Battery adaptive equalization control method and battery management system

Abstract

The invention discloses a battery adaptive equalization control method and a battery management system, and relates to the technical field of power battery management. The method specifically comprises the following steps: when the battery is in a natural discharge state, respectively acquiring the residual electric quantity of each battery cell in the battery at a first time node and a second time node, and calculating the difference value of each battery cell relative to the minimum residual electric quantity; based on the difference variation of the first time node and the second time node and the corresponding time interval, determining the self-discharge speed difference between each battery cell and the battery cell with the minimum residual electric quantity; and when the self-discharge speed difference of each battery cell exceeds a first threshold value, balancing the single battery cells exceeding the threshold value. The invention aims to realize a more efficient and flexible equalization scheme with adaptive capability so as to reduce the complexity of parameter configuration, improve the adaptive capability of a battery cell and enhance the intelligent level of a battery management system.

Description

Technical Field

[0001] The present invention relates to the technical field of power battery management, and in particular to a battery adaptive balancing control method and a battery management system. Background Art

[0002] In the battery management system (BMS), battery balancing technology is a key means to ensure the consistency of battery packs, increase service life and improve energy utilization. The current balancing solution commonly used in the industry is to configure parameters and lock the solution when the software is frozen, thereby ensuring the stability of the battery management strategy. Software freezing refers to the final control strategy and parameters determined in the later stage of battery management system development after multiple rounds of testing and verification, and no further adjustments are made.

[0003] The current balancing solution requires that the cell parameter calibration and balancing strategy be determined when the software is frozen. When different types of batteries or different models need to replace cells, recalibration must be performed. For example, in application scenarios such as new energy vehicles or energy storage, battery packs may be provided by different suppliers, and the same model may have different batches of batteries, resulting in certain differences in key parameters such as the internal resistance and capacity of the cell. If the original balancing parameters are still used, the balancing effect may be poor, and even the energy consumption performance and endurance of the entire vehicle may be affected. Therefore, each time the cell is replaced, the cell needs to be recalibrated, which increases development costs and debugging time.

[0004] Therefore, how to achieve a more efficient, flexible and adaptive balancing solution to reduce the complexity of parameter configuration, improve the adaptability of battery cells, and enhance the intelligence level of the battery management system is a technical problem that needs to be solved urgently in this field. Summary of the invention

[0005] The main purpose of the present invention is to provide a battery adaptive balancing control method and a battery management system, aiming to achieve a more efficient, flexible and adaptive balancing solution to reduce the complexity of parameter configuration, improve the adaptability of battery cells, and enhance the intelligence level of the battery management system.

[0006] In order to achieve the above object, the present invention proposes a battery adaptive balancing control method, comprising the following steps: When the battery is in natural discharge, the remaining power of each battery cell in the battery is obtained at a first time node and a second time node, and the difference of each battery cell relative to the minimum remaining power is calculated; Based on the difference change between the first time node and the second time node and the corresponding time interval, determine the self-discharge rate difference between each battery cell and the battery cell with the minimum remaining power; When the self-discharge rate difference of each battery cell exceeds a first threshold, the single battery cells exceeding the threshold are balanced.

[0007] During the natural discharge process of the battery, the self-discharge speed difference of each cell can be accurately calculated to timely discover the differences between cells and make adjustments through adaptive balancing strategies. It can effectively reduce the performance degradation caused by inconsistent power between cells, improve the efficiency and service life of the battery pack, and avoid energy loss and temperature rise caused by excessive or frequent balancing, thereby optimizing the battery management strategy and improving the overall performance of the battery.

[0008] In one embodiment of the present application, it also includes: When the self-discharge rate difference of each battery cell does not exceed the first threshold, the battery cell balancing is not performed.

[0009] When the self-discharge rate difference between the battery cells does not exceed the set first threshold, the battery management system will not perform cell balancing, thereby avoiding unnecessary balancing cycles. In this way, it can effectively reduce the energy loss and temperature rise problems that may occur during the balancing process, extend the battery life and improve the overall efficiency of the battery management system.

