A lithium battery BMS board control method and system based on power detection protection

Abstract

The present invention relates to the technical field of lithium battery management and control, and in particular to a lithium battery BMS board control method and system based on power detection protection, the method comprising the following steps: obtaining the real-time power of the lithium battery, calculating the actual discharge efficiency of the lithium battery according to the power change; comparing the preset discharge efficiency with the actual discharge efficiency, and calculating the deviation discharge efficiency; obtaining the temperature change of the battery during charging and discharging, and analyzing the correlation between the temperature change and the working time of the lithium battery; obtaining the self-discharge of the lithium battery at different temperatures, and analyzing the self-discharge efficiency of the lithium battery at different temperatures; calculating the actual power consumption efficiency based on the actual discharge efficiency, the deviation discharge efficiency and the self-discharge efficiency and generating a corrected charge and discharge termination strategy, so that the charging and discharging is stopped when the real-time power of the lithium battery reaches the power value for terminating the charging and discharging. This application optimizes the design and operation of the battery system through a comprehensive evaluation of the usage scenarios, improves the working efficiency and life, and reduces the risk of failure.

Description

Technical Field

[0001] The present invention relates to the technical field of lithium battery management and control, and in particular to a lithium battery BMS board control method and system based on power detection protection. Background Art

[0002] With the increasing popularity of electric vehicles, portable devices and renewable energy systems, lithium batteries have become a widely used high-energy density battery. At present, in the use of lithium batteries, it is necessary to monitor and control the charging and discharging of lithium batteries through a battery management system board (BMS board).

[0003] Existing BMS boards generally have preset control strategies to control the termination of charge and discharge of lithium batteries based on usage and production experience. They monitor the voltage and temperature of the battery, and control the charging current and charging termination conditions according to the preset charging strategy to avoid overcharging. In terms of discharge, the BMS board monitors the voltage and current of the battery, and controls the discharge current and discharge termination conditions according to the preset discharge strategy to avoid over-discharge.

[0004] With regard to the above-mentioned related technologies, there are the following defects: the preset BMS board control strategy is the optimal control strategy only in the preset usage environment and lithium battery usage conditions. During the actual use of the lithium battery, the environmental factors and the conditions of the lithium battery itself are different from the preset conditions. Therefore, the preset control strategy is difficult to control the charging and discharging of the lithium battery in time according to the actual situation to prevent overcurrent or over-discharge, thereby reducing the service life of the lithium battery. Summary of the invention

[0005] In order to improve the service life of lithium batteries, the present application provides a lithium battery BMS board control method and system based on power detection protection.

[0006] In the first aspect, the above-mentioned invention objective of the present application is achieved through the following technical solutions:

[0007] A lithium battery BMS board control method based on power detection protection, the lithium battery BMS board control method based on power detection protection comprises the steps of:

[0008] Obtain the real-time power of the lithium battery, and calculate the actual discharge efficiency of the lithium battery according to the change in power, the actual discharge efficiency = (battery discharge capacity change / battery rated capacity) * 100%, wherein the battery discharge capacity change represents the energy actually released by the battery during a discharge process, and the battery rated capacity represents the design capacity of the battery;

[0009] Compare the preset discharge efficiency with the actual discharge efficiency to calculate the deviation discharge efficiency, wherein the deviation discharge efficiency = the preset discharge efficiency - the actual discharge efficiency, wherein the preset discharge efficiency is the expected discharge efficiency preset based on the lithium battery design parameters;

[0010] Obtain the temperature changes of the battery during charging and discharging, record the temperature variables at different charging and discharging times, and analyze the correlation between temperature changes and lithium battery working time;

[0011] Obtain the self-discharge amount of lithium batteries at different temperatures, and build the correlation between temperature and self-discharge amount to analyze the self-discharge efficiency of lithium batteries at different temperatures;

[0012] The actual power consumption efficiency is calculated based on the actual discharge efficiency, the deviation discharge efficiency and the self-discharge efficiency, and the formula is: P1=P2-P3, wherein P1 is the actual power consumption efficiency, P2 is the actual discharge efficiency, and P3 is the self-discharge efficiency;

[0013] A modified charge and discharge suspension strategy is generated according to the actual power consumption efficiency. The modified charge and discharge suspension strategy includes the charge and discharge duration and the charge and discharge suspension power value. When the real-time power of the lithium battery reaches the charge and discharge suspension power value, the charge and discharge operation is stopped.

