WO2023011066A1 - 一种电池热管理***的性能检测方法及相关设备 - Google Patents
一种电池热管理***的性能检测方法及相关设备 Download PDFInfo
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- WO2023011066A1 WO2023011066A1 PCT/CN2022/102720 CN2022102720W WO2023011066A1 WO 2023011066 A1 WO2023011066 A1 WO 2023011066A1 CN 2022102720 W CN2022102720 W CN 2022102720W WO 2023011066 A1 WO2023011066 A1 WO 2023011066A1
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- battery pack
- temperature
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- 238000000034 method Methods 0.000 title claims abstract description 34
- 238000011056 performance test Methods 0.000 title abstract description 5
- 239000011159 matrix material Substances 0.000 claims abstract description 119
- 238000001514 detection method Methods 0.000 claims description 43
- 238000010276 construction Methods 0.000 claims description 17
- 230000002159 abnormal effect Effects 0.000 claims description 14
- 238000012360 testing method Methods 0.000 claims 2
- 230000002354 daily effect Effects 0.000 description 10
- 238000010586 diagram Methods 0.000 description 8
- 238000009825 accumulation Methods 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 239000000306 component Substances 0.000 description 1
- 238000001816 cooling Methods 0.000 description 1
- 239000008358 core component Substances 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 230000003203 everyday effect Effects 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/385—Arrangements for measuring battery or accumulator variables
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/374—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC] with means for correcting the measurement for temperature or ageing
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/392—Determining battery ageing or deterioration, e.g. state of health
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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
Definitions
- battery packs directly affect the performance of electric vehicles.
- the battery pack When the electric vehicle is running under different working conditions, when the battery pack is discharged at different rates, a large amount of heat will be generated. With time accumulation and space influence, uneven heat accumulation will occur, resulting in uneven temperature distribution in the battery pack, which will affect the battery life. Unity consistency. If the entire battery pack cannot be ventilated and dissipated in a timely manner at high temperatures, the excessively high operating temperature and the excessive temperature difference will not be relieved, which will reduce the charge-discharge cycle efficiency of the battery pack, affect the power and energy performance of the battery pack, and seriously Sometimes it will cause thermal runaway, which will eventually affect the safety and reliability of the battery pack.
- the battery thermal management system In order to maximize the performance of the battery pack and prolong the service life of the battery pack, the battery thermal management system is currently used to control the temperature of the battery pack.
- the battery thermal management system uses methods such as cooling and temperature equalization to adjust the possible impact of the external environment temperature on the battery pack, and balance the internal temperature difference of the battery pack to keep the temperature of the battery pack within a reasonable range.
- the present invention discloses a performance detection method of a battery thermal management system and related equipment, so as to realize the performance detection of the battery thermal management system.
- a performance detection method of a battery thermal management system comprising:
- the current battery temperature matrix is: a three-dimensional matrix of the battery pack output voltage sub-interval-the battery pack output current sub-interval-the maximum temperature of the single battery in the battery pack;
- An average value is taken for all the temperature offsets of the single cells to obtain a decay constant that characterizes the degree of performance decay of the battery thermal management system.
- the acquisition of the battery pack operating condition data of the current electric vehicle in the current preset time period specifically includes:
- the battery pack operating condition data that does not meet the preset vehicle continuous operating condition data in the original battery pack operating condition data is eliminated to obtain the battery pack operating condition data. status data.
- the constructing the current battery temperature matrix based on the operating condition data of the battery pack specifically includes:
- the current battery temperature matrix is constructed based on the N1 battery pack output voltage subintervals, the M1 battery pack output current subintervals, and the corresponding maximum temperature values of the single batteries.
- the construction process of the battery temperature reference matrix includes:
- the historical operating condition data of the battery pack that do not meet the preset vehicle continuous operating condition data in the historical operating condition data of the battery pack is eliminated to obtain the target historical operating condition data;
- the battery temperature reference matrix is constructed based on the N2 historical battery pack output voltage subintervals, the M2 historical battery pack output current subintervals, and the corresponding maximum values of the reference single battery temperature.
- the method further includes:
- the average value of all the temperature offsets of the single cells is taken to obtain a decay number representing the performance decay degree of the battery thermal management system, which specifically includes:
- a performance detection device for a battery thermal management system comprising:
- the data acquisition unit is used to acquire the operating condition data of the battery pack of the current electric vehicle in the current preset time period
- the first matrix construction unit is configured to construct a current battery temperature matrix based on the operating condition data of the battery pack, and the current battery temperature matrix is: battery pack output voltage sub-interval - battery pack output current sub-interval - cells in the battery pack Three-dimensional matrix of battery temperature maximum;
- the offset determination unit is used to obtain the quotient of the maximum temperature of each single battery in the current battery temperature matrix and the corresponding maximum temperature of the reference single battery in the pre-built battery temperature reference matrix to obtain the temperature of the single battery An offset, wherein, the maximum value of the single battery temperature and the maximum value of the reference single battery temperature correspond to the same battery pack output voltage subinterval and the same battery pack output current subinterval;
- the attenuation constant determination unit is configured to average all the temperature offsets of the single batteries to obtain an attenuation constant representing the degree of performance attenuation of the battery thermal management system.
- the first matrix construction unit specifically includes:
- the first voltage division subunit is used to divide all battery pack output voltages in the battery pack operating condition data into N1 battery pack output voltage sub-intervals, where N1 is a positive integer;
- the first current division subunit is used to divide all battery pack output currents in the battery pack operating condition data into M1 battery pack output current sub-intervals, where M1 is a positive integer;
- the first calculation subunit is used to calculate all the original single battery temperatures corresponding to each of the battery pack output voltage sub-intervals and each of the battery pack output current sub-intervals in the operating condition data of the battery pack The average value of the maximum value, and use the average value as the maximum temperature of the single battery in the battery pack;
- the first matrix construction subunit is used to construct and obtain the current battery temperature based on the N1 battery pack output voltage subintervals, the M1 battery pack output current subintervals, and the corresponding maximum temperature values of the single cells. matrix.
- the comparison unit is used to compare the attenuation constant with the attenuation after the attenuation constant determination unit averages all the temperature offsets of the single batteries to obtain the attenuation constant representing the performance attenuation degree of the battery thermal management system. Threshold to compare;
- An information output unit configured to output a prompt message indicating abnormal performance of the battery thermal management system when the decay constant is smaller than the decay threshold.
- a performance detection system for a battery thermal management system comprising: a vehicle-mounted mobile terminal, a TSP cloud platform, and a big data cloud platform, wherein the big data cloud platform includes the performance detection device for the battery thermal management system described above;
- the vehicle-mounted mobile terminal is used to collect the battery pack operating condition data of the current electric vehicle in the current preset time period;
- the TSP cloud platform is respectively connected with the vehicle-mounted mobile terminal and the big data cloud platform, and is used to send the battery pack operating condition data collected by the vehicle-mounted mobile terminal to the big data cloud platform.
- An electronic device comprising a memory and a processor
- the memory is used to store at least one instruction
- the processor is configured to execute the at least one instruction to implement the performance detection method of the battery thermal management system described above.
- a computer-readable storage medium wherein the computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed by a processor, the performance detection method of the battery thermal management system described above is implemented.
- the present invention discloses a performance detection method and related equipment of a battery thermal management system.
- the current battery temperature matrix is constructed based on the battery pack operating condition data of the current preset time period of the current electric vehicle.
- the current battery The temperature matrix is a three-dimensional matrix of the battery pack output voltage subinterval-battery pack output current subinterval-the maximum temperature of the single battery in the battery pack.
- the maximum temperature of each single battery in the current battery temperature matrix is compared with the pre-built battery temperature Calculate the maximum value of the corresponding reference cell temperature in the reference matrix to obtain the temperature offset of the cell, and obtain the attenuation constant representing the performance attenuation degree of the battery thermal management system by taking the average value of all the cell temperature offsets .
- the present invention realizes the performance detection of the battery thermal management system based on the battery pack operating condition data of the electric vehicle. Since the present invention uses the decay constant to characterize the performance of the battery thermal management system, it can Determine whether the performance of the battery thermal management system has declined or failed, so that when the performance of the battery thermal management system fails, the owner will be reminded to maintain the battery thermal management system in time to avoid affecting the charge and discharge cycle efficiency of the battery pack due to the failure of the thermal management system.
- the power of the battery pack and the thermal control ability of the battery thermal management system on the battery pack can improve the safety and reliability of the battery pack and avoid problems such as vehicle fire and insufficient power.
- Fig. 1 is a flowchart of a performance detection method of a battery thermal management system disclosed in an embodiment of the present invention
- Fig. 2 is a flowchart of a method for constructing a current battery temperature matrix based on battery pack operating condition data disclosed in an embodiment of the present invention
- Fig. 3 is a flowchart of a method for constructing a battery temperature reference matrix disclosed in an embodiment of the present invention, and the method is applied to a big data cloud platform;
- Fig. 4 is a schematic diagram of a decay degree curve of a battery thermal management system of an electric vehicle disclosed in an embodiment of the present invention in a preset time period;
- FIG. 5 is a schematic structural diagram of a performance detection device for a battery thermal management system disclosed in an embodiment of the present invention.
