Diagnostic method, device, medium and system for local cooling failure of battery system

Abstract

The present invention provides a method for diagnosing local cooling faults in a battery system, which aims to accurately determine local over-cooling or under-cooling faults by real-time monitoring of the temperature and voltage parameters of each area of ​​the battery system, combined with charge and discharge status analysis. The specific steps of this method are: dividing the battery system into several monitoring areas, collecting the temperature, battery cell voltage and system charge and discharge status of each area in real time and dividing the data time period according to preset conditions, statistically analyzing the temperature mean T, voltage mean U and their global statistics in each time period, and dynamically adjusting the C value of each area based on the charge and discharge status, and determining whether the area has an over-cooling or under-cooling fault by the C value. The present invention eliminates abnormal interference from the internal resistance of the battery through statistical principles, combines a long-term data accumulation mechanism to reduce the false alarm rate, and can be achieved by upgrading existing sensors and algorithms. It is suitable for scenarios such as electric vehicles and energy storage equipment, and has the advantages of high reliability and low cost.

Description

Technical Field

[0001] The present invention relates to the field of battery technology, and in particular to a method, device, medium and system for diagnosing a local cooling fault in a battery system. Background Art

[0002] Batteries, such as lithium-ion batteries, are currently widely used in a variety of fields, including electric vehicles, electrochemical energy storage devices, and power tools. Typically, multiple battery cells are connected in series and parallel to form a battery system to meet energy storage and power output requirements. The battery system generates a large amount of heat due to its internal resistance during charging and discharging, necessitating the use of cooling devices for thermal management. This aims to suppress excessive and rapid temperature rise in the battery system and maintain temperature consistency across all regions of the battery system to prevent localized overheating or underheating from impacting battery system performance.

[0003] The cooling devices of battery systems include various methods such as air cooling, liquid cooling and phase change material cooling, and are usually sophisticatedly designed to meet the temperature rise suppression and temperature consistency requirements of the battery system. However, failures are inevitable during the operation of the cooling device, so monitoring and diagnosis are required. For example, Chinese patents CN113511076A and CN112329357A both involve methods for diagnosing the failure of increased resistance in liquid cooling pipes used to cool electric vehicle battery packs. In terms of the temperature consistency of the battery system caused by the failure of the cooling device itself, there is currently a lack of scientific, reasonable, simple, easy-to-use and highly reliable monitoring and diagnosis methods, so new technical means are urgently needed. Summary of the Invention

[0004] The present invention provides a scientific, reasonable, simple, easy and reliable method for diagnosing local cooling faults in battery systems, and provides corresponding devices, media and systems for diagnosing whether there are local over-cooling and / or under-cooling faults during battery system operation, thereby promptly reminding users to check and maintain, so as to better maintain the temperature consistency of the battery system.

[0005] According to a first aspect of the present invention, a method for diagnosing a local cooling fault in a battery system is provided, wherein the battery system comprises battery cells connected in series and a cooling device. The method comprises:

[0006] The battery system is divided into several monitoring areas, and the initial value of the cooling coefficient C of each area is set to 0;

[0007] Real-time collection of the temperature of each area, the voltage of each battery unit, and the system charge and discharge status, where the charge and discharge status includes charging, discharging, and shelving;

[0008] The collected data is divided into time periods, and the division trigger conditions are any of the following conditions:

[0009] 1) The number of acquisitions reaches the preset value;

[0010] 2) Changes in charge and discharge status;

[0011] For each time period of collected data, the average temperature T and the average battery cell voltage U of each area in the time period are calculated, as well as the mean μ of all T values. T and standard deviation σ T , the mean value of all U values ​​μ U and standard deviation σ U :

[0012] If the time period is on hold:

[0013] 1) And there exists T>μ T +pσ T If the area is , the C value of the corresponding area is reduced by 1;

[0014] 2) and there exists T < μ T -pσ T If the area is , the C value of the corresponding area is increased by 1;

[0015] If the time period is charging state:

[0016] 1) And there exists T>μ T +pσ T And U<μ U +qσ U If the area is , the C value of the corresponding area is reduced by 1;

[0017] 2) There exists T < μ - pσ and U > μ U -qσ U If the area is , the C value of the corresponding area is increased by 1;

[0018] If the time period is the discharge state:

[0019] 1) And there exists T>μ T +pσ T And U>μ U -qσ U If the area is , the C value of the corresponding area is reduced by 1;

[0020] 2) There exists T < μ-pσ and U < μ U +qσ U If the area is , the C value of the corresponding area is increased by 1;

[0021] When the C value of a certain area is greater than C I Or if the net increase in the C value within the preset time is greater than ΔC, the area is judged to be overcooled;

[0022] When the C value of a certain area is less than C IIOr if the net decrease in the C value within the preset time is greater than ΔC, the area is judged to be insufficiently cooled;

[0023] The above p and q are coefficients greater than 0, C I >0>C II .

[0024] Specifically, in the above-mentioned method for diagnosing a local cooling fault of a battery system, the average voltage value U of the battery cells in a certain area within a certain time period is the average value of all voltage collection values ​​of all battery cells contained in the area within the time period.

[0025] Specifically, in the above-mentioned method for diagnosing a local cooling fault of a battery system, the battery unit is composed of one battery cell or a plurality of battery cells connected in parallel.

[0026] Optionally, in the above-mentioned method for diagnosing local cooling failure of the battery system, the frequency of real-time data acquisition is between 0.05 Hz and 1 Hz; the preset value of the number of acquisitions for dividing the acquired data into time periods is between 10 and 1000; and the preset time for determining whether there is excessive or insufficient regional cooling is between 10 minutes and 100 hours.

[0027] Optionally, in the above-mentioned method for diagnosing local cooling failure of the battery system, the coefficients p and q are both between 1 and 3, and C I Between 20 and 500, C II Between -500 and -20, ΔC between 10 and 1000.

[0028] According to a second aspect of the present invention, a device for diagnosing a local cooling fault in a battery system is provided, for implementing any of the above-mentioned methods for diagnosing a local cooling fault in a battery system. The device comprises a collection module, a storage module, an analysis module, and an output module.

[0029] The acquisition module includes a temperature sensor, a voltage sensor, and a current sensor, which are used to collect the temperature of each area, the voltage of each battery cell, and the charging and discharging status of the system respectively;

[0030] The storage module is used to receive and store the data collected by the acquisition module;

[0031] The analysis module is used to read data from the storage module and perform fault diagnosis analysis;

[0032] The output module is used to obtain and output the diagnostic results from the analysis module.

[0033] According to a third aspect of the present invention, a computer-readable storage medium is provided, storing a plurality of computer instructions, wherein the computer instructions are suitable for loading by a processor to execute any of the above-mentioned methods for diagnosing local cooling faults of a battery system.

[0034] According to a fourth aspect of the present invention, a battery system is provided, which integrates the above-mentioned diagnostic device for local cooling failure of the battery system.

[0035] Optionally, the battery system is mounted on an electric vehicle.

[0036] Optionally, the above-mentioned battery system is mounted on a battery energy storage device.

[0037] The beneficial effects of the technical solution of the present invention are introduced below in conjunction with the principle thereof.

[0038] The temperature of a specific area in a battery system is primarily determined by the heat generated by the battery cells during the charge and discharge process within that area and the cooling intensity applied by the cooling device. Because the battery cells are connected in series and carry equal current, the heat generated by each cell is related to its internal resistance. The magnitude of this internal resistance is typically reflected in the degree to which the voltage deviates from the equilibrium potential during the charge and discharge process. During charging, the battery voltage is higher than the equilibrium potential. Under the same conditions, the higher the cell voltage, the greater the internal resistance and, consequently, the higher the heat generation power. During discharging, the battery voltage is lower than the equilibrium potential. Under the same conditions, the lower the cell voltage, the greater the internal resistance and, consequently, the higher the heat generation power.