[0010] In one embodiment of the present application, after balancing the single cells exceeding the threshold, the method further includes: The balancing execution time is obtained, and the balancing self-adaptation interval time is adjusted according to the balancing execution time and a set second threshold; wherein the adjustment of the balancing self-adaptation interval time does not exceed a minimum time limit.

[0011] By dynamically adjusting the balancing adaptive interval time, the self-discharge characteristics of the battery cell and the battery status changes can be more accurately matched, avoiding the disadvantages of fixed interval time and making the balancing operation more flexible and efficient.

[0012] In one embodiment of the present application, when the equalization execution time exceeds an upper limit ratio of a set time, the equalization self-adaptation interval time is reduced.

[0013] When the balancing execution time exceeds the upper limit of the set time, by shortening the balancing adaptive interval time, the response speed of the battery management system can be improved, making the balancing operation more timely, thereby more effectively preventing the increase of the power difference between the cells. Further improve the balancing efficiency of the battery pack and reduce the performance degradation caused by inconsistent cells.

[0014] In an embodiment of the present application, when the equalization execution time is lower than a lower limit ratio of a set time, the equalization self-adaptation interval time is increased.

[0015] When the balancing execution time is lower than the lower limit ratio of the set time, by increasing the balancing adaptive interval time, the battery management system can avoid energy loss and battery over-balancing problems caused by too frequent balancing operations.

[0016] In one embodiment of the present application, after reducing the equalization adaptive interval time, it is determined whether the reduced equalization adaptive interval time is the minimum time, and if so, the equalization duty cycle is increased.

[0017] After reducing the balancing adaptive interval time, by judging whether the reduced balancing adaptive interval time reaches the minimum set value and increasing the balancing duty cycle when it reaches the minimum value, it can be ensured that the battery management system can fully eliminate the power difference between the cells within the shortest balancing cycle by extending the duration of each balancing operation.

[0018] In an embodiment of the present application, after reducing the equalization self-adaptation interval time, it is determined whether the reduced equalization self-adaptation interval time is the minimum time, and if not, the equalization duty cycle is reduced.

[0019] After reducing the balancing adaptive interval time, if the reduced balancing adaptive interval time does not reach the minimum setting value, the balancing control strategy of the battery can be further optimized by reducing the balancing duty cycle. Without increasing additional energy consumption and temperature rise, the intensity and cycle of the balancing operation can be reasonably adjusted to better adapt to the self-discharge characteristics of the battery.

[0020] In an embodiment of the present application, when the balancing execution time exceeds a second threshold, a suggestion to replace the battery cell is output.

[0021] When the balancing execution time exceeds the second threshold, the system automatically outputs a prompt "Replacement of battery cells" to promptly identify potential battery cell problems and handle them accordingly. This helps the battery management system maintain battery health more effectively, promptly identify battery cell anomalies and take necessary replacement measures, thereby ensuring the safety of the battery pack.

[0022] In one embodiment of the present application, after the balancing is completed, the following further steps are included: Record historical equilibrium time and historical state parameters, and train equilibrium parameter learning model; The current state parameters are obtained, and the equilibrium time is obtained according to the equilibrium parameter learning model.

[0023] By recording the historical balancing time and state parameters and training the balancing parameter learning model, the balancing process can be intelligently optimized, making each balancing operation more accurate and efficient.

[0024] The present application also discloses a battery management system, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the battery adaptive balancing control method as described in any one of the above items.

[0025] The above technical solution can accurately calculate the self-discharge speed difference of each cell during the natural discharge process of the battery, timely discover the difference between cells, and make adjustments through adaptive balancing strategies. It can effectively reduce the performance degradation caused by inconsistent power between cells, improve the efficiency and service life of the battery pack, and avoid energy loss and temperature rise caused by excessive or frequent balancing, thereby optimizing the battery management strategy and improving the overall performance of the battery. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The present invention is described in detail below with reference to specific embodiments and accompanying drawings, wherein: Figure 1 This is a schematic diagram of the process structure of the first embodiment of the present invention. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solution and advantages of the present invention clearer, the present invention is described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the following specific embodiments are only used to explain the present invention and do not constitute a limitation to the present invention.