- FIG. 6 is a schematic structural diagram of a first matrix construction unit disclosed in an embodiment of the present invention.
- Fig. 7 is a schematic structural diagram of a performance detection system of a battery thermal management system disclosed in an embodiment of the present invention.
- the embodiment of the present invention discloses a performance detection method and related equipment of a battery thermal management system. Based on the battery pack operating condition data of an electric vehicle, the performance detection of the battery thermal management system is realized. Since the present invention uses a decay constant to characterize the battery thermal management System performance, so it can be determined whether the performance of the battery thermal management system has declined or failed according to the attenuation constant, so that when the performance of the battery thermal management system fails, the car owner is promptly reminded to maintain the battery thermal management system to avoid damage caused by the thermal management system.
- Functional failure affects the charge and discharge cycle efficiency of the battery pack and the power of the battery pack, as well as the thermal control capability of the battery thermal management system on the battery pack, thereby improving the safety and reliability of the battery pack and avoiding problems such as vehicle fires and insufficient power.
- a flowchart of a performance detection method of a battery thermal management system disclosed in an embodiment of the present invention the method is applied to a big data cloud platform, and the method includes:
- Step S101 Obtain the operating condition data of the battery pack of the current electric vehicle in the current preset time period
- the operating condition data of the battery pack includes: time stamp, output voltage of the battery pack, output current of the battery pack, and the maximum temperature of the single cells in the battery pack at different times.
- the value of the current preset time period is determined according to actual needs, such as one day, which is not limited in the present invention.
- Step S102 constructing a current battery temperature matrix based on the operating condition data of the battery pack
- the current battery temperature matrix is: a three-dimensional matrix of: battery pack output voltage subinterval-battery pack output current subinterval-maximum value of single battery temperature in the battery pack.
- the current battery temperature matrix constructed is actually: the daily battery temperature matrix DayMax.
- a flowchart of a method for constructing a current battery temperature matrix based on battery pack operating condition data disclosed in an embodiment of the present invention includes:
- Step S201 dividing all battery pack output voltages in the battery pack operating condition data into N1 battery pack output voltage sub-intervals, where N1 is a positive integer;
- the division standard of the battery pack output voltage sub-intervals can be determined according to the maximum value of the battery pack output voltage and the minimum value of the battery pack output voltage among all the battery pack output voltages.
- Step S202 dividing all battery pack output currents in the battery pack operating condition data into M1 battery pack output current sub-intervals, where M1 is a positive integer;
- Step S203 Calculating the average value of the maximum temperature values of all the original single cells corresponding to each of the battery pack output voltage sub-intervals and each of the battery pack output current sub-intervals in the operating condition data of the battery pack , and use the average value as the maximum temperature of the single battery in the battery pack;
- Step S204 based on the N1 battery pack output voltage subintervals, the M1 battery pack output current subintervals and the corresponding maximum temperature values of the single cells, construct the current battery temperature matrix.
- the battery pack operating condition data is the battery pack operating condition data of the current electric vehicle on that day
- the current battery temperature matrix is the daily battery temperature matrix DayMax.
- N1 10, battery pack output voltage sub-range, respectively: [310,320), [320,330), [330,340), [340,350), [350,360), [360,370), [370,380), [380,390), [390,400) and [400,410);
- the battery pack output current sub-intervals are: [30, 40), [40, 50), [50, 60), [60, 70), [80, 90) and [90, 100);
- the daily battery temperature matrix DayMax is shown in Table 1.
- Step S103 calculating the quotient of the maximum temperature of each single battery in the current battery temperature matrix and the corresponding maximum temperature of the reference single battery in the pre-built battery temperature reference matrix to obtain the temperature offset of the single battery;
- the maximum temperature of the single battery and the maximum temperature of the reference single battery correspond to the same battery pack output voltage subinterval and the same battery pack output current subinterval.
- the battery temperature reference matrix is obtained based on the historical operating condition data of the battery pack of the electric vehicle in the historical preset time period, and the battery temperature reference matrix is specifically: the historical battery pack output voltage sub-interval - the historical battery pack output current sub-interval - A three-dimensional matrix of the maximum value of the reference cell temperature.
- the temperature offset of each single battery corresponding to the maximum temperature of each single battery in the daily battery temperature matrix is sequentially calculated.
- Step S104 taking the average value of all the temperature offsets of the single batteries to obtain a decay constant representing the degree of performance decay of the battery thermal management system.
- the attenuation degree of the performance of the battery thermal management system compared with the initial performance can be measured according to the magnitude of the attenuation constant.
- the present invention discloses a performance detection method of a battery thermal management system, which constructs a current battery temperature matrix based on the battery pack operating condition data of the current electric vehicle in the current preset time period, and the current battery temperature matrix is the output of the battery pack.
- Voltage subinterval-battery pack output current subinterval-three-dimensional matrix of the maximum temperature of the single battery in the battery pack, the maximum temperature of each single battery in the current battery temperature matrix and the corresponding reference in the pre-built battery temperature reference matrix
- the maximum value of the single battery temperature is calculated to obtain the temperature offset of the single battery, and the attenuation constant representing the performance attenuation degree of the battery thermal management system is obtained by taking the average value of all the temperature offsets of the single battery.
- the present invention realizes the performance detection of the battery thermal management system based on the battery pack operating condition data of the electric vehicle. Since the present invention uses the decay constant to characterize the performance of the battery thermal management system, it can Determine whether the performance of the battery thermal management system has declined or failed, so that when the performance of the battery thermal management system fails, the owner will be reminded to maintain the battery thermal management system in time to avoid affecting the charge and discharge cycle efficiency of the battery pack due to the failure of the thermal management system.
- the power of the battery pack and the thermal control ability of the battery thermal management system on the battery pack can improve the safety and reliability of the battery pack and avoid problems such as vehicle fire and insufficient power.
- the present invention will also check the operating condition data that does not meet the requirements after obtaining the original operating condition data of the battery pack.
- the battery pack operating condition data under the continuous operating condition of the vehicle is eliminated.
- step S101 may specifically include:
- the battery pack operating condition data that does not meet the preset vehicle continuous operating condition data in the original battery pack operating condition data is eliminated to obtain the battery pack operating condition data. status data.
- the preset continuous running condition of the vehicle may be determined according to the continuous running time or the continuous running distance of the electric vehicle.
- each operating condition data in the obtained original battery pack operating condition data has a corresponding time stamp, and based on the timestamp, it can be determined whether the corresponding operating condition data is data generated during continuous operation of the vehicle.
- FIG. 3 a flow chart of a method for constructing a battery temperature reference matrix disclosed in an embodiment of the present invention.
- the method is applied to a big data cloud platform, and the method includes:
- Step S301 obtaining the historical operating condition data of the battery pack of the electric vehicle in the historical preset time period
- the value of the historical preset time period is determined according to actual needs, such as the historical operating condition data of the battery pack of the electric vehicle for two months from the start-up.
- the historical operating condition data of the battery packs of multiple electric vehicles in the historical preset time period can be obtained.
- the historical operating condition data of the battery pack includes: time stamp, historical battery pack output voltage, historical battery pack output current, and historical maximum temperature of single cells in the battery pack at different times.
- Step S302 based on the time stamp in the historical operating condition data of the battery pack, remove the historical operating condition data of the battery pack that do not meet the preset continuous operating conditions of the vehicle in the historical operating condition data of the battery pack, and obtain the target history Operating condition data;
- Step S303 dividing all historical battery pack output voltages in the target historical operating condition data into N2 historical battery pack output voltage subintervals, where N2 is a positive integer;
- Step S304 dividing all historical battery pack output currents in the target historical operating condition data into M2 historical battery pack output current sub-intervals, where M2 is a positive integer;
- Step S305 calculating the maximum value of all the historical single battery temperatures corresponding to each of the historical battery pack output voltage sub-intervals and each of the historical battery pack output current sub-intervals in the target historical operating condition data average value, and use the average value as the maximum value of the reference cell temperature;
- Step S306 based on the N2 historical battery pack output voltage subintervals, the M2 historical battery pack output current subintervals and the corresponding maximum value of the reference single battery temperature, construct the battery temperature reference matrix.
- step S302 to step S306 refer to the corresponding part of the embodiment shown in FIG. 2 , which will not be repeated here.
- the current battery temperature offset matrix corresponding to the current battery temperature matrix can be constructed by calculating the single battery temperature offset corresponding to the maximum temperature of each single battery in the current battery temperature matrix.
- step S104 may specifically include:
- the daily battery temperature offset matrix BiasMax shown in Table 3 can be constructed based on the temperature offset rate of each single battery and the battery pack output voltage subinterval and battery pack output current subinterval in the daily battery temperature matrix DayMax.
- the battery pack output voltage sub-interval [310, 320) and the battery pack output current sub-interval [30, 40) correspond to the temperature offset of the single battery: 0.89, which is consistent with the above calculation of the battery pack output
- step S103 For the specific calculation process of the temperature offset of each single battery in the daily battery temperature offset matrix BiasMax, please refer to step S103.