[0039] The present invention first divides the battery system into several areas and assigns an initial value of 0 to the cooling coefficient C of each area.

[0040] Then, during the operation of the battery system, the collected data of each time period is analyzed and processed to adjust the value of the cooling coefficient C of each area. The battery system is in the same working state within the same time period. Specifically, the average temperature T and the average battery cell voltage U of each area in the time period are calculated, as well as the mean of all T values ​​μ. T and standard deviation σ T , the mean value of all U values ​​μ U and standard deviation σ U , adjust the value of cooling coefficient C in each area:

[0041] (1) If the time period is idle, no current flows through the battery system and the battery itself generates almost no heat. It is only necessary to directly determine whether the temperature in the area is too high or too low based on statistical principles:

[0042] 1) When T>μ T +pσ T If there are areas with high temperatures relative to the whole area, it is initially believed that there may be insufficient cooling, so the C value of the corresponding area is reduced by 1;

[0043] 2) When T < μ T -pσ TWhen there are areas with low temperature relative to the whole area, it is initially believed that they may be overcooled, so the C value of the corresponding area is increased by 1.

[0044] (2) If the time period is charging, the battery system itself generates heat due to charging. It is necessary to further rule out whether the temperature abnormality is related to the abnormal heat generation of the battery itself.

[0045] 1) When T>μ T +pσ T It means that the temperature in these areas is relatively high. At the same time, if we further find that the corresponding areas U<μ U +qσ U , it means that there is no high voltage phenomenon in these areas, and it is preliminarily believed that the high temperature may be caused by insufficient cooling rather than excessive internal resistance, so the C value of the corresponding area is reduced by 1;

[0046] 2) When there are regions with T<μ-pσ, it means that the temperature in these regions is relatively low. At the same time, if we further find that the corresponding regions have U>μ U -qσ U , it means that there is no low voltage phenomenon in these areas, and it is preliminarily believed that the low temperature may be caused by excessive cooling rather than too small internal resistance, so the C value of the corresponding area is increased by 1;

[0047] If the time period is the discharge state:

[0048] 1) When T>μ T +pσ T It means that the temperature in these areas is relatively high. At the same time, if we further find that the corresponding areas U>μ U -qσ U , it means that there is no low voltage phenomenon in these areas, and it is preliminarily believed that the high temperature may be caused by insufficient cooling rather than excessive internal resistance, so the C value of the corresponding area is reduced by 1;

[0049] 2) When there are regions where T<μ-pσ, it means that the temperature in these regions is relatively low. At the same time, if we further find that the corresponding regions U<μ U +qσ U If there are areas with high voltage, it means that there is no high voltage phenomenon in these areas. It is preliminarily believed that the low temperature may be caused by excessive cooling rather than too small internal resistance, so the C value of the corresponding area is increased by 1.

[0050] The results of a single time period during battery system operation can only be considered preliminary. To avoid false positives, a final conclusion requires extensive long-term statistical verification. This is because actual operation may experience temporary fluctuations and instabilities due to various factors. For example, in a specific area, the C value may increase during a certain time period and decrease during another time period. However, over the long term, the C value generally remains stable near its initial value of 0.

[0051] When the C value of a certain area is greater than C I , it means that its C value has accumulated and increased over a long period of time, so it can be determined that the area is overcooled; when the net increase of the C value of a certain area within the preset time is greater than ΔC, it means that its C value has a trend of rapid increase, and it can also be determined that the area is overcooled.

[0052] Correspondingly, when the C value of a certain area is less than C II , it means that its C value has been decreasing cumulatively over a long period of time, so it can be determined that the area is not cooled enough; when the net decrease in the C value of a certain area within the preset time is greater than ΔC, it means that its C value has a trend of rapidly decreasing, and it can also be determined that the area is not cooled enough.

[0053] Insufficient or excessive local cooling in various areas are considered local cooling failures that have a significant impact on the temperature consistency of the battery system. The causes are multifaceted, such as local pipe blockage, uneven fluid distribution, and too tight or too loose fit between the cold plate and the battery cell. These problems are difficult to detect during the operation of the battery system.