[0028] like Figure 1 As shown, in order to achieve the above purpose, the present invention proposes a battery adaptive balancing control method, comprising the following steps: When the battery is in natural discharge, the remaining power of each battery cell in the battery is obtained at a first time node and a second time node, and the difference of each battery cell relative to the minimum remaining power is calculated; Based on the difference change between the first time node and the second time node and the corresponding time interval, determine the self-discharge rate difference between each battery cell and the battery cell with the minimum remaining power; When the self-discharge rate difference of each battery cell exceeds a first threshold, the single battery cells exceeding the threshold are balanced.

[0029] Specifically, when the battery is in a natural discharge state, the battery management system monitors the remaining power of each battery cell in the battery in real time through the battery management unit. The battery management system records the remaining power data of each battery cell at a first time node and a second time node, respectively. The first time node and the second time node are selected as the moments when the battery is in a static state to ensure that the change in the power of the battery cell is caused by self-discharge. The data obtained at these two time nodes will be used to calculate the difference of each battery cell relative to the battery cell with the minimum remaining power. The battery management system compares the remaining power of all batteries with the battery cell with the minimum remaining power, and calculates the power difference of each battery cell.

[0030] The battery management system calculates the self-discharge rate of each battery cell based on the difference in the remaining power of the battery cell at the first time node and the second time node, combined with the time interval between the two time nodes. The core of this step is to analyze the power attenuation of each battery cell within a given time period, so as to determine the difference between the self-discharge characteristics of each battery cell and the minimum remaining power cell.

[0031] When the battery management system detects that the self-discharge rate difference of some cells exceeds the set first threshold, the system will start the balancing mechanism. When the self-discharge rate difference of a cell exceeds the set first threshold, the cell will be marked as a target cell that needs to be balanced. The battery management system will balance these target cells and adopt appropriate balancing strategies to correct the power difference of each cell, and finally make the remaining power of all cells consistent. During the balancing process, the battery management system ensures that the power difference of each cell in the battery pack is minimized by adjusting the current flow between the cells, so as to achieve ideal power consistency.

[0032] The following are some examples: Step 1: When the vehicle is no longer in use and enters the stationary mode, the battery management system's built-in timer wake-up module will perform a timed operation on the open circuit voltage detection module. When the timing is met, the open circuit voltage detection module will be started to correct the battery state of charge and record the current state of charge of each single battery and the first time node of the current time.

[0033] Step 2: According to the state of charge value of each single battery, the difference in the state of charge of the battery is calculated. During the calculation, each single battery is compared with the battery with the lowest state of charge to obtain the difference value of the battery state of charge, that is, the difference in the battery state of charge between any single battery and the lowest single battery at the beginning of the adaptation. And the difference value of the battery state of charge at this time is associated with the first time node. That is, the consistency difference feature information of the start of the timing of the adaptive algorithm is obtained.

[0034] Step 3: When the set adaptive interval time is reached, the next time the vehicle meets the stationary mode and is awakened by the timer awakening module, the battery charge state module is started to correct the battery charge state and record the current charge state of each single battery and the second time node.

[0035] Step 4: According to the state of charge value of each single battery, the battery state of charge difference is calculated. During the calculation, each single battery is compared with the battery with the lowest state of charge to obtain the battery state of charge difference value, that is, the battery state of charge difference between any single battery and the lowest single battery at the beginning of the adaptation. And the battery state of charge difference value at this time is associated with the second time node. That is, the consistency difference feature information at the end of the timing of the adaptive algorithm is obtained.

[0036] Step 5: In step 2 and step 4, the consistency difference and time difference are obtained respectively. The self-discharge speed difference between each battery cell and the lowest cell obtained by this adaptive calculation is calculated by the ratio of the consistency difference to the time difference. Speed1=(Diff_SOC_end-Diff_SOC_Start) / (Data2-Data1); wherein, Diff_SOC_end represents the battery state of charge difference between any cell and the lowest cell at the end of the adaptive process; Diff_SOC_Start represents the battery state of charge difference between any cell and the lowest cell at the start of the adaptive process; Data2 represents the second time node; Data1 represents the first time node.

