Battery thermal runaway risk diagnosis method and apparatus

Abstract

A battery thermal runaway risk diagnosis method, comprising: acquiring a first voltage of each battery cell of a battery at each first acquisition moment in a target phase (step S1); averaging the first voltages of all the battery cells at each first acquisition moment to obtain a voltage average value, determining a first difference between the first voltage of each battery cell at each first acquisition moment and the voltage average value, and averaging all the first differences corresponding to each battery cell at all the first acquisition moments to obtain a difference average value (step S2); and if the battery cells have a first average value greater than a third average value and have a second average value less than the third average value, determining that a charge-discharge voltage hysteresis phenomenon occurs in the battery (step S3).

Description

Battery thermal runaway risk diagnosis method and device CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to Chinese patent application No. 202311827281.3 filed on December 28, 2023, the entire contents of which are incorporated herein by reference. Technical Field

[0002] The present disclosure relates to the field of battery technology, and in particular to a method and device for diagnosing battery thermal runaway risk. Background Art

[0003] As the number of new energy vehicles in the market continues to increase, issues such as safety, endurance, and energy consumption have also attracted much attention. Among them, battery thermal runaway is the biggest issue affecting the safety of new energy vehicles. The causes of battery thermal runaway include the impact of byproducts produced during battery use (during the charge and discharge cycle) on the battery. For example, when the byproduct is lithium deposition, it will affect the electrochemical performance of the battery and cause abnormalities such as increased internal resistance of the battery cell. Battery cells with increased internal resistance often have higher voltages during charging and lower voltages during discharge, which is the "high charge, low discharge" phenomenon.

[0004] Related technologies, based on battery thermal runaway cases, have found that a significant proportion of batteries experience overcharging and undercharging before thermal runaway occurs. Therefore, timely detection of this overcharging and undercharging phenomenon is crucial for identifying thermal runaway risks. Therefore, monitoring this overcharging and undercharging phenomenon is crucial. Summary of the Invention

[0005] By utilizing one or more embodiments of the present disclosure, a battery thermal runaway risk diagnosis method and device are provided to solve the technical problem of how to detect the "high charge and low discharge" phenomenon of a battery.

[0006] According to a first aspect of the present disclosure, a battery thermal runaway risk diagnosis method is provided, which may include: obtaining a first voltage of each battery cell of the battery at each first collection moment in a target journey; wherein the target journey includes a charging journey, a discharging journey, and a rest journey; averaging the first voltages of all battery cells at each first collection moment to obtain a voltage average value; separately determining a first difference between the first voltage of each battery cell at each first collection moment and the voltage average value; averaging all first differences corresponding to each battery cell at all first collection moments to obtain a difference average value; wherein the difference average value corresponding to the charging journey is a first average value, the difference average value corresponding to the discharging journey is a second average value, and the difference average value corresponding to the rest journey is a third average value; if the first average value of the battery cell is greater than the third average value, and the second average value is less than the third average value, it is determined that the battery has been overcharged and undercharged.

[0007] According to a second aspect of the present disclosure, a battery thermal runaway risk diagnosis device is provided, which may include: an acquisition module, configured to acquire a first voltage of each battery cell of a battery at each first acquisition moment in a target journey; the target journey includes a charging journey, a discharging journey, and a rest journey; a calculation module, configured to average the first voltages of all battery cells at each first acquisition moment to obtain a voltage average; and average all first differences corresponding to each battery cell at all first acquisition moments to obtain a difference average; wherein the difference average corresponding to the charging journey is a first average, the difference average corresponding to the discharging journey is a second average, and the difference average corresponding to the rest journey is a third average; and a judgment module, configured to determine that a high-charge and low-discharge phenomenon has occurred in the battery if the first average of the battery cells is greater than the third average, and the second average is less than the third average.

[0008] According to a third aspect of the present disclosure, an electronic device is provided, which may include a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the above-mentioned battery thermal runaway risk diagnosis method can be implemented.

[0009] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the computer program can implement the above-mentioned battery thermal runaway risk diagnosis method. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0011] FIG1 shows a flow chart of a method for diagnosing battery thermal runaway risk according to some embodiments of the present disclosure.

[0012] FIG2 shows a schematic structural diagram of a battery thermal runaway risk diagnosis device according to some embodiments of the present disclosure. DETAILED DESCRIPTION

[0013] According to some embodiments of the present disclosure, the battery thermal runaway risk diagnosis method and device solve the technical problem of how to detect the "high charge and low discharge" phenomenon of the battery.

[0014] In order to better understand the technical solution of the present disclosure, the technical solution of the present disclosure will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0015] During the use of the battery, the inventor discovered that if a single cell of the battery experiences the "high charging and low discharging" phenomenon, the voltage of the single cell will be higher during the charging process, and lower during the discharging process. In addition, the internal resistance of the single cell will continue to increase, gradually becoming the cell with the highest voltage during charging and the cell with the lowest voltage during discharging. The above-mentioned cell will seriously affect the use effect and life of the battery.