[0054] From the above principles, it is not difficult to find that the technical solution of the present invention has the following beneficial effects:

[0055] (1) By drawing on the principles of heat transfer, electrochemistry, and statistics, and taking into account the factors affecting the temperature of the battery system area, the local cooling intensity and the heat generation power of the battery itself in the area, the possibility of abnormal heat generation caused by abnormal internal resistance of the battery in the corresponding area is first excluded when judging whether there is insufficient or excessive local cooling. Therefore, it is scientific and reasonable;

[0056] (2) The temperature, voltage and current sensors involved in the relevant diagnostic devices are common configurations of existing battery systems. Therefore, they basically only need to be supplemented at the software level to complete the adaptation of existing battery system products. They are low in cost, easy to implement, and highly versatile. At the same time, they are suitable for typical application scenarios of battery systems such as electric vehicles and battery energy storage.

[0057] (3) When it is preliminarily determined that abnormal temperatures occur in certain areas during a certain period of time, there is no rush to draw conclusions. Instead, sufficient data is accumulated and statistically significant before a diagnosis of local cooling failure is made. Therefore, the system is highly reliable and can avoid false alarms. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 This is a flow chart of a method for diagnosing local cooling faults in a battery system according to an embodiment of the present invention.

[0059] Figure 2 Schematic diagram of a local cooling fault diagnosis device for a battery system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0060] The present invention will be further described below with reference to the accompanying drawings and examples.

[0061] like Figure 1 As shown, a method for diagnosing a local cooling failure of a battery system, wherein the battery system includes battery cells connected in series and a cooling device, the method is:

[0062] The battery system is divided into several monitoring areas, and the initial value of the cooling coefficient C of each area is set to 0;

[0063] Real-time collection of the temperature of each area, the voltage of each battery unit, and the system charge and discharge status, where the charge and discharge status includes charging, discharging, and shelving;

[0064] The collected data is divided into time periods, and the division trigger conditions are any of the following conditions:

[0065] 1) The number of acquisitions reaches the preset value;

[0066] 2) Changes in charge and discharge status;

[0067] For each time period of collected data, the average temperature T and the average battery cell voltage U of each area in the time period are calculated, as well as the mean μ of all T values. T and standard deviation σ T , the mean value of all U values ​​μ U and standard deviation σ U :

[0068] If the time period is on hold:

[0069] 1) And there exists T>μ T +pσ T If the area is , the C value of the corresponding area is reduced by 1;

[0070] 2) and there exists T < μ T -pσ T If the area is , the C value of the corresponding area is increased by 1;

[0071] If the time period is charging state:

[0072] 1) And there exists T>μ T +pσ T And U<μ U +qσ U If the area is , the C value of the corresponding area is reduced by 1;

[0073] 2) There exists T < μ - pσ and U > μ U -qσ U If the area is , the C value of the corresponding area is increased by 1;

[0074] If the time period is the discharge state:

[0075] 1) And there exists T>μ T +pσ T And U>μ U -qσ U If the area is , the C value of the corresponding area is reduced by 1;

[0076] 2) There exists T < μ-pσ and U < μ U +qσ U If the area is , the C value of the corresponding area is increased by 1;

[0077] When the C value of a certain area is greater than C I Or if the net increase in the C value within the preset time is greater than ΔC, the area is judged to be overcooled;

[0078] When the C value of a certain area is less than C II Or if the net decrease in the C value within the preset time is greater than ΔC, the area is judged to be insufficiently cooled;

[0079] The above p and q are coefficients greater than 0, C I >0>C II .

[0080] Specifically, the battery unit is composed of one battery cell or a plurality of battery cells connected in parallel.

[0081] Specifically, the monitoring areas of the battery system can be divided according to the structural characteristics of the battery system and its cooling device.