[0037] Step 6: When the speed Speed1 in step 5 is greater than the set start threshold of the self-discharge speed difference between each battery cell and the lowest single cell, the single cells exceeding the threshold are marked for balancing.

[0038] Step 7: Start the cell balancing mechanism with the balancing mark to balance the power of each cell until it reaches the balanced consistency.

[0039] Step 8: Record the equalization time and start the equalization parameter self-learning intelligent program.

[0040] Step 9: The balance is completed and waits for the next execution.

[0041] The above technical solution can accurately calculate the self-discharge speed difference of each cell during the natural discharge process of the battery, timely discover the difference between cells, and make adjustments through adaptive balancing strategies. It can effectively reduce the performance degradation caused by inconsistent power between cells, improve the efficiency and service life of the battery pack, and avoid energy loss and temperature rise caused by excessive or frequent balancing, thereby optimizing the battery management strategy and improving the overall performance of the battery.

[0042] In one embodiment of the present application, it also includes: When the self-discharge rate difference of each battery cell does not exceed the first threshold, the battery cell balancing is not performed.

[0043] Specifically, when the battery management system detects that the self-discharge speed difference of all cells does not exceed the set first threshold, the system stops the balancing operation. In this case, since the self-discharge speed difference between the cells is small, the battery management system determines that cell balancing is not necessary. Therefore, the system will not adjust the power between the cells, avoid unnecessary balancing operations, reduce energy loss, and improve the efficiency of the battery management system.

[0044] With the above technical solution, when the self-discharge rate difference between the battery cells does not exceed the set first threshold, the battery management system will not perform the cell balancing operation, thereby avoiding unnecessary balancing cycles. In this way, it is possible to effectively reduce the energy loss and temperature rise problems that may occur during the balancing process, extend the battery life and improve the overall efficiency of the battery management system.

[0045] In one embodiment of the present application, after balancing the single cells exceeding the threshold, the method further includes: The balancing execution time is obtained, and the balancing self-adaptation interval time is adjusted according to the balancing execution time and a set second threshold; wherein the adjustment of the balancing self-adaptation interval time does not exceed a minimum time limit.

[0046] Specifically, after balancing the cells exceeding the set threshold, the battery management system also monitors and records the execution time of the balancing operation when performing the balancing operation. The balancing execution time refers to the time interval from starting the balancing operation to completing the balancing operation.

[0047] When the battery management system finds that the balancing execution time exceeds the set second threshold, the system will advance the trigger time of the next balancing operation, that is, shorten the balancing adaptive interval. On the contrary, if the balancing execution time does not reach the second threshold, the system will delay the trigger time of the next balancing operation and increase the balancing adaptive interval. Through this dynamic adjustment mechanism, the battery management system can better adapt to changes in the battery cell state and optimize the timing of battery balancing operations.

[0048] It is worth noting that in order to avoid too frequent balancing operations or too long waiting time, the adjustment of the balancing interval time will be subject to the minimum time constraint. Even if the balancing adaptive interval time calculated by the system needs to be further adjusted, the battery management system will ensure that the adjusted balancing interval time is not less than the preset minimum time limit. In this way, the battery management system can ensure the cell balancing effect while avoiding unnecessary energy loss and temperature rise caused by frequent balancing operations.

[0049] By adopting the above technical solution, by dynamically adjusting the balancing adaptive interval time, the self-discharge characteristics of the battery cell and the battery state changes can be more accurately matched, avoiding the disadvantages brought by the fixed interval time, and making the balancing operation more flexible and efficient.

[0050] In one embodiment of the present application, when the equalization execution time exceeds an upper limit ratio of a set time, the equalization self-adaptation interval time is reduced.

[0051] Specifically, when the battery management system finds that the current balancing execution time exceeds the set upper limit ratio, the system will dynamically adjust the adaptive interval time of the next balancing operation based on this information. The adjustment method is to shorten the balancing adaptive interval time, thereby triggering the next balancing operation in advance. This adjustment can help the system perform balancing operations between cells more timely and avoid large differences in cell status due to long balancing time.

