values are taken within respective value ranges according to the performance of actual data statistics.
Further, the purpose of step S5 is to find a vehicle about to generate or generating battery overheating in time through the battery overheating judgment strategy constructed in step S4, and includes the following steps:
s5-1: checking whether the judgment conditions of S4-1, S4-2 and S4-3 are simultaneously satisfied in the S4 process;
s5-2: checking whether the judgment conditions of S4-1, S4-2 and S4-4 are simultaneously satisfied in the S4 process;
s5-3: if one of the processes S5-1 and S5-2 is simultaneously established, the vehicle is subjected to 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 pretreatment 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 and not to limit 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 comprise 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 to determine whether abnormal data such as null values, exceedence of 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 by the S2-1 and the 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 comprise the steps of:
s3-1: consuming the data processed by 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 delta) at the current moment t ) Subtract the temperature value (temp) at the previous moment t-1 )：
tempΔ＝temp t -temp t-1
Wherein t represents the current time and t-1 represents the last time.
S3-4: and calculating the voltage difference of the single battery voltage at different moments, the last moment voltage value of the single battery voltage, the difference of the single battery voltage at 2 continuous moments and the difference of the single battery voltage at 5 continuous moments.
Wherein the cell voltage difference value (vol delta) is equal to the cell voltage value (vol delta) at the current moment t ) Subtract the cell voltage value (vol) at the previous time t-1 )：
volΔ＝vol t -vol t-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 comprise 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: charge =3.
Vehicle charging or rest state: charge =1 or charge =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 the 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 single battery is less than or equal to-1 mV at 2 continuous moments;
s4-3-5: if the conditions of S4-3-1, S4-3-2, S4-3-4 or S4-3-1, S4-3-3, S4-3-4 are simultaneously satisfied, it indicates that the judgment condition of the S4-3 process is satisfied.
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 voltage of the single battery at the last moment is more than or equal to 150mV;
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: and if the conditions of S4-4-1, S4-4-2, S4-4-3 or 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 whether the judgment conditions of S4-1, S4-2 and S4-3 are simultaneously satisfied in the S4 process;
s5-2: checking whether the judgment conditions of S4-1, S4-2 and S4-4 are simultaneously satisfied in the S4 process;
s5-3: if one of the processes S5-1 and S5-2 is established simultaneously, the vehicle is overheated abnormally.
S6: and according to the result of S5, giving an alarm on overheating of the overheated vehicle in real time.
The further embodiment of the invention is a real-time online early warning system after the battery is overheated, 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 pretreatment 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 specifically 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 judging 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 implement the 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 (6)
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: according to the result of S5, carrying out overheating real-time alarm on the overheated vehicle;
the step S3 includes the steps of:
s3-1: consuming the data processed by 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
The temperature difference value at each continuous moment, and the maximum temperature value of the battery, wherein
；
S3-4: calculating the voltage difference value of the single battery voltage at different moments and the continuous t of the single battery voltageThe last moment in second is that the voltage value and the monomer voltage are
Difference value at each continuous time, cell voltage is
A difference value of successive time instants, wherein
、
；
The step S4 includes the steps of:
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 continuously
The maximum temperature of the battery continuously rises at any moment
Maximum and continuous temperature difference at each moment
Whether the voltage difference value of the single battery at each moment exceeds or is lower than a corresponding threshold value or not; wherein
、
；
S4-4: judging continuity
The voltage difference value of the single battery at each moment, the last moment voltage value of the single battery and continuity
The voltage difference value of the previous moment when the voltage continuously drops at each moment is continuously reduced
Whether the maximum value of the battery temperature difference exceeds or falls below a corresponding threshold value at each moment, wherein
、
。
2. The real-time online early warning method after the battery is overheated according to claim 1, wherein the signal data of the step S1 comprises a frame number, a battery cell voltage, a temperature, a total voltage, a total current, an insulation resistance, a charging state, a fault grade and a fault code;
the step S2 includes the steps of:
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 by the S2-1 and the S2-2.
3. The method for real-time online early warning after battery overheating according to claim 1, wherein the distributed real-time computing engine can adopt a Flink, storm, spark Streaming, and other distributed real-time computing engines.
4. The real-time online early warning method after the battery is overheated according to claim 1, wherein the step S5 comprises the following steps:
s5-1: checking whether the judgment conditions of S4-1, S4-2 and S4-3 are simultaneously satisfied in the S4 process;
s5-2: checking whether the judgment conditions of S4-1, S4-2 and S4-4 are simultaneously satisfied in the S4 process;
s5-3: if one of the processes S5-1 and S5-2 is established simultaneously, the vehicle is overheated abnormally.