[0016] Based on the above problems, some embodiments of the battery thermal runaway risk diagnosis method disclosed herein obtain the first voltage of each battery cell in the battery target stroke at each first collection moment within a preset collection time period, and analyze and calculate the voltage change of the battery cell in each target stroke based on the obtained first voltage. If the first average value corresponding to a certain battery cell is greater than the third average value, the voltage of the battery cell in the charging stroke is higher than the voltage in the static stroke; if the second average value corresponding to the battery cell is less than the third average value, the voltage of the battery cell in the discharge stroke is lower than the voltage in the static stroke; that is, the voltage of the battery cell during the battery charging process is too high and the voltage during the battery discharging process is too low, that is, the battery cell has a high charge and low discharge phenomenon, and the battery cell can be used as a risk cell of the battery, thereby realizing the detection of the high charge and low discharge phenomenon of the battery.

[0017] Below, the technical solution of the present disclosure and how the technical solution of the present disclosure solves the above-mentioned technical problems are described in detail with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present disclosure will be described below with reference to the accompanying drawings.

[0018] As shown in FIG1 , it is a flow chart of a battery thermal runaway risk diagnosis method according to some embodiments of the present disclosure. The battery thermal runaway risk diagnosis method according to some embodiments of the present disclosure includes:

[0019] Step S1: acquiring a first voltage of each cell of the battery at each first acquisition moment in the target travel.

[0020] In some embodiments, the first collection time is determined within a preset collection time period based on the first collection interval, and the target range of the battery may include a charging range, a discharging range, and a rest range.

[0021] In some embodiments, the preset collection time period may be a natural day, and the first collection interval may be determined based on the first collection frequency. For example, the first collection interval may be 30 minutes or 20 seconds, which is not specifically limited herein.

[0022] Step S2: averaging the first voltages of all battery cells at each first acquisition moment to obtain a voltage average; determining a first difference between the first voltage of each battery cell at each first acquisition moment and the voltage average; and averaging all first differences corresponding to each battery cell at all first acquisition moments to obtain a difference average.

[0023] In some embodiments, the average value of the differences corresponding to the charging stroke is a first average value, the average value of the differences corresponding to the discharging stroke is a second average value, and the average value of the differences corresponding to the resting stroke is a third average value.

[0024] Step S3: If the first average value of any battery cell is greater than the third average value, and the second average value is less than the third average value, the battery cell is regarded as a risky battery cell, and it is determined that the battery has experienced a high-charge and low-discharge phenomenon.

[0025] In some embodiments, the resting stroke satisfies the condition that the battery is in a non-charging state, the absolute value of the total battery current is ≤0.05C, and the duration is more than 10 minutes. The first acquisition moment is determined based on the acquisition frequency of the cell voltage, i.e., the first acquisition frequency, and the first voltage is the cell voltage. Taking the charging stroke as an example, assuming that the battery has 3 cells (No. 1 to No. 3), the cell voltage is collected once every 1 second, and the cell voltage is collected 3 times in total. Then, step S1 will obtain the 3 cell voltages collected at the 1st second, the 3 cell voltages collected at the 2nd second, and the 3 cell voltages collected at the 3rd second in the charging stroke. Step S2 calculates the average value of the voltages of the three cells at the first second, i.e., the first voltage average value, the first difference between the voltage of each cell at the first second and the first voltage average value (i.e., the three first differences corresponding to the first second), the second voltage average value of the voltages of the three cells at the second second, the first difference between the voltage of each cell at the second second and the second voltage average value (i.e., the three first differences corresponding to the second second), the average value of the voltages of the three cells at the third second, i.e., the third voltage average value, the first difference between the voltage of each cell at the third second and the third voltage average value (i.e., the three first differences corresponding to the third second), and obtains a total of three first differences corresponding to cell No. 1, three first differences corresponding to cell No. 2, and three first differences corresponding to cell No. 3. Then, the average value of the three first differences corresponding to cell No. 1, the average value of the three first differences corresponding to cell No. 2, and the average value of the three first differences corresponding to cell No. 3 are calculated, and a total of three first average values ​​corresponding to the three cells are obtained.

[0026] In step S3, if the first average value corresponding to a certain battery cell is greater than the third average value, it can be considered that the voltage of the battery cell in the charging stroke is higher than the voltage in the rest stroke; if the second average value corresponding to the battery cell is less than the third average value, it can be considered that the voltage of the battery cell in the discharge stroke is lower than the voltage in the rest stroke; that is, the voltage of the battery cell during the battery charging process is too high and the voltage during the battery discharging process is too low, and the battery cell has experienced the high-charge and low-discharge phenomenon, that is, the battery has experienced the high-charge and low-discharge phenomenon.

[0027] In some embodiments, a battery cell whose first average value is greater than a third average value and whose second average value is less than the third average value may be regarded as a risky battery cell in the battery.

[0028] When the overcharge and underdischarge phenomenon is not serious, the battery's thermal runaway risk is low, and there is no need to issue a battery overcharge and underdischarge abnormality warning. However, when the overcharge and underdischarge phenomenon is serious, the battery's thermal runaway risk is high, and a battery overcharge and underdischarge abnormality warning is required. Therefore, after step S3, the battery thermal runaway risk diagnosis method can also include: calculating the difference between the first average value and the second average value corresponding to each risk cell to obtain the risk cell; using each risk voltage difference as a severity parameter corresponding to the risk cell; the severity parameter is used to characterize the probability of the risk cell experiencing the overcharge and underdischarge phenomenon; and if the severity parameter is greater than a preset threshold, issuing a battery overcharge and underdischarge abnormality warning.