[0052] The adjusted balancing adaptive interval will take into account the overall battery usage status and the self-discharge characteristics of the battery cells. When the battery management system detects that the balancing execution time is too long and exceeds the upper limit, shortening the balancing adaptive interval can speed up the balancing frequency, helping the battery pack maintain a more consistent battery cell state, thereby improving the overall performance of the battery.

[0053] To avoid energy loss or system temperature rise caused by too frequent balancing operations, the adjustment of the balancing adaptive interval time is still subject to the minimum time limit. Even if the balancing execution time exceeds the set upper limit ratio, the adjusted balancing interval time will not be lower than the set minimum interval time, thereby ensuring the stability and safety of the battery management system during balancing.

[0054] The following are some examples: The initial balancing time of the battery is 30 days; when it is installed in the vehicle, the parameters are adapted. First, it is determined whether the balancing execution time exceeds the second threshold. If not, it is determined whether the balancing execution time exceeds 70% of the second threshold. If it exceeds 70% of the second threshold, the balancing adaptation interval is reduced by 5 days to achieve adaptive intelligent adjustment. At the same time, in order to avoid the interval time being too short, the minimum time is set to 5 days.

[0055] By adopting the above technical solution, when the equalization execution time exceeds the upper limit ratio of the set time, the response speed of the battery management system can be improved by shortening the equalization adaptive interval time, making the equalization operation more timely, thereby more effectively preventing the increase of the power difference between the cells. The equalization efficiency of the battery pack is further improved, and the performance degradation caused by inconsistent cells is reduced.

[0056] In an embodiment of the present application, when the equalization execution time is lower than a lower limit ratio of a set time, the equalization self-adaptation interval time is increased.

[0057] Specifically, when the battery management system detects that the balancing execution time is lower than the set time lower limit ratio, it means that the current balancing operation is executed too short. In order to ensure that the power difference between the cells can be better adjusted, the battery management system will dynamically adjust the balancing adaptive interval. The specific adjustment method is to increase the balancing adaptive interval, that is, to delay the trigger time of the next balancing operation. By extending the balancing interval, the system can ensure that the battery management system makes sufficient balancing adjustments to the cells to avoid excessive operations or energy waste due to frequent balancing.

[0058] When increasing the adaptive equalization interval, the battery management system will intelligently adjust the triggering time of the next equalization according to the actual cell state, usage conditions and self-discharge characteristics. This not only helps to avoid unnecessary frequent equalization when the cell state changes are not obvious, but also ensures that the battery management system performs equalization operations at reasonable intervals.

[0059] The following are some examples: The initial balancing time of the battery is 30 days. When it is installed in the vehicle, the parameters are adapted. First, it is determined whether the balancing execution time exceeds the second threshold. If not, it is determined whether the balancing execution time is less than 30% of the second threshold. If so, the balancing adaptation interval is increased by 5 days.

[0060] By adopting the above technical solution, when the balancing execution time is lower than the lower limit ratio of the set time, by increasing the balancing adaptive interval time, the battery management system can avoid energy loss and battery over-balancing problems caused by too frequent balancing operations.

[0061] In one embodiment of the present application, after reducing the equalization adaptive interval time, it is determined whether the reduced equalization adaptive interval time is the minimum time, and if so, the equalization duty cycle is increased.

[0062] Specifically, when the battery management system exceeds the set upper limit ratio in the balancing execution time, it triggers the next balancing operation in advance by reducing the balancing adaptive interval time. After reducing the balancing adaptive interval time, the battery management system first needs to determine whether the adjusted balancing adaptive interval time has reached the preset minimum setting value.

[0063] If the reduced balancing adaptive interval time has reached or fallen below the minimum setting value, the battery management system will start adjusting the balancing duty cycle. The balancing duty cycle refers to the proportion of balancing operation in a cycle. The purpose of increasing the balancing duty cycle is to further improve the consistency of power between cells by increasing the intensity and duration of the balancing operation when the balancing interval has reached the minimum setting value.