- step S104 the present invention obtains the attenuation constant BiasDayMax that characterizes the performance attenuation degree of the battery thermal management system by taking the average of all the temperature offsets of the single batteries.
- the operating condition data of the battery pack is also increasing. If an attenuation constant BiasDayMax is calculated every day from 2021/1/1 to 2021/1/11, the table can be obtained 4 shows the content.
- step S104 it may further include:
- the value of the attenuation threshold is determined according to actual needs, for example, the attenuation threshold is 0.4.
- the present invention determines whether the performance of the battery thermal management system is abnormal by comparing the attenuation constant with the attenuation threshold, and determines that the performance of the battery thermal management system is abnormal when the attenuation constant is less than the attenuation threshold.
- the prompt message of abnormal system performance reminds the owner to overhaul the battery thermal management system in time to avoid affecting the charge and discharge cycle efficiency of the battery pack and the power of the battery pack due to the failure of the thermal management system, as well as the thermal control ability of the battery thermal management system for the battery pack , so as to improve the safety and reliability of the battery pack, and avoid problems such as vehicle fire and insufficient power.
- the present invention also discloses a performance detection device for a battery thermal management system.
- FIG. 5 a schematic structural diagram of a performance detection device for a battery thermal management system disclosed in an embodiment of the present invention, which is applied to a big data cloud platform, and includes:
- the data acquisition unit 401 is used to acquire the battery pack operating condition data of the current electric vehicle in the current preset time period;
- the operating condition data of the battery pack includes: time stamp, output voltage of the battery pack, output current of the battery pack, and the maximum temperature of the single cells in the battery pack at different times.
- the value of the current preset time period is determined according to actual needs, such as one day, which is not limited in the present invention.
- the first matrix construction unit 402 is configured to construct a current battery temperature matrix based on the battery pack operating condition data, and the current battery temperature matrix is: battery pack output voltage sub-interval - battery pack output current sub-interval - battery pack single cell The three-dimensional matrix of the maximum temperature of the bulk battery;
- the offset determination unit 403 is configured to obtain the quotient of the maximum temperature of each single battery in the current battery temperature matrix and the corresponding maximum temperature of the reference single battery in the pre-built battery temperature reference matrix to obtain a single battery temperature offset;
- the maximum temperature of the single battery and the maximum temperature of the reference single battery correspond to the same battery pack output voltage subinterval and the same battery pack output current subinterval.
- the attenuation constant determination unit 404 is configured to average all the temperature offsets of the single batteries to obtain an attenuation constant representing the performance attenuation degree of the battery thermal management system.
- the attenuation degree of the performance of the battery thermal management system compared with the initial performance can be measured according to the magnitude of the attenuation constant.
- the present invention discloses a performance detection device for a battery thermal management system, which constructs a current battery temperature matrix based on the battery pack operating condition data of the current electric vehicle in the current preset time period, and the current battery temperature matrix is the output of the battery pack.
- Voltage subinterval-battery pack output current subinterval-three-dimensional matrix of the maximum temperature of the single battery in the battery pack, the maximum temperature of each single battery in the current battery temperature matrix and the corresponding reference in the pre-built battery temperature reference matrix
- the maximum value of the single battery temperature is calculated to obtain the temperature offset of the single battery, and the attenuation constant representing the performance attenuation degree of the battery thermal management system is obtained by taking the average value of all the temperature offsets of the single battery.
- the present invention realizes the performance detection of the battery thermal management system based on the battery pack operating condition data of the electric vehicle. Since the present invention uses the decay constant to characterize the performance of the battery thermal management system, it can Determine whether the performance of the battery thermal management system has declined or failed, so that when the performance of the battery thermal management system fails, the owner will be reminded to maintain the battery thermal management system in time to avoid affecting the charge and discharge cycle efficiency of the battery pack due to the failure of the thermal management system.
- the power of the battery pack and the thermal control capability of the battery thermal management system on the battery pack can improve the safety and reliability of the battery pack and avoid problems such as vehicle fire and insufficient power.
- the present invention will also check the operating condition data that does not meet the requirements after obtaining the original operating condition data of the battery pack.
- the battery pack operating condition data under the continuous operating condition of the vehicle is eliminated.
- the data acquisition unit 401 can specifically be used for:
- the battery pack operating condition data that does not meet the preset vehicle continuous operating condition data in the original battery pack operating condition data is eliminated to obtain the battery pack operating condition data. status data.
- the preset continuous running condition of the vehicle may be determined according to the continuous running time or the continuous running distance of the electric vehicle.
- each operating condition data in the obtained original battery pack operating condition data has a corresponding time stamp, and based on the timestamp, it can be determined whether the corresponding operating condition data is data generated during continuous operation of the vehicle.
- FIG. 6 a schematic structural diagram of a first matrix construction unit disclosed in an embodiment of the present invention.
- the first matrix construction unit includes:
- the first voltage division subunit 501 is configured to divide all battery pack output voltages in the battery pack operating condition data into N1 battery pack output voltage sub-intervals, where N1 is a positive integer;
- the historical operating condition data of the battery pack includes: time stamp, historical battery pack output voltage, historical battery pack output current, and historical maximum temperature of single cells in the battery pack at different times.
- the first current division subunit 502 is configured to divide all battery pack output currents in the battery pack operating condition data into M1 battery pack output current sub-intervals, where M1 is a positive integer;
- the first calculation subunit 503 is used to calculate all the original single cells corresponding to each sub-interval of the output voltage of the battery pack and each sub-interval of the output current of the battery pack in the operating condition data of the battery pack The average value of the maximum temperature, and use the average value as the maximum temperature of the single battery in the battery pack;
- the first matrix construction subunit 504 is configured to construct and obtain the current battery based on the N1 battery pack output voltage subintervals, the M1 battery pack output current subintervals, and the corresponding maximum temperature values of the single cells. temperature matrix.
- the current battery temperature offset matrix corresponding to the current battery temperature matrix can be constructed by calculating the single battery temperature offset corresponding to the maximum temperature of each single battery in the current battery temperature matrix.
- the attenuation constant determination unit 404 can specifically be used for:
- the performance detection device may also include:
- the second matrix construction unit is configured to construct the battery temperature reference matrix.
- the second matrix construction unit specifically includes:
- the data acquisition subunit is used to acquire the historical operating condition data of the battery pack of the electric vehicle in the historical preset time period;
- the data screening subunit is used to remove the historical operating condition data of the battery pack from the historical operating condition data of the battery pack that does not meet the preset continuous operating conditions of the vehicle based on the time stamp in the historical operating condition data of the battery pack , to obtain the target historical operating condition data;
- the second voltage division subunit is used to divide all historical battery pack output voltages in the target historical operating condition data into N2 historical battery pack output voltage subintervals, where N2 is a positive integer;
- the second current division subunit is used to divide all the historical battery pack output currents in the target historical operating condition data into M2 historical battery pack output current sub-intervals, where M2 is a positive integer;
- the second calculation subunit is used to calculate all historical cells corresponding to each of the historical battery pack output voltage sub-intervals and each of the historical battery pack output current sub-intervals in the target historical operating condition data the average value of the maximum temperature of the battery, and use the average value as the maximum temperature of the reference single battery;
- the second matrix construction subunit is used to construct and obtain said Battery temperature reference matrix.
- the performance detection device may further include:
- the comparison unit is used to compare the attenuation constant with the attenuation after the attenuation constant determination unit averages all the temperature offsets of the single batteries to obtain the attenuation constant representing the performance attenuation degree of the battery thermal management system. Threshold to compare;
- An information output unit configured to output a prompt message indicating abnormal performance of the battery thermal management system when the decay constant is smaller than the decay threshold.
- the value of the attenuation threshold is determined according to actual needs, for example, the attenuation threshold is 0.4.
- the present invention determines whether the performance of the battery thermal management system is abnormal by comparing the attenuation constant with the attenuation threshold, and determines that the performance of the battery thermal management system is abnormal when the attenuation constant is less than the attenuation threshold.
- the prompt message of abnormal system performance reminds the owner to overhaul the battery thermal management system in time to avoid affecting the charge and discharge cycle efficiency of the battery pack and the power of the battery pack due to the failure of the thermal management system, as well as the thermal control ability of the battery thermal management system for the battery pack , so as to improve the safety and reliability of the battery pack, and avoid problems such as vehicle fire and insufficient power.
- the present invention also discloses a performance detection system of a battery thermal management system.
- FIG. 7 a schematic structural diagram of a performance detection system of a battery thermal management system disclosed in an embodiment of the present invention, the system includes: a vehicle-mounted mobile terminal 601, a TSP (Telematics Service Provider, automobile remote service provider) cloud platform 602 and a large Data cloud platform 603 .
- TSP Transmission Control Service Provider, automobile remote service provider
- the vehicle-mounted mobile terminal 601 is used to collect the battery pack operating condition data of the current electric vehicle in the current preset time period.
- the battery pack operating condition data includes: time stamp, battery pack output voltage, battery pack output current and battery pack at different times The maximum temperature of the single battery.