[0029] In some embodiments, after issuing an abnormal warning of high charge and low discharge for the battery, the above method further includes: screening out the maximum value from the severity parameters of each risk battery cell as the battery severity parameter of the battery corresponding to the collection time period.

[0030] In some embodiments, a battery system including multiple batteries may be tested based on the above-mentioned method for detecting overcharge and undercharge of battery cells. The testing steps include:

[0031] S101 : Determine a first battery severity parameter corresponding to each battery in a battery system in each collection sub-time period within a preset total collection time period.

[0032] Specifically, each battery in the battery system can be tested based on the above-mentioned high-charge and low-discharge detection operation for a single battery. For example, the preset total collection time period can be 100 days, and each collection sub-time period can be one of the 100 days, that is, the first battery severity parameter of each battery on each day is determined.

[0033] S102, arranging the first battery severity parameter of each battery in all acquisition sub-time periods in ascending order to obtain a first sequence; obtaining the first battery severity parameter of the first target position in the first sequence as the second battery severity parameter of the battery; obtaining the first battery severity parameter of the second target position in the first sequence as the third battery severity parameter of the battery.

[0034] For example, the first target ranking may be 50th, and the second target ranking may be 25th, that is, for each battery, its corresponding 100 first battery severity parameters are arranged in ascending order, and the first battery severity parameter ranked at 50th is taken as the second battery severity parameter of the battery, and then the first battery severity parameter ranked at 25th is taken as the third battery severity parameter of the battery.

[0035] S103: Determine a parameter threshold according to each second battery severity parameter corresponding to all batteries in the battery system.

[0036] S1031. Arrange all the second battery severity parameters in ascending order to obtain a second sequence; obtain the second battery severity parameter of the third target position in the second sequence as the fourth battery severity parameter of the battery system; obtain the second battery severity parameter of the fourth target position in the second sequence as the fifth battery severity parameter of the battery system.

[0037] For example, the third target ranking can be 75th, and the fourth target ranking can be 25th, that is, the second battery severity parameters of all batteries are arranged in ascending order, and the fourth battery severity parameter V4 ranked at 75th is taken, and the fifth battery severity parameter V5 ranked at 25th is taken.

[0038] S1032: Determine the parameter threshold according to the difference between the fourth battery severity parameter and the fifth battery severity parameter.

[0039] For example, the parameter threshold V0 can be calculated based on the following formula:

[0040] V0=V4+1.5(V4-V5).

[0041] S104: When the third battery severity parameter of any of the batteries is greater than the parameter threshold, an abnormal warning of high charge and low discharge is issued for the battery system.

[0042] In the embodiments disclosed herein, the inventors discovered through battery thermal runaway cases that a considerable proportion of single cells not only had a "high charge and low discharge" phenomenon before thermal runaway, but also a "voltage rebound" phenomenon. In the embodiments disclosed herein, the terminal voltage of the battery is proportional to the concentration of lithium ions in the outermost layer of the battery's solid phase. When the battery is discharged, the solid-phase lithium ions in the positive electrode of the battery are consumed, and the battery liquid-phase lithium ions are needed to replenish the solid-phase lithium ions in the positive electrode of the battery. If the lithium ion concentration in the battery liquid phase is small at this time, the outermost layer of lithium ions in the solid phase of the positive electrode of the battery cannot be replenished in time and the concentration decreases, which will cause the terminal voltage of the battery to decrease, that is, the battery has a voltage rebound phenomenon at this time. The causes of voltage rebound can be divided into the following situations:

[0043] (1) When the battery enters the resting state from the discharge state, the liquid phase lithium ions of the battery are precipitated, resulting in a decrease in the concentration of liquid phase lithium ions. When the battery is discharged at a large current, the solid phase lithium ions of the positive electrode of the battery are replenished slowly, and the battery terminal voltage is pulled down. When the battery stops discharging and enters the resting state, the lithium ion concentration of the outermost layer of the battery solid phase is gradually replenished, and the terminal voltage of the battery gradually rebounds and increases, that is, the voltage rebound phenomenon occurs.

[0044] (2) Since the battery continuously produces byproducts such as lithium deposition during the charge and discharge cycle, the byproducts will consume the lithium ions in the battery liquid phase, resulting in a decrease in the lithium ion concentration in the battery liquid phase. When the battery is discharged at a large current, the solid phase lithium ions in the positive electrode of the battery are slowly replenished, and the battery terminal voltage is pulled down; when the battery stops discharging and enters a static state, the lithium ion concentration in the outermost layer of the battery solid phase is gradually replenished, and the battery terminal voltage gradually rebounds and increases, that is, the voltage rebound phenomenon occurs.

[0045] (3) Byproducts produced during battery recycling will accumulate and clog the pores on the battery separator, increasing the resistance to movement of lithium ions between the positive and negative electrodes. When the battery is discharged at a high current, the solid-phase lithium ions in the positive electrode of the battery are replenished slowly, and the battery terminal voltage is lowered. When the battery stops discharging and enters a static state, the lithium ion concentration in the outermost layer of the battery solid phase is gradually replenished, and the battery terminal voltage gradually rebounds and increases, i.e., voltage rebound occurs.

[0046] Therefore, if the "voltage rebound" phenomenon of the battery can be discovered in time, it will be more conducive to discovering the thermal runaway risk of the battery in advance, that is, the "voltage rebound" phenomenon of the battery needs to be monitored.