[0064] When the balancing adaptive interval is adjusted to the minimum setting value, the battery management system will increase the balancing duty cycle to strengthen the balancing adjustment between the cells. The increase in the balancing duty cycle means that the duration of each balancing operation will be extended, so that even if the balancing interval is at the minimum value, the battery management system can still ensure that the difference in cell power can be fully corrected by increasing the intensity of each balancing operation. Increasing the balancing duty cycle can ensure that the cells are fully charged and discharged in a shorter balancing cycle, thereby optimizing the overall performance of the battery.

[0065] The following are some examples: The initial balancing time of the battery is 30 days. When it is installed in the vehicle, the parameters are adapted. First, it is determined whether the balancing execution time exceeds the second threshold. If not, it is determined whether the balancing execution time exceeds 70% of the second threshold. If it exceeds 70% of the second threshold, the balancing adaptation interval is reduced by 5 days. It is determined whether the current balancing time interval is 5 days. If so, the duty cycle is increased.

[0066] By adopting the above technical solution, after reducing the balancing adaptive interval time, by judging whether the reduced balancing adaptive interval time reaches the minimum set value, and increasing the balancing duty cycle when it reaches the minimum value, it can be ensured that the battery management system can fully eliminate the power difference between the battery cells within the shortest balancing cycle by extending the duration of each balancing operation.

[0067] In an embodiment of the present application, after reducing the equalization self-adaptation interval time, it is determined whether the reduced equalization self-adaptation interval time is the minimum time, and if not, the equalization duty cycle is reduced.

[0068] Specifically, when the battery management system detects that the balancing execution time exceeds the set upper limit ratio, the system will reduce the balancing self-adaptation interval time to trigger the next balancing operation in advance. At this time, the battery management system first determines whether the reduced balancing self-adaptation interval time has reached the preset minimum setting value.

[0069] If the reduced balancing adaptive interval time does not reach the minimum set value, the battery management system will further optimize the balancing operation by reducing the balancing duty cycle. When the balancing adaptive interval time does not reach the minimum set value, reducing the balancing duty cycle can reduce the duration of each balancing operation and avoid unnecessary energy waste or temperature rise caused by too frequent balancing operations.

[0070] The following are some examples: The initial balancing time of the battery is 30 days. When it is installed in the vehicle, the parameters are adapted. First, determine whether the balancing execution time exceeds the second threshold. If not, determine whether the balancing execution time exceeds 70% of the second threshold. If it exceeds 70% of the second threshold, reduce the balancing adaptation interval by 5 days. Determine whether the current balancing time interval is 5 days. If not, reduce the duty cycle.

[0071] By adopting the above technical solution, after reducing the balancing adaptive interval time, if the reduced balancing adaptive interval time does not reach the minimum set value, the balancing control strategy of the battery can be further optimized by reducing the balancing duty cycle. Without increasing additional energy consumption and temperature rise, the intensity and cycle of the balancing operation can be reasonably adjusted to better adapt to the self-discharge characteristics of the battery.

[0072] In an embodiment of the present application, when the balancing execution time exceeds a second threshold, a suggestion to replace the battery cell is output.

[0073] Specifically, the battery management system continuously tracks the execution time of each balancing operation and compares it with the set upper limit of the balancing execution time. When the battery management system detects that the balancing execution time exceeds the second threshold, the system will automatically determine that there may be a large power difference or self-discharge problem in the battery cells, resulting in the balancing operation cannot be completed within the expected time. In this case, the battery management system will output a suggestion to prompt the operator or maintenance personnel to consider replacing the battery cells.

[0074] With the above technical solution, when the equalization execution time exceeds the second threshold, the prompt "recommendation to replace the battery cell" is automatically output, so that potential problems of the battery cell can be discovered in time and handled accordingly. It can help the battery management system to maintain battery health more effectively, discover battery cell abnormalities in time and take necessary replacement measures, thereby ensuring the safety of the battery pack.

[0075] In one embodiment of the present application, after the balancing is completed, the following further steps are included: Record historical equilibrium time and historical state parameters, and train equilibrium parameter learning model; The current state parameters are obtained, and the equilibrium time is obtained according to the equilibrium parameter learning model.