- the vehicle-mounted mobile terminal 601 is mainly a vehicle-mounted TBOX (Telematics BOX), and the TBOX is mainly used to collect the operating condition data of the battery pack of the current electric vehicle in the current preset time period, and send the operating condition data of the battery pack to To TSP cloud platform 602.
- TBOX vehicle-mounted TBOX
- the TSP cloud platform 602 is connected to the vehicle-mounted mobile terminal 601 and the big data cloud platform 603 respectively, and is used to send the battery pack operating condition data collected by the vehicle-mounted mobile terminal 601 to the big data cloud platform 603 .
- the big data cloud platform 603 includes the performance detection device of the battery thermal management system in the above embodiment.
- the performance detection device for the specific processing process of the battery pack operating condition data by the big data cloud platform 603, please refer to the corresponding part of the performance detection device, which will not be repeated here.
- the big data cloud platform 603 can also store the operating condition data of the battery pack sent by the TSP cloud platform 602, so as to process the operating condition data of the battery pack subsequently.
- the TSP cloud platform 602 in this embodiment can also receive the data from the big data cloud platform 603 based on the battery pack operating condition data.
- the performance test results of the thermal management system when the performance of the battery thermal management system declines or fails, the performance test results of the battery thermal management system can be pushed to the mobile terminal (such as a mobile phone) of the car owner.
- the invention also discloses an electronic device, which includes a memory and a processor
- the memory is used to store at least one instruction
- the processor is configured to execute the at least one instruction to implement the performance detection method of the battery thermal management system described in the method embodiment.
- the present invention also discloses a computer-readable storage medium, the computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed by a processor, the performance detection method of the battery thermal management system described in the method embodiment is implemented .
- the embodiment of the present invention discloses an electronic device and a computer-readable storage medium, which can detect the performance of the battery thermal management system based on the operating condition data of the battery pack of the electric vehicle.
- Management system performance so it can be determined whether the performance of the battery thermal management system has declined or failed according to the attenuation constant, so that when the performance of the battery thermal management system fails, the car owner is promptly reminded to maintain the battery thermal management system to avoid damage caused by thermal management.
- the failure of the system function affects the charge and discharge cycle efficiency of the battery pack and the power of the battery pack, as well as the thermal control ability of the battery thermal management system on the battery pack, thereby improving the safety and reliability of the battery pack, and avoiding problems such as vehicle fire and insufficient power .
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Abstract
一种电池热管理***的性能检测方法及相关设备，获取当前电动汽车在当前预设时间段的电池包运行工况数据(S101)；基于电池包运行工况数据构建当前电池温度矩阵(S102)，当前电池温度矩阵为电池包输出电压子区间-电池包输出电流子区间-电池包中单体电池温度最大值的三维矩阵；将当前电池温度矩阵中每个单体电池温度最大值与电池温度基准矩阵中对应的基准单体电池温度最大值求商得到单体电池温度偏移量(S103)；对所有的单体电池温度偏移量取平均值得到表征电池热管理***性能衰减程度的衰减常数(S104)。基于电动汽车的电池包运行工况数据实现了对电池热管理***的性能检测，且根据表征电池热管理***性能衰减程度的衰减常数的大小即可确定电池热管理***的性能是否下降或失效。
Description
本申请要求于2021年08月03日提交中国专利局、申请号为202110888094.0、发明名称为“一种电池热管理***的性能检测方法、装置及***”的国内申请的优先权，其全部内容通过引用结合在本申请中。
电池包作为电动汽车的核心部件，直接影响电动汽车的工作性能。当电动汽车在不同工况下行驶，电池包以不同倍率放电时，会产生大量热量，随着时间累积及空间影响会产生不均匀的热量聚集，造成电池包内温度分布不均衡，从而影响电池单体的一致性。如果整个电池包在高温下得不到及时的通风散热，过高的工作温度和过大的温度差异得不到缓解，将降低电池包充放电循环效率，影响电池包的功率和能量发挥，严重时还会造成热失控，最终影响电池包的安全性和可靠性。
为了使电池包发挥最佳性能，以及延长电池包的使用寿命，目前主要采用电池热管理***对电池包进行温度控制。电池热管理***采用冷却、温度均衡等方式，对外部环境温度对电池包可能造成的影响进行相应调整，并对电池包内部温度差异进行均衡，以使电池包的温度处于合理区间内。
因此，当电池热管理***的性能下降甚至失效时，将影响电池包的充放电循环效率以及电池包的功率，严重时还会导致电池包的热失控，最终影响电池包的安全性和可靠性，所以如何对电池热管理***的性能进行检测成为了本领域技术人员亟需解决的技术问题。