[0047] In the embodiment of the present disclosure, a voltage rebound test may be performed on the battery after the battery enters the resting stage from the discharge stage. The test steps include:

[0048] S201: Determine a target time period in the stationary stroke.

[0049] S2011, counting the discharge rate and discharge capacity of the discharge stroke within 3 minutes before the battery switches from the discharge stroke to the rest stroke.

[0050] S2012: When the discharge rate is greater than a first threshold value and the discharge capacity is greater than a second threshold value, the 20th minute from the start of the electrostatic trip is used as the start time, and the end time of the electrostatic trip is used as the end time, and the target time period is determined based on the start time and the end time.

[0051] In some embodiments, the discharge rate and discharge capacity of the discharge stroke within 3 minutes before the battery switches from the discharge stroke to the rest stroke, that is, within the last 3 minutes of the discharge stroke, can be counted; when the discharge rate is greater than a first threshold and the discharge capacity is greater than a second threshold, the 20th minute from the start of the electrostatic stroke is used as the start time, and the end time of the electrostatic stroke is used as the end time, and the target time period is determined based on the start time and the end time.

[0052] For example, the change process of the battery from the discharge stroke to the static stroke can be obtained, and the average discharge rate and discharge capacity of the last 3 minutes of the discharge stroke can be counted. When the discharge rate is greater than or equal to 0.2C (that is, the battery capacity is fully discharged in 5 hours) and the discharge capacity is greater than or equal to 3 times the feedback capacity (that is, the charging capacity), then the change process meets the preset effective sampling scenario, and the sampling time of the battery voltage is determined according to the static stroke, that is, the target time period.

[0053] S202 : At each second collection moment in the target time period, collect a second voltage of each cell of the battery.

[0054] In some implementations, the second collection time is a collection time determined within the target time period based on a second collection interval.

[0055] S203: Obtain the rest starting voltage of each battery cell in the rest stroke.

[0056] In some embodiments, the second frame of data entering the rest stroke is taken as the starting data, and the voltage values ​​of all the cells at this time are counted, namely, the rest start voltage.

[0057] S204 , at each of the second collection moments, respectively calculating the difference between the second voltage of each battery cell and the corresponding static start voltage to obtain a rebound voltage.

[0058] S205 , respectively calculating an average value of the rebound voltage of each battery cell at all second collection moments as an average rebound voltage; and determining a rebound voltage threshold corresponding to each battery cell based on the average rebound voltage of each battery cell.

[0059] In some implementations, 1.5 times the average rebound voltage may be used as the corresponding rebound voltage threshold.

[0060] S206 , when any rebound voltage corresponding to the battery cell is greater than the corresponding rebound voltage threshold, the battery cell is regarded as a rebound battery cell, and a voltage rebound warning for the battery is issued.

[0061] S207 , for each battery cell, respectively calculating the difference between each corresponding rebound voltage and the corresponding average rebound voltage to obtain a voltage rebound parameter, and taking the maximum value of all the voltage rebound parameters of the battery cell as the battery cell rebound parameter of the battery cell.

[0062] S208: The maximum value among all the cell rebound parameters is used as the battery rebound parameter of the battery. In some embodiments, after collecting cell voltages at a fixed frequency, i.e., the second collection frequency, each collection will obtain a frame of voltage data consisting of all cell voltages. The resting start voltage of the cell can be the second frame of data after entering the resting range (taking into account that the battery may not have actually entered the resting range when the first frame of data is collected). The preset duration can be 20 minutes, and the time difference between two adjacent second collection moments can be 30 minutes. That is, after the battery enters the resting range for 20 minutes, a voltage data frame is collected every 30 minutes until 3 frames of data before the end of the resting range. The last data with an interval of less than 30 minutes is also calculated as valid data. Assuming that the battery has 3 cells and the second voltage is collected 3 times in total, 3 resting start voltages and 3 cell voltages (second voltages) at each second collection moment can be obtained. The 3 second differences corresponding to each second collection moment, i.e., the rebound voltage, and the average of the 3 second differences corresponding to the 3 second collection moments, i.e., the average rebound voltage, can be calculated. The maximum value among the average values ​​of all the second differences is greater than zero, indicating that the voltage of the battery 20 minutes after entering the resting cycle is higher than the voltage immediately after entering the resting cycle, i.e., voltage rebound occurs.

[0063] In some embodiments, a battery system including multiple batteries may be tested based on the voltage rebound detection method described above, and the testing steps include:

[0064] S301 : Determine a first battery rebound parameter corresponding to each battery in a battery system in each target sub-time period within a preset target total time period.

[0065] The target total time period may be 100 days, and the target sub-time period may be 1 day. The rebound detection operations of S201 to S208 may be performed on each battery in the battery system every day within the 100 days to determine the first battery rebound parameter of each battery every day.

[0066] S302, arranging the first battery rebound parameter of each battery in all target sub-time periods in ascending order to obtain a third sequence; obtaining the first battery rebound parameter of the first target position in the third sequence as the second battery rebound parameter of the battery; obtaining the first battery rebound parameter of the second target position in the third sequence as the third battery rebound parameter of the battery.

[0067] In some embodiments, the first target ranking may be 50th, and the second target ranking may be 25th.