[0082] In one embodiment, the cooling device is a liquid cooling plate with liquid inlet at one end and liquid outlet at the other end. The battery system is divided into 20 monitoring areas along the upstream and downstream of the coolant flow channel and taking into account the branching relationship of each flow channel.

[0083] In another embodiment, the battery system is composed of 30 modules, and the battery system is divided into 30 monitoring areas according to the areas where the modules are located, and each area corresponds to one module.

[0084] Specifically, the number of battery cells in each area may be equal or unequal.

[0085] Specifically, in the above-mentioned method for diagnosing a local cooling fault of a battery system, the average voltage value U of the battery cells in a certain area within a certain time period is the average value of all voltage collection values ​​of all battery cells contained in the area within the time period.

[0086] In one embodiment, a certain area has a total of 10 battery cells. The average voltage value U of the battery cells in the area during a certain time period is the average value of all voltage collection values ​​of all 10 battery cells in the area during the time period.

[0087] Preferably, in the above-mentioned method for diagnosing local cooling failure of the battery system, the frequency of real-time data acquisition is between 0.05Hz and 1Hz; the preset value of the number of acquisitions for dividing the acquired data into time periods is between 10 and 1000; and the preset time duration for determining whether there is excessive or insufficient regional cooling is between 10 minutes and 100 hours.

[0088] Preferably, in the above-mentioned method for diagnosing local cooling failure of the battery system, the coefficients p and q are both between 1 and 3, and C I Between 20 and 500, C II Between -500 and -20, ΔC between 10 and 1000.

[0089] like Figure 2 As shown, a diagnostic device for local cooling failure of a battery system is used to implement the diagnostic method for local cooling failure of a battery system. The device includes an acquisition module, a storage module, an analysis module, and an output module:

[0090] The acquisition module includes a temperature sensor, a voltage sensor, and a current sensor, which are used to collect the temperature of each area, the voltage of each battery cell, and the charging and discharging status of the system respectively;

[0091] The storage module is used to receive and store the data collected by the acquisition module;

[0092] The analysis module is used to read data from the storage module and perform fault diagnosis analysis;

[0093] The output module is used to obtain and output the diagnostic results from the analysis module.

[0094] Specifically, at least one temperature sensor is set in each area. If more than one temperature sensor is set in a single area, the average temperature measurement of all temperature sensors is output as the collected value.

[0095] Preferably, the temperature sensor is arranged on the surface of the battery cell.

[0096] Preferably, the output module can communicate with the battery management system (BMS) of the battery system to upload the diagnosis results.

[0097] The present invention also provides a computer-readable storage medium storing a plurality of computer instructions, wherein the computer instructions are suitable for being loaded by a processor to execute the above-mentioned method for diagnosing a local cooling fault of a battery system.

[0098] The present invention also provides a battery system integrated with the above-mentioned battery system local cooling failure diagnosis device.

[0099] Furthermore, the battery system can be installed in an electric vehicle.

[0100] Furthermore, the above-mentioned battery system can also be mounted on a battery energy storage device.

[0101] Example

[0102] Please refer to Figures 1 to 2 Let's understand a more specific embodiment. The battery system in this embodiment is composed of 2 parallel and 100 series lithium iron phosphate lithium-ion battery cells, so each battery cell is composed of 2 battery cells connected in parallel. The battery system uses a liquid cooling plate to exchange heat with each battery cell. The battery system is divided into 20 monitoring areas, 1# to 20#, based on the upstream and downstream and branch characteristics of the liquid cooling flow channel. Each monitoring area is equipped with a temperature sensor, for a total of 20 temperature sensors; each battery cell is equipped with a voltage sensor, for a total of 100 voltage sensors; a Hall sensor is installed at the total positive terminal of the battery system output to measure the current of the battery system and thus determine its working status.

[0103] In this embodiment, the frequency of real-time data collection is 1 Hz, the preset value of the number of collection times for dividing the collected data into time periods is 100, the preset time for determining whether there is excessive or insufficient cooling of the area is 30 minutes, the coefficient p is 2.5, q is 2, and C I =100, C II =-100, ΔC=30.