发明内容
有鉴于此，本发明公开一种电池热管理***的性能检测方法及相关设备，以实现对电池热管理***的性能检测。
一种电池热管理***的性能检测方法，包括：
获取当前电动汽车在当前预设时间段的电池包运行工况数据；
基于所述电池包运行工况数据构建当前电池温度矩阵，所述当前电池温度矩阵为：电池包输出电压子区间-电池包输出电流子区间-电池包中单 体电池温度最大值的三维矩阵；
将所述当前电池温度矩阵中每个单体电池温度最大值与预先构建的电池温度基准矩阵中对应的基准单体电池温度最大值求商，得到单体电池温度偏移量，其中，所述单体电池温度最大值和所述基准单体电池温度最大值对应相同的电池包输出电压子区间和相同的电池包输出电流子区间；
对所有的所述单体电池温度偏移量取平均值，得到表征电池热管理***性能衰减程度的衰减常数。
可选的，所述获取当前电动汽车在当前预设时间段的电池包运行工况数据，具体包括：
获取所述当前电动汽车在所述当前预设时间段的原始电池包运行工况数据；
基于所述原始电池包运行工况数据中的时间戳，将所述原始电池包运行工况数据中不满足预设车辆连续运行条件的电池包运行工况数据剔除，得到所述电池包运行工况数据。
可选的，所述基于所述电池包运行工况数据构建当前电池温度矩阵，具体包括：
将所述电池包运行工况数据中所有的电池包输出电压划分成N1个电池包输出电压子区间，N1为正整数；
将所述电池包运行工况数据中所有的电池包输出电流划分成M1个电池包输出电流子区间，M1为正整数；
计算所述电池包运行工况数据中与每个所述电池包输出电压子区间以及每个所述电池包输出电流子区间同时对应的所有的原始单体电池温度最大值的平均值，并将所述平均值作为电池包中单体电池温度最大值；
基于N1个所述电池包输出电压子区间、M1个所述电池包输出电流子区间以及对应的所述单体电池温度最大值，构建得到所述当前电池温度矩阵。
可选的，所述电池温度基准矩阵的构建过程包括：
获取电动汽车在历史预设时间段的电池包历史运行工况数据；
基于所述电池包历史运行工况数据中的时间戳，将所述电池包历史运行工况数据中不满足预设车辆连续运行条件的电池包历史运行工况数据剔 除，得到目标历史运行工况数据；
将所述目标历史运行工况数据中所有的历史电池包输出电压划分成N2个历史电池包输出电压子区间，N2为正整数；
将所述目标历史运行工况数据中所有的历史电池包输出电流划分成M2个历史电池包输出电流子区间，M2为正整数；
计算所述目标历史运行工况数据中与每个所述历史电池包输出电压子区间以及每个所述历史电池包输出电流子区间同时对应的所有的历史单体电池温度最大值的平均值，并将所述平均值作为所述基准单体电池温度最大值；
基于N2个所述历史电池包输出电压子区间、M2个所述历史电池包输出电流子区间以及对应的所述基准单体电池温度最大值，构建得到所述电池温度基准矩阵。
可选的，在所述对所有的所述单体电池温度偏移量取平均值，得到表征电池热管理***性能衰减程度的衰减常数之后，还包括：
将所述衰减常数与衰减阈值进行比较；
当所述衰减常数小于所述衰减阈值时，输出电池热管理***性能异常的提示信息。
可选的，所述对所有的所述单体电池温度偏移量取平均值，得到表征电池热管理***性能衰减程度的衰减数，具体包括：
基于每个所述单体电池温度偏移量以及所述当前电池温度矩阵中的电池包输出电压子区间和电池包输出电流子区间，构建当前电池温度偏移矩阵；
将所述当前电池温度偏移矩阵中所有的所述单体电池温度偏移量取平均值，得到所述衰减数。
一种电池热管理***的性能检测装置，包括：
数据获取单元，用于获取当前电动汽车在当前预设时间段的电池包运行工况数据；
第一矩阵构建单元，用于基于所述电池包运行工况数据构建当前电池温度矩阵，所述当前电池温度矩阵为：电池包输出电压子区间-电池包输出电流子区间-电池包中单体电池温度最大值的三维矩阵；
偏移量确定单元，用于将所述当前电池温度矩阵中每个单体电池温度最大值与预先构建的电池温度基准矩阵中对应的基准单体电池温度最大值求商，得到单体电池温度偏移量，其中，所述单体电池温度最大值和所述基准单体电池温度最大值对应相同的电池包输出电压子区间和相同的电池包输出电流子区间；
衰减常数确定单元，用于对所有的所述单体电池温度偏移量取平均值，得到表征电池热管理***性能衰减程度的衰减常数。
可选的，所述第一矩阵构建单元具体包括：
第一电压划分子单元，用于将所述电池包运行工况数据中所有的电池包输出电压划分成N1个电池包输出电压子区间，N1为正整数；
第一电流划分子单元，用于将所述电池包运行工况数据中所有的电池包输出电流划分成M1个电池包输出电流子区间，M1为正整数；
第一计算子单元，用于计算所述电池包运行工况数据中与每个所述电池包输出电压子区间以及每个所述电池包输出电流子区间同时对应的所有的原始单体电池温度最大值的平均值，并将所述平均值作为电池包中单体电池温度最大值；
第一矩阵构建子单元，用于基于N1个所述电池包输出电压子区间、M1个所述电池包输出电流子区间以及对应的所述单体电池温度最大值，构建得到所述当前电池温度矩阵。
可选的，还包括：
比较单元，用于在所述衰减常数确定单元在对所有的所述单体电池温度偏移量取平均值，得到表征电池热管理***性能衰减程度的衰减常数之后，将所述衰减常数与衰减阈值进行比较；
信息输出单元，用于当所述衰减常数小于所述衰减阈值时，输出电池热管理***性能异常的提示信息。
一种电池热管理***的性能检测***，包括：车载移动终端、TSP云平台和大数据云平台，所述大数据云平台包括上述所述的电池热管理***的性能检测装置；
所述车载移动终端，用于采集当前电动汽车在当前预设时间段的电池包运行工况数据；
所述TSP云平台分别与所述车载移动终端和所述大数据云平台连接，用于将所述车载移动终端采集的所述电池包运行工况数据发送至所述大数据云平台。
一种电子设备，所述电子设备包括存储器和处理器；
所述存储器用于存储至少一个指令；
所述处理器用于执行所述至少一个指令以实现上述所述的电池热管理***的性能检测方法。
一种计算机可读存储介质，所述计算机可读存储介质存储至少一个指令，所述至少一个指令被处理器执行时实现上述所述的电池热管理***的性能检测方法。
从上述的技术方案可知，本发明公开了一种电池热管理***的性能检测方法及相关设备，基于当前电动汽车在当前预设时间段的电池包运行工况数据构建当前电池温度矩阵，当前电池温度矩阵为电池包输出电压子区间-电池包输出电流子区间-电池包中单体电池温度最大值的三维矩阵，将当前电池温度矩阵中每个单体电池温度最大值与预先构建的电池温度基准矩阵中对应的基准单体电池温度最大值求商得到单体电池温度偏移量，通过对所有的单体电池温度偏移量取平均值，得到表征电池热管理***性能衰减程度的衰减常数。由此可以看出，本发明基于电动汽车的电池包运行工况数据实现了对电池热管理***的性能检测，由于本发明用衰减常数表征电池热管理***性能，因此根据衰减常数的大小即可确定电池热管理***的性能是否下降或失效，以便在电池热管理***的性能失效时，及时提醒车主对电池热管理***进行维修，避免因热管理***功能失效影响电池包的充放电循环效率和电池包的功率，以及电池热管理***对电池包的热控制能力，从而提高电池包的安全性和可靠性，避免导致车辆着火、动力不足等问题。
为了更清楚地说明本发明实施例或现有技术中的技术方案，下面将对 实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据公开的附图获得其他的附图。
图1为本发明实施例公开的一种电池热管理***的性能检测方法流程图；
图2为本发明实施例公开的一种基于电池包运行工况数据构建当前电池温度矩阵的方法流程图；
图3为本发明实施例公开的一种电池温度基准矩阵的构建方法流程图，该方法应用于大数据云平台；
图4为本发明实施例公开的一种电动汽车的电池热管理***在预设时间段的衰减程度曲线示意图；
图5为本发明实施例公开的一种电池热管理***的性能检测装置的结构示意图；
图6为本发明实施例公开的一种第一矩阵构建单元的结构示意图；
图7为本发明实施例公开的一种电池热管理***的性能检测***的结构示意图。
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的区间。
本发明实施例公开了一种电池热管理***的性能检测方法及相关设备，基于电动汽车的电池包运行工况数据实现对电池热管理***的性能检测，由于本发明用衰减常数表征电池热管理***性能，因此根据衰减常数的大小即可确定电池热管理***的性能是否下降或失效，以便在电池热管理***的性能失效时，及时提醒车主对电池热管理***进行维修，避免因热管理***功能失效影响电池包的充放电循环效率和电池包的功率，以及 电池热管理***对电池包的热控制能力，从而提高电池包的安全性和可靠性，避免导致车辆着火，动力不足等问题。
参见图1，本发明实施例公开的一种电池热管理***的性能检测方法流程图，该方法应用于大数据云平台，该方法包括：
步骤S101、获取当前电动汽车在当前预设时间段的电池包运行工况数据；
电池包运行工况数据包括：时间戳、电池包输出电压、电池包输出电流和不同时刻的电池包中单体电池温度最大值。
其中，当前预设时间段的取值依据实际需要而定，比如一天，本发明在此不做限定。
步骤S102、基于所述电池包运行工况数据构建当前电池温度矩阵；
其中，所述当前电池温度矩阵为：电池包输出电压子区间-电池包输出电流子区间-电池包中单体电池温度最大值的三维矩阵。
当电池包运行工况数据为当前电动汽车当天的电池包运行工况数据时，构建的当前电池温度矩阵实际为：日电池温度矩阵DayMax。
具体的，参见图2，本发明实施例公开的一种基于电池包运行工况数据构建当前电池温度矩阵的方法流程图，该方法包括：
步骤S201、将电池包运行工况数据中所有的电池包输出电压划分成N1个电池包输出电压子区间，N1为正整数；
在实际应用中，可以根据所有的电池包输出电压中电池包输出电压最大值和电池包输出电压最小值，确定电池包输出电压子区间的划分标准。
举例说明，将电池包运行工况数据中所有的电池包输出电压划分成10个电池包输出电压子区间，分别为：[310，320)、[320，330)、[330，340)、[340，350)、[350，360)、[360，370)、[370，380)、[380，390)、[390，400)和[400，410)。