[0068] For example, the first battery rebound parameter corresponding to each battery for 100 days may be arranged in ascending order, the second battery rebound parameter at the 50th position is taken, and the third battery rebound parameter at the 25th position is taken.

[0069] S303 : Determine a rebound parameter threshold value according to each second battery rebound parameter corresponding to all batteries in the battery system.

[0070] S3031, arrange all the second battery rebound parameters in ascending order to obtain a fourth sequence; obtain the second battery rebound parameter of the third target position in the fourth sequence as the fourth battery rebound parameter of the battery system; obtain the second battery rebound parameter of the fourth target position in the fourth sequence as the fifth battery rebound parameter of the battery system.

[0071] In some embodiments, the third target ranking may be 75th, and the fourth target ranking may be 25th. For example, the second battery rebound parameters corresponding to all batteries may be sorted in ascending order, and the fourth battery rebound parameter V4^ ranked 75th is obtained, and the fifth battery rebound parameter V5^ ranked 25th is obtained.

[0072] S3032: Determine the rebound parameter threshold according to the difference between the fourth battery rebound parameter and the fifth battery rebound parameter.

[0073] In some embodiments, the rebound parameter threshold V0^ can be calculated based on the following formula:

[0074] V0^=V4^+1.5(V4^-V5^).

[0075] S304 : When the third battery rebound parameter of any of the batteries is greater than the rebound parameter threshold, issuing a voltage rebound abnormality warning for the battery system.

[0076]

[0077] FIG2 is a schematic diagram of a battery thermal runaway risk diagnosis device according to some embodiments of the present disclosure. The battery thermal runaway risk diagnosis device according to some embodiments of the present disclosure includes:

[0078] an acquisition module, configured to acquire a first voltage of each battery cell of the battery at each first acquisition moment during a target trip, wherein the first acquisition moment is a acquisition moment determined within a preset acquisition time period based on a first acquisition interval, and the target trip includes a charging trip, a discharging trip, and a rest trip;

[0079] a calculation module, configured to average the first voltages of all battery cells at each first collection moment to obtain a voltage average; respectively determine a first difference between the first voltage of each battery cell at each first collection moment and the voltage average; and average all first differences corresponding to each battery cell at all first collection moments to obtain a difference average;

[0080] The average value of the differences corresponding to the charging stroke is the first average value, the average value of the differences corresponding to the discharging stroke is the second average value, and the average value of the differences corresponding to the resting stroke is the third average value;

[0081] The judgment module is configured to treat the battery cell as a risky battery cell and determine that the battery has experienced a high-charge and low-discharge phenomenon if the first average value of the battery cell is greater than the third average value and the second average value is less than the third average value.

[0082] Furthermore, the calculation module can also be used to calculate the difference between the first average value and the second average value corresponding to each risk cell to obtain a risk voltage difference; each risk voltage difference is used as a severity parameter corresponding to the risk cell as the severity parameter of the risk cell; wherein the severity parameter is used to characterize the probability of the risk cell experiencing a high-charge and low-discharge phenomenon;

[0083] The battery thermal runaway risk diagnosis device may further include an early warning module for issuing an abnormal early warning of overcharging or undercharging of the battery if the severity parameter is greater than a preset threshold.

[0084] Furthermore, the computing module is further configured to:

[0085] A maximum value is selected from the severity parameters of each risky battery cell as the battery severity parameter corresponding to the collection time period.

[0086] Furthermore, the computing module is further configured to:

[0087] Determining a first battery severity parameter corresponding to each battery in the battery system in each collection sub-time period within a preset total collection time period;

[0088] Arrange the first battery severity parameter of each battery in all acquisition sub-time periods in ascending order to obtain a first sequence; obtain the first battery severity parameter of the first target position in the first sequence as the second battery severity parameter of the battery; obtain the first battery severity parameter of the second target position in the first sequence as the third battery severity parameter of the battery;

[0089] Determining a parameter threshold according to each second battery severity parameter corresponding to all batteries in the battery system;

[0090] When the third battery severity parameter of any of the batteries is greater than the parameter threshold, an abnormal warning of high charge and low discharge is issued for the battery system.

[0091] Furthermore, the above device also includes a voltage rebound detection module, which is used to:

[0092] determining a target time period in the static trip;

[0093] At each second collection moment in the target time period, collecting a second voltage of each cell of the battery; wherein the second collection moment is a collection moment determined within the target time period based on a second collection interval;

[0094] Obtaining a rest starting voltage of each battery cell in the rest stroke;

[0095] At each of the second collection moments, respectively calculating the difference between the second voltage of each battery cell and the corresponding static start voltage to obtain a rebound voltage;

[0096] respectively calculating an average value of the rebound voltage of each battery cell at all second acquisition moments as an average rebound voltage; and determining a rebound voltage threshold value corresponding to each battery cell based on the average rebound voltage of each battery cell;

[0097] When any rebound voltage corresponding to the battery cell is greater than the corresponding rebound voltage threshold, the battery cell is regarded as a rebound battery cell, and a voltage rebound warning for the battery is issued.

[0098] Furthermore, the voltage rebound detection module is also used to:

[0099] Counting the discharge rate and discharge capacity of the battery in the discharge stroke within 3 minutes before the battery switches from the discharge stroke to the rest stroke;

[0100] When the discharge rate is greater than a first threshold and the discharge capacity is greater than a second threshold, the 20th minute from the start of the electrostatic trip is used as the start time, and the end time of the electrostatic trip is used as the end time, and the target time period is determined based on the start time and the end time.