[0076] Specifically, after the battery management system completes the balancing operation, the system will continue to perform the following steps. First, the battery management system will record the historical balancing time and corresponding historical state parameters of each balancing operation. The historical state parameters include but are not limited to important data such as the SOC, temperature, and voltage of the battery cell, which will be used as the training input of the balancing parameter learning model. After multiple balancing operations, the battery management system will gradually accumulate enough historical data and use these historical data to train the balancing parameter learning model. The learning model can establish an adaptive prediction model based on the relationship between the historical balancing time and the historical state parameters to optimize the operation strategy in the future balancing process. Next, at the beginning of each balancing operation, the battery management system will obtain the current battery state parameters in real time, including information such as the SOC, temperature, and voltage of each battery cell, and input these current state parameters into the previously trained balancing parameter learning model. Through this model, the system can predict the balancing time required for the current balancing operation. According to the predicted balancing time, the system will dynamically adjust the length of the balancing operation to ensure that the battery pack completes the balancing task as efficiently as possible while maintaining safety.

[0077] By adopting the above technical solution, by recording the historical balancing time and state parameters and training the balancing parameter learning model, the balancing process can be intelligently optimized, making each balancing operation more accurate and efficient.

[0078] The present application also discloses a battery management system, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the battery adaptive balancing control method as described in any one of the above items.

[0079] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. All equivalent structural changes made by using the contents of the present invention specification and drawings under the inventive concept of the present invention, or directly / indirectly applied in other related technical fields are included in the patent protection scope of the present invention.

Claims

1. A battery adaptive balancing control method, characterized in that: The following steps are involved: When the battery is in natural discharge, the remaining power of each battery cell in the battery is obtained at a first time node and a second time node, and the difference of each battery cell relative to the minimum remaining power is calculated; Based on the difference change between the first time node and the second time node and the corresponding time interval, determine the self-discharge rate difference between each battery cell and the battery cell with the minimum remaining power; When the self-discharge rate difference of each battery cell exceeds a first threshold, the single battery cells exceeding the threshold are balanced.

2. The method for adaptive balancing control of a battery according to claim 1, characterized in that: Also includes: When the difference in self-discharge speeds of the battery cells does not exceed the first threshold, battery cell balancing is not performed.

3. The method for adaptive balancing control of a battery according to claim 1, characterized in that: After balancing the single cells that exceed the threshold, it also includes: The balancing execution time is obtained, and the balancing self-adaptation interval time is adjusted according to the balancing execution time and a set second threshold; wherein the adjustment of the balancing self-adaptation interval time does not exceed a minimum time limit.

4. The method for controlling the adaptive balancing of a battery according to claim 3, wherein: When the balancing execution time exceeds an upper limit ratio of a set time, the balancing self-adaptation interval time is reduced.

5. The method for adaptive balancing control of a battery as claimed in claim 3, characterized in that: When the balancing execution time is lower than the lower limit ratio of the set time, the balancing self-adaptation interval time is increased.

6. The method for adaptive balancing control of a battery as claimed in claim 4, characterized in that: After reducing the equalization self-adaptation interval time, it is determined whether the reduced equalization self-adaptation interval time is the minimum time, and if so, the equalization duty cycle is increased.

7. The method for controlling the adaptive balancing of a battery according to claim 6, wherein: After reducing the equalization self-adaptation interval time, it is determined whether the reduced equalization self-adaptation interval time is the minimum time, and if not, the equalization duty cycle is reduced.

8. The method for controlling the adaptive balancing of a battery according to claim 4, wherein: When the balancing execution time exceeds the second threshold, a suggestion to replace the battery cell is output.

9. The method for controlling the adaptive balancing of a battery according to claim 1, wherein: After the balance is completed, it also includes: Record historical equilibrium time and historical state parameters, and train equilibrium parameter learning model; The current state parameters are obtained, and the equilibrium time is obtained according to the equilibrium parameter learning model.

10. A battery management system, comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the adaptive balancing control method for a battery according to any one of claims 1 to 9.

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