[0014] By adopting the above technical scheme, the actual discharge efficiency, temperature change and self-discharge of the battery are monitored in real time, and the actual power consumption efficiency is calculated based on these parameters and a corrected charge and discharge termination strategy is generated. Compared with the existing charge and discharge strategy that is only set according to factory parameters, this scheme predicts the actual power consumption of the battery and judges the power situation. Based on the actual power consumption and the prediction results, a corrected charge and discharge termination strategy is generated to more accurately control the charge and discharge process of the battery, avoid excessive charge and discharge, reduce battery loss, and thus extend the service life of the battery; based on the deviation discharge efficiency and the self-discharge efficiency, a corrected charge and discharge termination strategy is formulated to ensure that the battery does not exceed a safe range during the charging and discharging process. The specific charge and discharge termination strategy is determined according to actual needs, for example, whether to terminate the charge and discharge process is determined based on a preset threshold or algorithm. Compared with the existing charge and discharge termination strategy, this scheme is more flexible and practical.

[0015] In a preferred example, the present application can be further configured as follows: in the step of obtaining the temperature change of the battery during charging and discharging, recording the temperature variables of different charging and discharging durations, and analyzing the correlation between the temperature change and the working duration of the lithium battery, the steps are as follows:

[0016] Obtain the temperature data corresponding to different working hours of the battery and build a temperature-working hour correlation database;

[0017] The preset temperature-working time correlation calculation model calculates the temperature-working time correlation factor based on the temperature data in the temperature-working time correlation database;

[0018] The preset correlation verification model analyzes the correlation between temperature and working time based on the temperature data of the temperature-working time correlation database, and the correlation includes a linear relationship and a nonlinear relationship. Specifically, the calculation formula of the temperature-working time correlation coefficient is as follows: Where, T is the temperature and t is the working time;

[0019] If ρ does not reach the preset reference value, the temperature data is abnormal, and the abnormal temperature data is backed up.

[0020] By adopting the above technical scheme, the preset temperature-working time correlation calculation model calculates the temperature-working time correlation factor based on the temperature data in the associated database, which is used for quantitative evaluation of the relationship between temperature and working time, so that this scheme has the ability to predict stable changes; the correlation between temperature and working time is verified through the preset correlation verification model to determine whether there is a linear relationship or a nonlinear relationship between temperature and working time, and further confirm the degree of influence of temperature on working time, and whether there are other factors. The correlation coefficient ρ is used to check the correlation degree of temperature data. If the preset baseline value is not reached, it can be judged that the temperature data is abnormal, which helps to timely discover and deal with temperature abnormalities, improve the safety and reliability of the battery system, and help optimize the design and operation of the battery system, improve the working efficiency and life of the battery, and reduce the risk of overcharging and over-discharging failures.

[0021] In a preferred example, the present application can be further configured as follows: after obtaining the temperature change of the battery during charging and discharging, recording the temperature variables of different charging and discharging durations, and analyzing the correlation between the temperature change and the working duration of the lithium battery, the following steps are included:

[0022] Acquire ambient temperature data and ambient humidity data, and input the ambient temperature data and ambient humidity data into a preset usage scenario database, and define different ambient temperature data and ambient humidity data in the usage scenario database as different usage scenarios;

[0023] The temperature change efficiency corresponding to different usage scenarios is obtained, and the usage scenario is associated with the temperature change efficiency, and a scene factor K corresponding to the usage scenario is generated, wherein the scene factor K is used to represent the influence of the ambient temperature data and the ambient humidity data on the temperature change efficiency.

[0024] By adopting the above technical solution, a scenario factor K is generated according to the degree of influence of the ambient temperature data and the ambient humidity data to represent the influence of these factors on the temperature change efficiency, and the scenario factor K is calculated according to the changes in the ambient temperature data and the ambient humidity data. This solution considers the influence of ambient temperature and humidity on the temperature change efficiency and represents it through the scenario factor K. Such analysis more comprehensively evaluates the temperature change efficiency of lithium batteries in different usage scenarios, helps to optimize the design and usage strategy of the lithium battery system, and improves the performance and reliability of the system.

[0025] In a preferred example, the present application may be further configured as follows: in the step of obtaining the temperature change efficiency corresponding to different usage scenarios, associating the usage scenarios with the temperature change efficiency, and generating the scenario factor K corresponding to the usage scenarios, the following steps are included:

[0026] Acquire location data and usage time data when the battery is working, and associate the location data and the usage time data with the usage scenario;

[0027] Building a usage scenario portrait based on the location data and the usage time data, and associating the usage scenario with the usage scenario portrait;

[0028] Analyzing the location data based on the temperature change efficiency of the usage scenario to generate a location scenario factor d related to the location data;

[0029] Analyzing the usage time based on the temperature change efficiency of the usage scenario to generate a usage time factor x related to the usage time;

[0030] The scene factor K is calculated based on the location scene factor d and the usage time factor x. Specifically, the scene factor K=d*x / v, wherein v is a preset reference value. The larger the value of K, the higher the calculation accuracy of the scene factor.