[0101] Furthermore, the voltage rebound detection module is also used to:

[0102] For each battery cell, respectively calculate the difference between each corresponding rebound voltage and the corresponding average rebound voltage to obtain a voltage rebound parameter, and take the maximum value of all the voltage rebound parameters of the battery cell as the battery cell rebound parameter of the battery cell;

[0103] The maximum value of all the cell rebound parameters is used as the battery rebound parameter of the battery.

[0104] Furthermore, the voltage rebound detection module is also used to:

[0105] Determining a first battery rebound parameter corresponding to each battery of the battery system in each target sub-time period within a preset target total time period;

[0106] Arrange the first battery rebound parameter of each battery in all target sub-time periods in ascending order to obtain a third sequence; obtain the first battery rebound parameter of the first target position in the third sequence as the second battery rebound parameter of the battery; obtain the first battery rebound parameter of the second target position in the third sequence as the third battery rebound parameter of the battery;

[0107] Determining a rebound parameter threshold value according to each second battery rebound parameter corresponding to all batteries in the battery system;

[0108] When the third battery rebound parameter of any of the batteries is greater than the rebound parameter threshold, a voltage rebound abnormality warning for the battery system is issued.

[0109] Based on the same inventive concept as the battery thermal runaway risk diagnosis method described above, an embodiment of the present disclosure also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of any one of the battery thermal runaway risk diagnosis methods described above are implemented.

[0110] Among them, the bus architecture (represented by the bus), the bus can include any number of interconnected buses and bridges, and the bus links together various circuits including one or more processors represented by the processor and memory represented by the memory. The bus can also link together various other circuits such as peripherals, voltage regulators, and power management circuits, which are all well known in the art and therefore will not be described further herein. The bus interface provides an interface between the bus and the receiver and transmitter. The receiver and transmitter can be the same component, namely a transceiver, which provides a unit for communicating with various other devices on a transmission medium. The processor is responsible for managing the bus and general processing, while the memory can be used to store data used by the processor when performing operations.

[0111] Since the electronic device described in the embodiments of the present disclosure is the electronic device used to implement the battery thermal runaway risk diagnosis method in the embodiments of the present disclosure, based on the battery thermal runaway risk diagnosis method described in the embodiments of the present disclosure, those skilled in the art will be able to understand the specific implementation of the electronic device in the embodiments of the present disclosure and its various variations. Therefore, how the electronic device implements the method in the embodiments of the present disclosure will not be described in detail here. As long as those skilled in the art implement the electronic device used in the battery thermal runaway risk diagnosis method in the embodiments of the present disclosure, it falls within the scope of protection to be provided by the present disclosure.

[0112] Based on the same inventive concept as the above-mentioned battery thermal runaway risk diagnosis method, the present disclosure also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements any of the above-mentioned battery thermal runaway risk diagnosis methods.

[0113] Those skilled in the art will appreciate that the embodiments of the present disclosure may be provided as methods, systems, or computer program products. Therefore, the present disclosure may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present disclosure may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0114] The present disclosure is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present disclosure. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0115] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction device that implements the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0116] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0117] Although the preferred embodiments of the present disclosure have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concepts. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present disclosure.

[0118] Obviously, those skilled in the art may make various changes and modifications to the present disclosure without departing from the spirit and scope of the present disclosure. Thus, if these modifications and variations of the present disclosure fall within the scope of the claims of the present disclosure and their equivalents, the present disclosure is intended to include these modifications and variations.

Claims

1. A method for diagnosing the risk of battery thermal runaway, comprising: At each first acquisition moment during the target journey, acquiring the first voltage of each battery cell of the battery; wherein, the target journey includes a charging journey, a discharging journey, and a static state journey; Calculating the average value of the first voltages of all battery cells at each first acquisition moment to obtain a voltage average value; Respectively determining the first difference between the first voltage of each battery cell at each first acquisition moment and the voltage average value; Calculating the average value of all the first differences corresponding to each battery cell at all first acquisition moments to obtain a difference average value, wherein the difference average value corresponding to the charging journey is the first average value, the difference average value corresponding to the discharging journey is the second average value, and the difference average value corresponding to the static state journey is the third average value; and If the first average value of the battery cell is greater than the third average value, and the second average value is less than the third average value, it is determined that the battery has the phenomenon of high charging and low discharging.

2. The battery thermal runaway risk diagnosis method according to claim 1, wherein, After determining that the battery has the phenomenon of high charging and low discharging, it further includes: If the first average value of the battery cell is greater than the third average value, and the second average value is less than the third average value, taking the battery cell as a risk battery cell; Respectively calculating the difference between the first average value and the second average value corresponding to each risk battery cell to obtain a risk voltage difference; Taking each risk voltage difference as the severity parameter corresponding to the risk battery cell; wherein, the severity parameter is used to characterize the probability of the risk battery cell having the phenomenon of high charging and low discharging; If the severity parameter is greater than a preset threshold, an abnormal warning of high charging and low discharging for the battery is issued.