步骤S202、将所述电池包运行工况数据中所有的电池包输出电流划分成M1个电池包输出电流子区间，M1为正整数；
举例说明，假设将电池包运行工况数据中所有的电池包输出电流划分成6个电池包输出电流子区间，分别为：[30，40)、[40，50)、[50，60)、[60，70)、[80，90)和[90，100)。
步骤S203、计算所述电池包运行工况数据中与每个所述电池包输出电压子区间以及每个所述电池包输出电流子区间同时对应的所有的原始单体电池温度最大值的平均值，并将所述平均值作为电池包中单体电池温度最大值；
举例说明，计算电池包输出电流处于[40，50)且电池包输出电压处于[320，330)区间内所有的原始单体电池温度最大值的平均值，得到19.33，并将19.33确定为与电池包输出电流子区间[40，50)以及电池包输出电压子区间[320，330)区间同时对应的单体电池温度最大值。
步骤S204、基于N1个所述电池包输出电压子区间、M1个所述电池包输出电流子区间以及对应的所述单体电池温度最大值，构建得到所述当前电池温度矩阵。
假设，电池包运行工况数据为当前电动汽车当天的电池包运行工况数据，当前电池温度矩阵为日电池温度矩阵DayMax。
N1＝10，电池包输出电压子区间，分别为：[310，320)、[320，330)、[330，340)、[340，350)、[350，360)、[360，370)、[370，380)、[380，390)、[390，400)和[400，410)；
M1＝6，电池包输出电流子区间，分别为：[30，40)、[40，50)、[50，60)、[60，70)、[80，90)和[90，100)；
则日电池温度矩阵DayMax如表1所示。
表1
步骤S103、将所述当前电池温度矩阵中每个单体电池温度最大值与预先构建的电池温度基准矩阵中对应的基准单体电池温度最大值求商，得到单体电池温度偏移量；
其中，所述单体电池温度最大值和所述基准单体电池温度最大值对应相同的电池包输出电压子区间和相同的电池包输出电流子区间。
需要说明的是，电池温度基准矩阵基于电动汽车在历史预设时间段的电池包历史运行工况数据得到，电池温度基准矩阵具体为：历史电池包输出电压子区间-历史电池包输出电流子区间-基准单体电池温度最大值的三维矩阵。
举例说明，假设电池温度基准矩阵如表2所示。
表2
举例说明计算单体电池温度偏移量的过程，从表1中可以看出，日电池温度矩阵中DayMax电池包输出电压子区间[310，320)和电池包输出电流子区间[30，40)对应的单体电池温度最大值为17.20，从表2中可以看出，电池温度基准矩阵BaseMax中历史电池包输出电压子区间[310，320)和历史电池包输出电流子区间[30，40)对应的基准单体电池温度最大值为19.33，则电池包输出电压子区间[310，320)和电池包输出电流子区间[30，40)对应的单体电池温度偏移量为：17.20÷19.33＝0.89。
按照上述方法，依次计算日电池温度矩阵中每个单体电池温度最大值对应的单体电池温度偏移量。
步骤S104、对所有的所述单体电池温度偏移量取平均值，得到表征电池热管理***性能衰减程度的衰减常数。
本实施例中，根据衰减常数的大小可以衡量电池热管理***的性能相较于初始性能的衰减程度。
综上可知，本发明公开了一种电池热管理***的性能检测方法，基于当前电动汽车在当前预设时间段的电池包运行工况数据构建当前电池温度矩阵，当前电池温度矩阵为电池包输出电压子区间-电池包输出电流子区间-电池包中单体电池温度最大值的三维矩阵，将当前电池温度矩阵中每个单体电池温度最大值与预先构建的电池温度基准矩阵中对应的基准单体电池 温度最大值求商得到单体电池温度偏移量，通过对所有的单体电池温度偏移量取平均值，得到表征电池热管理***性能衰减程度的衰减常数。由此可以看出，本发明基于电动汽车的电池包运行工况数据实现了对电池热管理***的性能检测，由于本发明用衰减常数表征电池热管理***性能，因此根据衰减常数的大小即可确定电池热管理***的性能是否下降或失效，以便在电池热管理***的性能失效时，及时提醒车主对电池热管理***进行维修，避免因热管理***功能失效影响电池包的充放电循环效率和电池包的功率，以及电池热管理***对电池包的热控制能力，从而提高电池包的安全性和可靠性，避免导致车辆着火、动力不足等问题。
为尽量降低环境温度对电池包运行工况数据的影响，保证电池包运行工况数据为车辆连续运行时生成的数据，本发明在获取原始电池包运行工况数据后，还会对不满足预设车辆连续运行条件的电池包运行工况数据剔除。
因此，为进一步优化上述实施例，步骤S101具体可以包括：
获取所述当前电动汽车在所述当前预设时间段的原始电池包运行工况数据；
基于所述原始电池包运行工况数据中的时间戳，将所述原始电池包运行工况数据中不满足预设车辆连续运行条件的电池包运行工况数据剔除，得到所述电池包运行工况数据。
其中，预设车辆连续运行条件可以依据电动汽车连续运行的时间或是连续运行的行程确定。
在实际应用中，获取的原始电池包运行工况数据中的各个工况数据均有对应的时间戳，基于该时间戳即可确定对应的运行工况数据是否为车辆连续运行时生成的数据。
比如，从原始电池包运行工况数据中剔除电动汽车运行时间小于30分钟的电池包运行工况数据，以保证剩余的所有的电池包运行工况数据均为电动汽车运行时间大于30分钟，运行里程大于2km时生成的运行工况数据，从而尽可能的降低环境温度的影响。
为进一步优化上述实施例，参见图3，本发明实施例公开的一种电池温度基准矩阵的构建方法流程图，该方法应用于大数据云平台，该方法包括：
步骤S301、获取电动汽车在历史预设时间段的电池包历史运行工况数据；
其中，历史预设时间段的取值依据实际需要而定，比如电动汽车从开机开始两个月的电池包历史运行工况数据。为获取更多的电池包历史运行工况数据，在实际应用中，可以获取多辆电动汽车在历史预设时间段的电池包历史运行工况数据。
电池包历史运行工况数据包括：时间戳、历史电池包输出电压、历史电池包输出电流和不同时刻的电池包中历史单体电池温度最大值。
步骤S302、基于所述电池包历史运行工况数据中的时间戳，将所述电池包历史运行工况数据中不满足预设车辆连续运行条件的电池包历史运行工况数据剔除，得到目标历史运行工况数据；
步骤S303、将所述目标历史运行工况数据中所有的历史电池包输出电压划分成N2个历史电池包输出电压子区间，N2为正整数；
步骤S304、将所述目标历史运行工况数据中所有的历史电池包输出电流划分成M2个历史电池包输出电流子区间，M2为正整数；
步骤S305、计算所述目标历史运行工况数据中与每个所述历史电池包输出电压子区间以及每个所述历史电池包输出电流子区间同时对应的所有的历史单体电池温度最大值的平均值，并将所述平均值作为所述基准单体电池温度最大值；
步骤S306、基于N2个所述历史电池包输出电压子区间、M2个所述历史电池包输出电流子区间以及对应的所述基准单体电池温度最大值，构建得到所述电池温度基准矩阵。
其中，步骤S302～步骤S306的具体过程可参见图2所示实施例对应部分，此处不再赘述。
需要说明的是，在实际应用中，可以通过计算当前电池温度矩阵中每个单体电池温度最大值对应的单体电池温度偏移量，构建当前电池温度矩 阵对应的当前电池温度偏移矩阵。
因此，为进一步优化上述实施例，步骤S104具体可以包括：
基于每个所述单体电池温度偏移量以及所述当前电池温度矩阵中的电池包输出电压子区间和电池包输出电流子区间，构建当前电池温度偏移矩阵；
将所述当前电池温度偏移矩阵中所有的所述单体电池温度偏移量取平均值，得到所述衰减数。
举例说明，假设当前电池温度矩阵为表1中示出的日电池温度矩阵DayMax，当采用步骤S103计算得到日电池温度矩阵中每个单体电池温度最大值对应的单体电池温度偏移量后，就可以基于每个单体电池温度偏移率以及日电池温度矩阵DayMax中的电池包输出电压子区间和电池包输出电流子区间，构建表3所示的日电池温度偏移矩阵BiasMax。
表3
从表3中可以看出，电池包输出电压子区间[310，320)和电池包输出 电流子区间[30，40)对应的单体电池温度偏移量为：0.89，与上述计算电池包输出电压子区间[310，320)和电池包输出电流子区间[30，40)对应的单体电池温度偏移量：17.20÷19.33＝0.89的结果一致。
日电池温度偏移矩阵BiasMax中其他的各个单体电池温度偏移量的具体计算过程可参见步骤S103。
从步骤S104可以看出，本发明通过将所有的单体电池温度偏移量取平均值，得到表征电池热管理***性能衰减程度的衰减常数BiasDayMax。在实际应用中，随着电动汽车不断的运行，电池包运行工况数据也不断的增多，如果从2021/1/1～2021/1/11每天都计算得到一个衰减常数BiasDayMax，则可以得到表4所示内容。
表4
| BiasDayMax | |
| 2021/1/1 | 0.97 |
| 2021/1/2 | 0.92 |
| 2021/1/3 | 0.96 |
| 2021/1/4 | 0.96 |
| 2021/1/5 | 0.89 |
| 2021/1/6 | 0.94 |
| 2021/1/7 | 0.83 |
| 2021/1/8 | 0.92 |
| 2021/1/9 | 0.88 |
| 2021/1/10 | 0.92 |
| 2021/1/11 | 0.92 |
通过对表4中所示的衰减常数BiasDayMax进行绘制，可以得到图4 所示的电动汽车的电池热管理***在预设时间段2021/1/1～2021/1/11期间的衰减程度曲线示意图。
在实际应用中，可以根据衰减常数的数值大小，确定电池热管理***的性能是否异常以及是否需要检修。
因此，为进一步优化上述实施例，在步骤S104之后，还可以包括：
将衰减常数与衰减阈值进行比较；
当所述衰减常数小于所述衰减阈值时，输出电池热管理***性能异常的提示信息。
其中，衰减阈值的取值依据实际需要而定，比如，衰减阈值为0.4。