5. 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;
the alarm module is used for giving an alarm on overheating of the overheated vehicle in real time;
the calculation module is configured to perform the steps of:
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
A temperature difference value at each successive time, and a maximum battery temperature value, wherein
；
S3-4: calculating the voltage difference value of the single battery voltage at different moments, the last moment voltage value of the single battery voltage in continuous t seconds, and the single battery voltage
Difference value of each continuous time and monomer voltage of
A difference value of successive time instants, wherein
、
；
The determination module is configured to perform the steps of:
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 continuously
Continuous rising value and continuous rising value of the maximum temperature of the battery at each moment
Maximum and continuous temperature difference at each moment
Whether the voltage difference value of the single battery at each moment exceeds or is lower than a corresponding threshold value or not; wherein
、
；
S4-4: judgment of continuity
The voltage difference value of the single battery at each moment, the last moment voltage value of the single battery and continuity
The voltage difference value of the previous moment when the voltage continuously drops at each moment is continuously reduced
Whether the maximum value of the battery temperature difference at each moment exceeds or falls below a corresponding threshold value, wherein
、
。
6. The system of claim 5, wherein the identification module is configured to perform the following steps:
s5-1: checking whether the judgment conditions of S4-1, S4-2 and S4-3 are simultaneously satisfied in the S4 process;
s5-2: checking whether the judgment conditions of S4-1, S4-2 and S4-4 are simultaneously satisfied in the S4 process;
s5-3: if one of the processes S5-1 and S5-2 is established simultaneously, the vehicle is overheated abnormally.
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Families Citing this family (5)
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| CN114312319B (en) * | 2021-12-15 | 2023-06-02 | 重庆长安新能源汽车科技有限公司 | Battery safety monitoring method based on voltage accumulation value, storage medium and vehicle |
| CN114274777B (en) * | 2021-12-15 | 2023-06-02 | 重庆长安新能源汽车科技有限公司 | Battery abnormality monitoring method and system and vehicle |
| CN115626062B (en) * | 2022-12-21 | 2023-08-04 | 中汽研汽车检验中心（天津）有限公司 | Battery pack temperature early warning method and system based on battery pack thermal management system modeling |
| 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 |
| CN117523809B (en) * | 2024-01-08 | 2024-03-12 | 四川千页科技股份有限公司 | Fire monitoring, evaluating and managing method for lithium ion battery energy storage station |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102014209252A1 (en) * | 2014-05-15 | 2015-11-19 | Ford Global Technologies, Llc | Method for managing the electrical power supply in a motor vehicle |
| KR20160109062A (en) * | 2015-03-09 | 2016-09-21 | 삼성전자주식회사 | Method and apparatus for estimating state of battery |
| CN110515005A (en) * | 2019-08-13 | 2019-11-29 | 上海欣诣科技有限公司 | A kind of spontaneous combustion early warning system for the electric car in charging pile monitoring charging |
| CN111114328A (en) * | 2020-02-27 | 2020-05-08 | 湖北亿纬动力有限公司 | Thermal runaway early warning method, device and system for power storage battery of electric automobile |
| CN111653840A (en) * | 2020-06-08 | 2020-09-11 | 中国第一汽车股份有限公司 | Early warning method, device, equipment and storage medium |
| CN111883861A (en) * | 2020-07-17 | 2020-11-03 | 北京成功领行汽车技术有限责任公司 | Electric vehicle thermal runaway early warning and inhibiting system and control method thereof |
Family Cites Families (25)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TWM332909U (en) * | 2007-11-30 | 2008-05-21 | Lifebatt Production Inc | Far-end monitoring system for a battery module of an electromotive vehicle |
| US8219333B2 (en) * | 2010-06-29 | 2012-07-10 | O2Micro, Inc | Battery management systems for protecting batteries from fault conditions |
| US9177466B2 (en) * | 2011-01-20 | 2015-11-03 | Indiana University Research And Technology Corporation | Advanced battery early warning and monitoring system |
| CN103323775B (en) * | 2012-03-20 | 2015-07-08 | 北汽福田汽车股份有限公司 | Balanced monitoring and test system used for battery module |