3. The battery thermal runaway risk diagnosis method according to claim 2, wherein, The first acquisition moment is an acquisition moment determined within a preset acquisition time period based on a first acquisition interval; After issuing the abnormal warning of high charging and low discharging for the battery, it further includes: Selecting the maximum value from the severity parameters of each risk battery cell as the battery severity parameter corresponding to the battery within the acquisition time period.

4. The battery thermal runaway risk diagnosis method according to claim 3, wherein, After selecting the maximum value from the severity parameters of each risk battery cell as the battery severity parameter corresponding to the battery within the acquisition time period, it further includes: Within each acquisition sub-time period of the preset total acquisition time period, respectively determining the first battery severity parameter corresponding to each battery in the battery system; Respectively arranging the first battery severity parameters of each battery in all acquisition sub-time periods in ascending order to obtain a first sequence; obtaining the first battery severity parameter at the first target position in the first sequence as the second battery severity parameter of the battery; obtaining the first battery severity parameter at the second target position in the first sequence as the third battery severity parameter of the battery; Determining a parameter threshold according to the second battery severity parameters corresponding to all the batteries in the battery system respectively; When the third battery severity parameter of any one battery is greater than the parameter threshold, an abnormal warning of high charging and low discharging for the battery system is issued.

5. The battery thermal runaway risk diagnosis method according to claim 4, wherein, The determining the parameter threshold according to the second battery severity parameters corresponding to all the batteries in the battery system respectively includes: Arrange all the second battery severity parameters in ascending order to obtain a second sequence; obtain the second battery severity parameter at the third target position in the second sequence as the fourth battery severity parameter of the battery system, and obtain the second battery severity parameter at the fourth target position in the second sequence as the fifth battery severity parameter of the battery system; Determine the parameter threshold according to the difference between the fourth battery severity parameter and the fifth battery severity parameter.

6. The battery thermal runaway risk diagnosis method according to claim 1, wherein, The method further includes: Determine the target time period in the static travel; At each second acquisition moment in the target time period, collect the second voltage of each battery cell of the battery; wherein, the second acquisition moment is an acquisition moment determined based on a second acquisition interval within the target time period; Obtain the static start voltage of each battery cell in the static travel; At each second acquisition moment, calculate the difference between the second voltage of each battery cell and the corresponding static start voltage respectively to obtain a rebound voltage; Respectively calculate the average value of the rebound voltages of each battery cell at all second acquisition moments as the average rebound voltage; and respectively determine the rebound voltage threshold corresponding to each battery cell based on the average rebound voltage of each battery cell; When any one of the rebound voltages corresponding to the battery cell is greater than the corresponding rebound voltage threshold, then regard the battery cell as a rebound battery cell and issue a voltage rebound warning for the battery.

7. The method for diagnosing the risk of battery thermal runaway according to claim 6, wherein, The determining the target time period in the static travel includes: Statistically calculate the discharge rate and discharge capacity of the discharge travel within 3 minutes before the battery switches from the discharge travel to the static travel; When the discharge rate is greater than a first threshold and the discharge capacity is greater than a second threshold, then take the 20th minute from the start of the static travel as the start time and the end time of the static travel as the end time, and determine the target time period based on the start time and the end time.

8. The battery thermal runaway risk diagnosis method according to claim 6, wherein, After the voltage rebound warning for the battery is issued, it includes: For each battery cell, calculate the difference between the corresponding rebound voltage and the corresponding average rebound voltage respectively to obtain a voltage rebound parameter, and take the maximum value among all the voltage rebound parameters of the battery cell as the cell rebound parameter of the battery cell; Take the maximum value among all the cell rebound parameters as the battery rebound parameter of the battery.

9. The battery thermal runaway risk diagnosis method according to claim 8, wherein, The method further includes: Within each target sub-time period within a preset target total time period, respectively determine the first battery rebound parameter corresponding to each battery of the battery system; Respectively arrange the first battery rebound parameters of each battery in all target sub-time periods in ascending order to obtain a third sequence; obtain the first battery rebound parameter at the first target position in the third sequence as the second battery rebound parameter of the battery; obtain the first battery rebound parameter at the second target position in the third sequence as the third battery rebound parameter of the battery; Determine the rebound parameter threshold according to the second battery rebound parameters corresponding to all the batteries of the battery system respectively; When the third battery rebound parameter of any one of the batteries is greater than the rebound parameter threshold, then issue a voltage rebound anomaly warning for the battery system.

10. The battery thermal runaway risk diagnosis method according to claim 9, wherein, Determining a threshold value of the resilience parameter according to the respective second battery resilience parameters corresponding to all the batteries of the battery system includes: Arranging all the second battery resilience parameters in ascending order to obtain a fourth sequence; obtaining the second battery resilience parameter at a third target position in the fourth sequence as the fourth battery resilience parameter of the battery system; obtaining the second battery resilience parameter at a fourth target position in the fourth sequence as the fifth battery resilience parameter of the battery system; Determining the threshold value of the resilience parameter according to the difference between the fourth battery resilience parameter and the fifth battery resilience parameter.