综上可知，本发明通过将衰减常数与衰减阈值进行比较来确定电池热管理***的性能是否异常，并在衰减常数小于衰减阈值时，确定电池热管理***性能异常，此时通过输出电池热管理***性能异常的提示信息提醒车主及时对电池热管理***进行检修，避免因热管理***功能失效影响电池包的充放电循环效率和电池包的功率，以及电池热管理***对电池包的热控制能力，从而提高电池包的安全性和可靠性，避免导致车辆着火，动力不足等问题。
与上述方法实施例相对应，本发明还公开了一种电池热管理***的性能检测装置。
参见图5，本发明实施例公开的一种电池热管理***的性能检测装置的结构示意图，该装置应用于大数据云平台，该装置包括：
数据获取单元401，用于获取当前电动汽车在当前预设时间段的电池包运行工况数据；
电池包运行工况数据包括：时间戳、电池包输出电压、电池包输出电流和不同时刻的电池包中单体电池温度最大值。
其中，当前预设时间段的取值依据实际需要而定，比如一天，本发明在此不做限定。
第一矩阵构建单元402，用于基于所述电池包运行工况数据构建当前电池温度矩阵，所述当前电池温度矩阵为：电池包输出电压子区间-电池包 输出电流子区间-电池包中单体电池温度最大值的三维矩阵；
偏移量确定单元403，用于将所述当前电池温度矩阵中每个单体电池温度最大值与预先构建的电池温度基准矩阵中对应的基准单体电池温度最大值求商，得到单体电池温度偏移量；
其中，所述单体电池温度最大值和所述基准单体电池温度最大值对应相同的电池包输出电压子区间和相同的电池包输出电流子区间。
衰减常数确定单元404，用于对所有的所述单体电池温度偏移量取平均值，得到表征电池热管理***性能衰减程度的衰减常数。
本实施例中，根据衰减常数的大小可以衡量电池热管理***的性能相较于初始性能的衰减程度。
综上可知，本发明公开了一种电池热管理***的性能检测装置，基于当前电动汽车在当前预设时间段的电池包运行工况数据构建当前电池温度矩阵，当前电池温度矩阵为电池包输出电压子区间-电池包输出电流子区间-电池包中单体电池温度最大值的三维矩阵，将当前电池温度矩阵中每个单体电池温度最大值与预先构建的电池温度基准矩阵中对应的基准单体电池温度最大值求商得到单体电池温度偏移量，通过对所有的单体电池温度偏移量取平均值，得到表征电池热管理***性能衰减程度的衰减常数。由此可以看出，本发明基于电动汽车的电池包运行工况数据实现了对电池热管理***的性能检测，由于本发明用衰减常数表征电池热管理***性能，因此根据衰减常数的大小即可确定电池热管理***的性能是否下降或失效，以便在电池热管理***的性能失效时，及时提醒车主对电池热管理***进行维修，避免因热管理***功能失效影响电池包的充放电循环效率和电池包的功率，以及电池热管理***对电池包的热控制能力，从而提高电池包的安全性和可靠性，避免导致车辆着火，动力不足等问题。
为尽量降低环境温度对电池包运行工况数据的影响，保证电池包运行工况数据为车辆连续运行时生成的数据，本发明在获取原始电池包运行工况数据后，还会对不满足预设车辆连续运行条件的电池包运行工况数据剔除。
因此，为进一步优化上述实施例，数据获取单元401具体可以用于：
获取所述当前电动汽车在所述当前预设时间段的原始电池包运行工况数据；
基于所述原始电池包运行工况数据中的时间戳，将所述原始电池包运行工况数据中不满足预设车辆连续运行条件的电池包运行工况数据剔除，得到所述电池包运行工况数据。
其中，预设车辆连续运行条件可以依据电动汽车连续运行的时间或是连续运行的行程确定。
在实际应用中，获取的原始电池包运行工况数据中的各个工况数据均有对应的时间戳，基于该时间戳即可确定对应的运行工况数据是否为车辆连续运行时生成的数据。
比如，从原始电池包运行工况数据中剔除电动汽车运行时间小于30分钟的电池包运行工况数据，以保证剩余的所有的电池包运行工况数据均为电动汽车运行时间大于30分钟，运行里程大于2km时生成的运行工况数据，从而尽可能的降低环境温度的影响。
为进一步优化上述实施例，参见图6本发明实施例公开的一种第一矩阵构建单元的结构示意图，第一矩阵构建单元包括：
第一电压划分子单元501，用于将所述电池包运行工况数据中所有的电池包输出电压划分成N1个电池包输出电压子区间，N1为正整数；
电池包历史运行工况数据包括：时间戳、历史电池包输出电压、历史电池包输出电流和不同时刻的电池包中历史单体电池温度最大值。
第一电流划分子单元502，用于将所述电池包运行工况数据中所有的电池包输出电流划分成M1个电池包输出电流子区间，M1为正整数；
第一计算子单元503，用于计算所述电池包运行工况数据中与每个所述电池包输出电压子区间以及每个所述电池包输出电流子区间同时对应的所有的原始单体电池温度最大值的平均值，并将所述平均值作为电池包中单体电池温度最大值；
第一矩阵构建子单元504，用于基于N1个所述电池包输出电压子区间、M1个所述电池包输出电流子区间以及对应的所述单体电池温度最大值，构建得到所述当前电池温度矩阵。
需要说明的是，在实际应用中，可以通过计算当前电池温度矩阵中每个单体电池温度最大值对应的单体电池温度偏移量，构建当前电池温度矩阵对应的当前电池温度偏移矩阵。
因此，为进一步优化上述实施例，衰减常数确定单元404具体可以用于：
基于每个所述单体电池温度偏移量以及所述当前电池温度矩阵中的电池包输出电压子区间和电池包输出电流子区间，构建当前电池温度偏移矩阵；
将所述当前电池温度偏移矩阵中所有的所述单体电池温度偏移量取平均值，得到所述衰减数。
为进一步优化上述实施例，性能检测装置还可以包括：
第二矩阵构建单元，用于构建所述电池温度基准矩阵。
所述第二矩阵构建单元具体包括：
数据获取子单元，用于获取电动汽车在历史预设时间段的电池包历史运行工况数据；
数据筛选子单元，用于基于所述电池包历史运行工况数据中的时间戳，将所述电池包历史运行工况数据中不满足预设车辆连续运行条件的电池包历史运行工况数据剔除，得到目标历史运行工况数据；
第二电压划分子单元，用于将所述目标历史运行工况数据中所有的历史电池包输出电压划分成N2个历史电池包输出电压子区间，N2为正整数；
第二电流划分子单元，用于将所述目标历史运行工况数据中所有的历史电池包输出电流划分成M2个历史电池包输出电流子区间，M2为正整数；
第二计算子单元，用于计算所述目标历史运行工况数据中与每个所述历史电池包输出电压子区间以及每个所述历史电池包输出电流子区间同时对应的所有的历史单体电池温度最大值的平均值，并将所述平均值作为所述基准单体电池温度最大值；
第二矩阵构建子单元，用于基于N2个所述历史电池包输出电压子区 间、M2个所述历史电池包输出电流子区间以及对应的所述基准单体电池温度最大值，构建得到所述电池温度基准矩阵。
在实际应用中，可以根据衰减常数的数值大小，确定电池热管理***的性能是否异常以及是否需要检修。
因此，为进一步优化上述实施例，性能检测装置还可以包括：
比较单元，用于在所述衰减常数确定单元在对所有的所述单体电池温度偏移量取平均值，得到表征电池热管理***性能衰减程度的衰减常数之后，将所述衰减常数与衰减阈值进行比较；
信息输出单元，用于当所述衰减常数小于所述衰减阈值时，输出电池热管理***性能异常的提示信息。
其中，衰减阈值的取值依据实际需要而定，比如，衰减阈值为0.4。
综上可知，本发明通过将衰减常数与衰减阈值进行比较来确定电池热管理***的性能是否异常，并在衰减常数小于衰减阈值时，确定电池热管理***性能异常，此时通过输出电池热管理***性能异常的提示信息提醒车主及时对电池热管理***进行检修，避免因热管理***功能失效影响电池包的充放电循环效率和电池包的功率，以及电池热管理***对电池包的热控制能力，从而提高电池包的安全性和可靠性，避免导致车辆着火，动力不足等问题。
需要特别说明的是，装置实施例中各组成部分的具体工作原理，请参见方法实施例对应部分，此处不再赘述。
与上述实施例相对应，本发明还公开了一种电池热管理***的性能检测***。
参见图7，本发明实施例公开的一种电池热管理***的性能检测***的结构示意图，该***包括：车载移动终端601、TSP(Telematics Service Provider，汽车远程服务提供商)云平台602和大数据云平台603。
其中：
车载移动终端601用于采集当前电动汽车在当前预设时间段的电池包运行工况数据，电池包运行工况数据包括：时间戳、电池包输出电压、电 池包输出电流和不同时刻的电池包中单体电池温度最大值。
在实际应用中，车载移动终端601主要为车载TBOX(Telematics BOX)，TBOX主要用于采集当前电动汽车在当前预设时间段的电池包运行工况数据，并将该电池包运行工况数据发送至TSP云平台602。
TSP云平台602分别与车载移动终端601和大数据云平台603连接，用于将车载移动终端601采集的所述电池包运行工况数据发送至大数据云平台603。
大数据云平台603包括上述实施例中的电池热管理***的性能检测装置，大数据云平台603对电池包运行工况数据的具体处理过程可参见性能检测装置相应部分，此处不再赘述。
需要说明的是，大数据云平台603还可以对TSP云平台602发送的电池包运行工况数据进行存储，以便后续对电池包运行工况数据进行处理。
本实施例中的TSP云平台602除了将车载移动终端601采集的所述电池包运行工况数据发送至大数据云平台603，还可以接收大数据云平台603基于电池包运行工况数据对电池热管理***的性能检测结果，当电池热管理***的性能下降或失效时，可以将电池热管理***的性能检测结果推送至车主的移动终端(如手机)上。
本发明还公开了一种电子设备，电子设备包括存储器和处理器；
所述存储器用于存储至少一个指令；
所述处理器用于执行所述至少一个指令以实现方法实施例所述的电池热管理***的性能检测方法。
本发明还公开了一种计算机可读存储介质，所述计算机可读存储介质存储至少一个指令，所述至少一个指令被处理器执行时实现方法实施例所述的电池热管理***的性能检测方法。
需要特别说明的是，电子设备和计算机可读存储介质在进行电池热管理***的性能检测时采用的工作原理，请参见方法实施例对应部分，此处不再赘述。