[0104] On a certain day, the battery system starts working, and the startup time is recorded as t=0. At this time, the cooling coefficient C value of each area is set to 0.

[0105] Taking the first 1000s as an example, from t = 0 to t = 560s the system is in a discharging state, from t = 561s to t = 700s the system is in a shelving state, and from t = 701s to t = 1000s the system is in a charging state. The time periods for data collection are shown in Table 1. In Table 1, the time periods are numbered in chronological order for easy understanding.

[0106] Table 1 Time period division of the first 1000s of data collection

[0107] serial number Start and end time System Status 1 0 to 100s discharge 2 101 to 200s discharge 3 201 to 300s discharge 4 301 to 400s discharge 5 401 to 500s discharge 6 501 to 560s discharge 7 561 to 660s Shelved 8 661 to 700s Shelved 9 701 to 800s Charge 10 801 to 900s Charge 11 901 to 1000s Charge

[0108] The following focuses on the 1# monitoring area as an example.

[0109] In the time period numbered 120, the C value of monitoring area 1# is 4.

[0110] During the time period numbered 121, monitoring area 1# was in a standby state, with an average temperature of T = 42.3°C and an average battery cell voltage of U = 3.31V; the mean T value of all 20 monitoring areas μ T =41.8℃, standard deviation σ T=0.26℃, the average value of all U values ​​μ U =3.30V, standard deviation σ U =0.006V. Because μ T +pσ T =41.8+2.5*0.26=42.45℃,μ T -pσ T =41.8-2.5*0.26=41.15℃, so for monitoring area 1#, T>μ in the time period numbered 121 T +pσ T and T<μ T -pσ T If all the conditions are not met, the value of C remains unchanged at 4.

[0111] In the time period numbered 122, the 1# monitoring area is in the discharge state, with an average temperature of T = 44.5°C and an average battery cell voltage of U = 3.20V; the mean T value of all 20 monitoring areas μ T =43.7℃, standard deviation σ T =0.29℃, the average value of all U values ​​μ U =3.19V, standard deviation σ U =0.007V. Because μ T +pσ T =43.7+2.5*0.29=44.43℃,μ U -qσ U =3.19-2*0.007=3.176V, so for monitoring area 1#, T>μ in the time period numbered 122 T +pσ T And U>μ U -qσ U If it holds, reduce C by 1 and change its value to 3.

[0112] In the time period numbered 123, the 1# monitoring area is in the charging state, with an average temperature of T = 45.9°C and an average battery cell voltage of U = 3.34V; the mean T value of all 20 monitoring areas μ T =44.9℃, standard deviation σ T =0.32℃, the average value of all U values ​​μ U =3.33V, standard deviation σ U =0.006V. Because μ T +pσ T =44.9+2.5*0.32=45.7℃,μ U +qσ U =3.33+2*0.006=3.342V, so for monitoring area 1#, T>μ in the time period numbered 123T +pσ T And U<μ U +qσ U If it holds, reduce C by 1 and change its value to 2.

[0113] After a certain period of time, the C value of monitoring area 1# is -101, which is less than C II Therefore, the output module of the diagnostic device outputs the local cooling fault information of insufficient cooling in the 1# monitoring area to the BMS of the battery system.

[0114] The technical solution in this embodiment is based on the principles of heat transfer, electrochemistry, and statistics. It fully considers the correlation between the temperature of the battery system area and the local cooling intensity and heat generation power. It determines the cooling intensity under the premise of eliminating the heat generation deviation caused by abnormal battery internal resistance. The diagnostic process relies on existing temperature / voltage / current sensors to achieve hardware compatibility. Only software algorithm supplementation is required to adapt to typical scenarios such as electric vehicles and energy storage. The final diagnostic decision uses a data accumulation mechanism. The fault diagnosis is triggered only after the temperature anomaly is statistically verified, which can effectively reduce the false alarm rate. Therefore, this technical solution is scientific and reasonable, simple and easy to implement, and highly reliable.