| DE102015002071A1 (en) * | 2015-02-18 | 2016-08-18 | Audi Ag | Battery cell with monitoring device and associated operating method |
| CN106450519B (en) * | 2016-10-24 | 2019-03-15 | 湖南金杯新能源发展有限公司 | Protector for battery charging and method |
| CN106556802A (en) * | 2016-11-01 | 2017-04-05 | 东软集团股份有限公司 | A kind of accumulator battery exception cell recognition methodss and device |
| CN107064803B (en) * | 2016-12-16 | 2019-12-13 | 蔚来汽车有限公司 | on-line detection method for short circuit in battery |
| CN108808754B (en) * | 2017-05-03 | 2020-10-16 | 华为技术有限公司 | Distributed battery, battery control method and electric automobile |
| WO2019017991A1 (en) * | 2017-07-21 | 2019-01-24 | Quantumscape Corporation | Predictive model for estimating battery states |
| DE102017219990A1 (en) * | 2017-11-09 | 2019-05-09 | Audi Ag | A warning method for a high-voltage battery of a motor vehicle in the event of an accident of the motor vehicle, a warning system for carrying out the warning method and a motor vehicle comprising components of the warning system |
| CN108562855B (en) * | 2017-12-18 | 2020-02-07 | 清华大学 | Method and device for detecting short circuit in battery and computer readable storage medium |
| CN108152755B (en) * | 2018-01-19 | 2020-01-21 | 上海理工大学 | Method for online quantitative diagnosis of battery micro short circuit fault |
| US10948544B2 (en) * | 2018-03-08 | 2021-03-16 | Industrial Technology Research Institute | Battery safety identifying method and method for setting hazard levels of battery internal short circuit and warning system using the same |
| CN108749607A (en) * | 2018-05-23 | 2018-11-06 | 清华大学深圳研究生院 | A kind of electric automobile power battery management and monitoring system based on cloud computing |
| CN109050261A (en) * | 2018-08-14 | 2018-12-21 | 深圳新荷科技有限公司 | One kind realizing programming automation diagnostic method based on new-energy automobile alarm code |
| DE102019206365A1 (en) * | 2019-05-03 | 2020-11-05 | Audi Ag | Method for early detection of impending overheating of at least one battery cell of a battery, detection device and motor vehicle |
| CN110208706A (en) * | 2019-06-13 | 2019-09-06 | 重庆长安新能源汽车科技有限公司 | A kind of power battery health status online evaluation system and method based on car networking |
| CN110350258B (en) * | 2019-06-17 | 2020-12-01 | 广东恒翼能科技有限公司 | Lithium battery thermal runaway early warning protection system and method |
| CN110504502B (en) * | 2019-08-29 | 2022-05-03 | 重庆长安新能源汽车科技有限公司 | Processing method and device for abnormal battery temperature acquisition, controller and automobile |
| CN111823952B (en) * | 2020-04-17 | 2022-07-05 | 北京嘀嘀无限科技发展有限公司 | Battery cell temperature diagnosis method, storage medium and electronic equipment |
| CN111572350A (en) * | 2020-05-29 | 2020-08-25 | 北京经纬恒润科技有限公司 | Electric automobile fire-starting early warning method and device |
| CN111890933A (en) * | 2020-06-11 | 2020-11-06 | 恒大恒驰新能源汽车研究院(上海)有限公司 | Battery management method and system for vehicle, vehicle and server |
| CN112124076B (en) * | 2020-08-28 | 2022-03-04 | 蜂巢能源科技有限公司 | Power battery short circuit detection method, device, automobile, system and storage medium |
| CN111999656B (en) * | 2020-08-28 | 2023-05-12 | 广州小鹏汽车科技有限公司 | Method and device for detecting short circuit in vehicle battery and electronic equipment |
-
2021
- 2021-02-08 CN CN202110172738.6A patent/CN112937303B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102014209252A1 (en) * | 2014-05-15 | 2015-11-19 | Ford Global Technologies, Llc | Method for managing the electrical power supply in a motor vehicle |
| KR20160109062A (en) * | 2015-03-09 | 2016-09-21 | 삼성전자주식회사 | Method and apparatus for estimating state of battery |
| CN110515005A (en) * | 2019-08-13 | 2019-11-29 | 上海欣诣科技有限公司 | A kind of spontaneous combustion early warning system for the electric car in charging pile monitoring charging |
| CN111114328A (en) * | 2020-02-27 | 2020-05-08 | 湖北亿纬动力有限公司 | Thermal runaway early warning method, device and system for power storage battery of electric automobile |
| CN111653840A (en) * | 2020-06-08 | 2020-09-11 | 中国第一汽车股份有限公司 | Early warning method, device, equipment and storage medium |
| CN111883861A (en) * | 2020-07-17 | 2020-11-03 | 北京成功领行汽车技术有限责任公司 | Electric vehicle thermal runaway early warning and inhibiting system and control method thereof |
Non-Patent Citations (1)
| Title |
|---|
| 动力锂电池在电动汽车中的应用;贾永丽等;《节能》;20141215(第12期);第4-7页 * |
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