综上可知，本发明实施例公开了一种电子设备及计算机可读存储介质，基于电动汽车的电池包运行工况数据实现对电池热管理***的性能检测， 由于本发明用衰减常数表征电池热管理***性能，因此根据衰减常数的大小即可确定电池热管理***的性能是否下降或失效，以便在电池热管理***的性能失效时，及时提醒车主对电池热管理***进行维修，避免因热管理***功能失效影响电池包的充放电循环效率和电池包的功率，以及电池热管理***对电池包的热控制能力，从而提高电池包的安全性和可靠性，避免导致车辆着火，动力不足等问题。
最后，还需要说明的是，在本文中，诸如第一和第二等之类的关系术语仅仅用来将一个实体或者操作与另一个实体或操作区分开来，而不一定要求或者暗示这些实体或操作之间存在任何这种实际的关系或者顺序。而且，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者设备所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括所述要素的过程、方法、物品或者设备中还存在另外的相同要素。
本说明书中各个实施例采用递进的方式描述，每个实施例重点说明的都是与其他实施例的不同之处，各个实施例之间相同相似部分互相参见即可。
对所公开的实施例的上述说明，使本领域专业技术人员能够实现或使用本发明。对这些实施例的多种修改对本领域的专业技术人员来说将是显而易见的，本文中所定义的一般原理可以在不脱离本发明的精神或区间的情况下，在其它实施例中实现。因此，本发明将不会被限制于本文所示的这些实施例，而是要符合与本文所公开的原理和新颖特点相一致的最宽的区间。
Claims (12)
- 一种电池热管理***的性能检测方法，其特征在于，包括：获取当前电动汽车在当前预设时间段的电池包运行工况数据；基于所述电池包运行工况数据构建当前电池温度矩阵，所述当前电池温度矩阵为：电池包输出电压子区间-电池包输出电流子区间-电池包中单体电池温度最大值的三维矩阵；将所述当前电池温度矩阵中每个单体电池温度最大值与预先构建的电池温度基准矩阵中对应的基准单体电池温度最大值求商，得到单体电池温度偏移量，其中，所述单体电池温度最大值和所述基准单体电池温度最大值对应相同的电池包输出电压子区间和相同的电池包输出电流子区间；对所有的所述单体电池温度偏移量取平均值，得到表征电池热管理***性能衰减程度的衰减常数。
- 根据权利要求1所述的性能检测方法，其特征在于，所述获取当前电动汽车在当前预设时间段的电池包运行工况数据，具体包括：获取所述当前电动汽车在所述当前预设时间段的原始电池包运行工况数据；基于所述原始电池包运行工况数据中的时间戳，将所述原始电池包运行工况数据中不满足预设车辆连续运行条件的电池包运行工况数据剔除，得到所述电池包运行工况数据。
- 根据权利要求1所述的性能检测方法，其特征在于，所述基于所述电池包运行工况数据构建当前电池温度矩阵，具体包括：将所述电池包运行工况数据中所有的电池包输出电压划分成N1个电池包输出电压子区间，N1为正整数；将所述电池包运行工况数据中所有的电池包输出电流划分成M1个电池包输出电流子区间，M1为正整数；计算所述电池包运行工况数据中与每个所述电池包输出电压子区间以及每个所述电池包输出电流子区间同时对应的所有的原始单体电池温度最大值的平均值，并将所述平均值作为电池包中单体电池温度最大值；基于N1个所述电池包输出电压子区间、M1个所述电池包输出电流子 区间以及对应的所述单体电池温度最大值，构建得到所述当前电池温度矩阵。
- 根据权利要求1所述的性能检测方法，其特征在于，所述电池温度基准矩阵的构建过程包括：获取电动汽车在历史预设时间段的电池包历史运行工况数据；基于所述电池包历史运行工况数据中的时间戳，将所述电池包历史运行工况数据中不满足预设车辆连续运行条件的电池包历史运行工况数据剔除，得到目标历史运行工况数据；将所述目标历史运行工况数据中所有的历史电池包输出电压划分成N2个历史电池包输出电压子区间，N2为正整数；将所述目标历史运行工况数据中所有的历史电池包输出电流划分成M2个历史电池包输出电流子区间，M2为正整数；计算所述目标历史运行工况数据中与每个所述历史电池包输出电压子区间以及每个所述历史电池包输出电流子区间同时对应的所有的历史单体电池温度最大值的平均值，并将所述平均值作为所述基准单体电池温度最大值；基于N2个所述历史电池包输出电压子区间、M2个所述历史电池包输出电流子区间以及对应的所述基准单体电池温度最大值，构建得到所述电池温度基准矩阵。
- 根据权利要求1所述的性能检测方法，其特征在于，在所述对所有的所述单体电池温度偏移量取平均值，得到表征电池热管理***性能衰减程度的衰减常数之后，还包括：将所述衰减常数与衰减阈值进行比较；当所述衰减常数小于所述衰减阈值时，输出电池热管理***性能异常的提示信息。
- 根据权利要求1所述的性能检测方法，其特征在于，所述对所有的所述单体电池温度偏移量取平均值，得到表征电池热管理***性能衰减程度的衰减数，具体包括：基于每个所述单体电池温度偏移量以及所述当前电池温度矩阵中的电池包输出电压子区间和电池包输出电流子区间，构建当前电池温度偏移矩 阵；将所述当前电池温度偏移矩阵中所有的所述单体电池温度偏移量取平均值，得到所述衰减数。
- 一种电池热管理***的性能检测装置，其特征在于，包括：数据获取单元，用于获取当前电动汽车在当前预设时间段的电池包运行工况数据；第一矩阵构建单元，用于基于所述电池包运行工况数据构建当前电池温度矩阵，所述当前电池温度矩阵为：电池包输出电压子区间-电池包输出电流子区间-电池包中单体电池温度最大值的三维矩阵；偏移量确定单元，用于将所述当前电池温度矩阵中每个单体电池温度最大值与预先构建的电池温度基准矩阵中对应的基准单体电池温度最大值求商，得到单体电池温度偏移量，其中，所述单体电池温度最大值和所述基准单体电池温度最大值对应相同的电池包输出电压子区间和相同的电池包输出电流子区间；衰减常数确定单元，用于对所有的所述单体电池温度偏移量取平均值，得到表征电池热管理***性能衰减程度的衰减常数。
- 根据权利要求7所述的性能检测装置，其特征在于，所述第一矩阵构建单元具体包括：第一电压划分子单元，用于将所述电池包运行工况数据中所有的电池包输出电压划分成N1个电池包输出电压子区间，N1为正整数；第一电流划分子单元，用于将所述电池包运行工况数据中所有的电池包输出电流划分成M1个电池包输出电流子区间，M1为正整数；第一计算子单元，用于计算所述电池包运行工况数据中与每个所述电池包输出电压子区间以及每个所述电池包输出电流子区间同时对应的所有的原始单体电池温度最大值的平均值，并将所述平均值作为电池包中单体电池温度最大值；第一矩阵构建子单元，用于基于N1个所述电池包输出电压子区间、M1个所述电池包输出电流子区间以及对应的所述单体电池温度最大值，构建得到所述当前电池温度矩阵。
- 根据权利要求7所述的性能检测装置，其特征在于，还包括：比较单元，用于在所述衰减常数确定单元在对所有的所述单体电池温度偏移量取平均值，得到表征电池热管理***性能衰减程度的衰减常数之后，将所述衰减常数与衰减阈值进行比较；信息输出单元，用于当所述衰减常数小于所述衰减阈值时，输出电池热管理***性能异常的提示信息。
- 一种电池热管理***的性能检测***，其特征在于，包括：车载移动终端、TSP云平台和大数据云平台，所述大数据云平台包括权利要求7～9任意一项所述的电池热管理***的性能检测装置；所述车载移动终端，用于采集当前电动汽车在当前预设时间段的电池包运行工况数据；所述TSP云平台分别与所述车载移动终端和所述大数据云平台连接，用于将所述车载移动终端采集的所述电池包运行工况数据发送至所述大数据云平台。
- 一种电子设备，其特征在于，所述电子设备包括存储器和处理器；所述存储器用于存储至少一个指令；所述处理器用于执行所述至少一个指令以实现如权利要求1～6任意一项所述的电池热管理***的性能检测方法。
- 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质存储至少一个指令，所述至少一个指令被处理器执行时实现如权利要求1～6任意一项所述的电池热管理***的性能检测方法。
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| CN202110888094.0A CN114966427A (zh) | 2021-08-03 | 2021-08-03 | 一种电池热管理***的性能检测方法、装置及*** |
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Cited By (4)
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| CN116256181A (zh) * | 2023-03-07 | 2023-06-13 | 苏州跃动汽车技术服务有限公司 | 一种混合动力汽车热管理***的测试方法及装置 |
| CN116882981A (zh) * | 2023-09-07 | 2023-10-13 | 深圳市海雷新能源有限公司 | 基于数据分析的智能电池管理*** |
| CN117250547A (zh) * | 2023-11-20 | 2023-12-19 | 深圳市菲尼基科技有限公司 | 一种电池储能***可靠性评估方法及*** |
| CN117972614A (zh) * | 2024-03-22 | 2024-05-03 | 东莞市欧派奇电子科技有限公司 | 一种移动电源充放电过程中的温度实时监测方法 |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115267589B (zh) * | 2022-09-26 | 2023-01-06 | 陕西汽车集团股份有限公司 | 一种电动汽车电池故障多参数联合诊断方法 |
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| EP4382936A1 (en) | 2024-06-12 |
| CN114966427A (zh) | 2022-08-30 |
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