11. A battery thermal runaway risk diagnosis device, wherein, Including: An acquisition module, configured to acquire, at each first acquisition moment in a target stroke, the first voltage of each battery cell of the battery; wherein, the target stroke includes a charging stroke, a discharging stroke, and a resting stroke; A calculation module, configured to calculate the average of the first voltages of all the battery cells at each first acquisition moment to obtain an average voltage value; respectively determine the first difference between the first voltage of each battery cell at each first acquisition moment and the average voltage value; calculate the average of all the first differences corresponding to each battery cell at all the first acquisition moments to obtain an average difference value; Wherein, the average difference value corresponding to the charging stroke is a first average value, the average difference value corresponding to the discharging stroke is a second average value, and the average difference value corresponding to the resting stroke is a third average value; and A judgment module, configured to determine that the battery has the phenomenon of overcharging and under-discharging if the first average value of the battery cell is greater than the third average value and the second average value is less than the third average value.

12. The battery thermal runaway risk diagnosis device according to claim 11, wherein, After the calculation module determines that the battery has the phenomenon of overcharging and under-discharging, it is further configured to: If the first average value of the battery cell is greater than the third average value and the second average value is less than the third average value, then regard the battery cell as a risk battery cell; Respectively calculate the difference between the first average value and the second average value corresponding to each risk battery cell to obtain a risk voltage difference; Use each risk voltage difference as the severity parameter corresponding to the risk battery cell as the severity parameter of the risk battery cell; wherein, the severity parameter is used to characterize the probability of the risk battery cell having the phenomenon of overcharging and under-discharging; The battery thermal runaway risk diagnosis device further includes an early warning module, configured to issue an early warning of overcharging and under-discharging abnormality for the battery if the severity parameter is greater than a preset threshold value.

13. The battery thermal runaway risk diagnosis device according to claim 12, wherein the calculation module is further configured to: Screen out the maximum value from the severity parameters of each risk battery cell as the battery severity parameter corresponding to the battery during the acquisition time period.

14. The battery thermal runaway risk diagnosis device according to claim 13, wherein the calculation module is further configured to: During each acquisition sub-time period of a preset total acquisition time period, respectively determine the first battery severity parameter corresponding to each battery in the battery system; Arrange the first battery severity parameters of each battery in all acquisition sub - time periods in ascending order to obtain a first sequence; obtain the first battery severity parameter at the first target position in the first sequence as the second battery severity parameter of the battery; obtain the first battery severity parameter at the second target position in the first sequence as the third battery severity parameter of the battery; Determine a parameter threshold according to the respective second battery severity parameters corresponding to all batteries of the battery system; When the third battery severity parameter of any one of the batteries is greater than the parameter threshold, an abnormal warning of over - charging and under - discharging for the battery system is issued.

15. The battery thermal runaway risk diagnosis device according to claim 11, wherein, The device further includes a voltage rebound detection module for: Determine the target time period in the rest stroke; At each second acquisition moment in the target time period, collect the second voltage of each battery cell of the battery; wherein, the second acquisition moment is an acquisition moment determined based on a second acquisition interval within the target time period; Obtain the rest start voltage of each battery cell in the rest stroke; At each second acquisition moment, calculate the difference between the second voltage of each battery cell and the corresponding rest start voltage to obtain a rebound voltage; Respectively calculate the average value of the rebound voltages of each battery cell at all second acquisition moments as the average rebound voltage; and respectively determine the rebound voltage threshold corresponding to each battery cell based on the average rebound voltage of each battery cell; When any one of the rebound voltages corresponding to the battery cell is greater than the corresponding rebound voltage threshold, the battery cell is regarded as a rebound cell, and a voltage rebound warning for the battery is issued.

16. The battery thermal runaway risk diagnosis device according to claim 15, wherein, The voltage rebound detection module is further used for: Statistically calculate the discharge rate and discharge capacity of the discharge stroke within 3 minutes before the battery converts from the discharge stroke to the rest stroke; When the discharge rate is greater than a first threshold and the discharge capacity is greater than a second threshold, take the 20th minute at the start of the rest stroke as the start time and the end time of the rest stroke as the end time, and determine the target time period based on the start time and the end time.

17. The battery thermal runaway risk diagnosis device according to claim 15, wherein, The voltage rebound detection module is further used for: For each battery cell, calculate the difference between the corresponding rebound voltage and the corresponding average rebound voltage to obtain a voltage rebound parameter, and take the maximum value among all the voltage rebound parameters of the battery cell as the cell rebound parameter of the battery cell; Take the maximum value among all the cell rebound parameters as the battery rebound parameter of the battery.

18. The battery thermal runaway risk diagnosis device according to claim 17, wherein, The voltage rebound detection module is further used for: Within each target sub - time period of a preset target total time period, respectively determine the first battery rebound parameter corresponding to each battery of the battery system; Arrange the first battery rebound parameters of each battery in all target sub - time periods in ascending order to obtain a third sequence; obtain the first battery rebound parameter at the first target position in the third sequence as the second battery rebound parameter of the battery; obtain the first battery rebound parameter at the second target position in the third sequence as the third battery rebound parameter of the battery; Determine a rebound parameter threshold according to the respective second battery rebound parameters corresponding to all the batteries of the battery system; When the third battery rebound parameter of any one of the batteries is greater than the rebound parameter threshold, a voltage rebound anomaly warning for the battery system is issued.

19. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein when the processor executes the computer program, the battery thermal runaway risk diagnosis method according to any one of claims 1-10 is implemented.

20. A computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the battery thermal runaway risk diagnosis method according to any one of claims 1-10 is implemented.

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