Claims

1. A method for diagnosing a local cooling failure in a battery system, wherein the battery system comprises battery cells connected in series and a cooling device, wherein: The battery system is divided into several monitoring areas, and the initial value of the cooling coefficient C of each area is set to 0; Real-time collection of the temperature of each area, the voltage of each battery unit, and the system charge and discharge status, where the charge and discharge status includes charging, discharging, and shelving; The collected data is divided into time periods, and the division trigger conditions are any of the following conditions: 1) The number of acquisitions reaches the preset value; 2) Changes in charge and discharge status; For each time period of collected data, the average temperature T and the average battery cell voltage U of each area in the time period are calculated, as well as the mean μ of all T values. T and standard deviation σ T , the mean value of all U values ​​μ U and standard deviation σ U : If the time period is on hold: 1) And there exists T>μ T +pσ T If the area is , the C value of the corresponding area is reduced by 1; 2) and there exists T < μ T -pσ T If the area is , the C value of the corresponding area is increased by 1; If the time period is charging state: 1) And there exists T>μ T +pσ T And U<μ U +qσ U If the area is , the C value of the corresponding area is reduced by 1; 2) There exists T < μ - pσ and U > μ U -qσ U If the area is , the C value of the corresponding area is increased by 1; If the time period is the discharge state: 1) And there exists T>μ T +pσ T And U>μ U -qσ U If the area is , the C value of the corresponding area is reduced by 1; 2) There exists T < μ-pσ and U < μ U +qσ U If the area is , the C value of the corresponding area is increased by 1; When the C value of a certain area is greater than C I Or if the net increase in the C value within the preset time is greater than ΔC, the area is judged to be overcooled; When the C value of a certain area is less than C II Or if the net decrease in the C value within the preset time is greater than ΔC, the area is judged to be insufficiently cooled; Above p and q are coefficients greater than 0, C I >0>C II .

2. The method for diagnosing a local cooling failure of a battery system according to claim 1, characterized in that: The average voltage value U of the battery cells in a certain area within a certain time period is the average value of all voltage collection values ​​of all battery cells contained in the area within the time period.

3. The method for diagnosing a local cooling failure of a battery system according to claim 1, wherein: The battery unit is composed of one battery cell or a plurality of battery cells connected in parallel.

4. The method for diagnosing a local cooling failure of a battery system according to claim 1, wherein: The frequency of real-time data collection is between 0.05Hz and 1Hz; the preset value of the number of collection times used to divide the collected data into time periods is between 10 and 1000; and the preset time duration used to determine whether there is excessive or insufficient cooling of an area is between 10 minutes and 100 hours.

5. The method for diagnosing a local cooling failure of a battery system according to claim 1, wherein: The coefficients p and q are both between 1 and 3, C I Between 20 and 500, C II Between -500 and -20, ΔC between 10 and 1000.

6. A device for diagnosing a local cooling failure of a battery system, used to implement the method for diagnosing a local cooling failure of a battery system according to any one of claims 1 to 5, characterized in that: Including acquisition module, storage module, analysis module and output module: The acquisition module includes temperature sensors, voltage sensors, and current sensors, which are used to collect the temperature of each area, the voltage of each battery cell, and the charging and discharging status of the system respectively; The storage module is used to receive and store the data collected by the acquisition module; The analysis module is used to read data from the storage module and perform fault diagnosis analysis; The output module is used to obtain and output the diagnostic results from the analysis module.

7. A computer-readable storage medium storing a plurality of computer instructions, characterized in that: The computer instructions are suitable for being loaded by a processor to execute the method for diagnosing a local cooling fault of a battery system according to any one of claims 1 to 5.

8. A battery system, characterized in that: The device is integrated with the diagnostic device for local cooling failure of the battery system as claimed in claim 6.

9. The battery system according to claim 8, wherein: Mounted on electric vehicles.

10. The battery system according to claim 8, wherein: Mounted on battery energy storage equipment.

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