[0031] By adopting the above technical solution, the location data and usage time data of the battery when it is working are obtained and associated with the usage scenario to build a usage scenario portrait. Based on the temperature change efficiency of the usage scenario, the location data and usage time are analyzed to generate a location scenario factor d related to the location data and a usage time factor x related to the usage time. Finally, the calculation accuracy of the scenario factor is evaluated by calculating the scenario factor K (T = d*x / v, where v is a preset reference value). This series of steps helps to understand the efficiency of temperature changes under different usage scenarios and associate the usage scenarios with the temperature change efficiency. Therefore, the beneficial effect of this solution is that it provides a comprehensive evaluation of usage scenarios, helps optimize the design and operation of battery systems, improves working efficiency and life, and reduces the risk of failure, thereby bringing significant benefits in practical applications.

[0032] In a preferred example, the present application can be further configured as follows: before obtaining the real-time power of the lithium battery and calculating the actual discharge efficiency of the lithium battery according to the power change, the actual discharge efficiency = (battery discharge capacity change / battery rated capacity) * 100%, wherein the battery discharge capacity change represents the energy actually released by the battery during a discharge process, and the battery rated capacity represents the battery design capacity, the following steps are included:

[0033] Record the number of times the lithium battery is charged and discharged as n, detect the real-time power of the battery and determine whether it has reached the maximum power;

[0034] If the real-time power of the battery reaches the maximum power, the real-time terminal voltage OCV of the battery is obtained, and the real-time terminal voltage OCV at this time is used as the actual maximum terminal voltage;

[0035] Calculating the battery loss rate m based on the actual maximum terminal voltage. Specifically, the calculation formula of the battery loss rate is: m=OCV / U0, where m is the battery loss rate, OCV is the actual maximum terminal voltage, and U0 is the rated terminal voltage of the battery;

[0036] Based on the battery loss rate and the charge and discharge times, a charge and discharge times-battery loss rate correlation curve is established, wherein the charge and discharge times-battery loss rate correlation curve is used to calculate the battery loss caused by battery charging and discharging;

[0037] The actual maximum power of the battery is obtained based on the charge and discharge times-battery loss rate correlation curve, and the actual maximum power is used to calibrate the actual battery capacity of the battery.

[0038] By adopting the above technical scheme, the real-time terminal voltage OCV of the battery is obtained and used as the actual maximum terminal voltage for calculating the battery loss rate and real-time terminal voltage calibration, so as to more accurately reflect the actual state of the battery, improve the calculation accuracy of the discharge efficiency, and establish a charge and discharge times-battery loss rate correlation curve to calculate the loss caused by battery charging and discharging. Compared with the prior art, this scheme is more in line with the actual use of the battery in terms of real-time terminal voltage calibration, establishment of charge and discharge times-battery loss rate correlation curve, and actual discharge efficiency calculation. These improvements and differences are helpful to improve the accurate assessment of the actual state of the lithium battery, optimize the design and operation of the battery system, and improve work efficiency and life.

[0039] In a preferred example, the present application can be further configured as follows: in the step of generating a modified charge and discharge suspension strategy according to the actual power consumption efficiency, the modified charge and discharge suspension strategy includes the charge and discharge duration and the power value for suspending charge and discharge, and when the real-time power of the lithium battery reaches the power value for suspending charge and discharge, the charge and discharge operation is stopped, and the modified charge and discharge suspension strategy also includes a buffer charge and discharge threshold, including the following steps:

[0040] When the real-time power level of the battery reaches the buffer charge and discharge threshold, a charge and discharge buffer instruction is generated, wherein the charge and discharge buffer instruction is used to shunt the charge and discharge of the battery;

[0041] When responding to the charge and discharge buffer instruction, the preset buffer unit works and performs charge and discharge.

[0042] Specifically, when the real-time power during the charging process reaches the buffer charge and discharge threshold, the customized current is shunted to the buffer unit to reduce the charging efficiency of the battery, so that the rate at which the battery approaches full load is reduced, which facilitates the detection of whether the battery power has reached the full load state;

[0043] When the buffer charge and discharge threshold is reached during the discharge process, the buffer unit discharges to provide a custom current, reducing the discharge of the battery and slowing down the rate at which the battery approaches no-load, making it easier to detect whether the battery has reached a no-load state.

[0044] By adopting the above technical scheme, the application of the modified charge and discharge termination strategy and the buffer charge and discharge threshold can more accurately control the battery charge and discharge process, avoid over-charge and discharge, extend the battery life, and improve safety. By shunting and adjusting the charge and discharge current, the rate at which the battery approaches a full charge or no-load state can be reduced, thereby improving the accurate monitoring of the battery status, helping to optimize battery management and improve the performance and reliability of the battery system.

[0045] In the second aspect, the above invention objective of the present application is achieved through the following technical solutions:

[0046] A lithium battery BMS board control device based on power detection protection, the lithium battery BMS board control device based on power detection protection comprising:

[0047] The actual discharge efficiency calculation module is used to obtain the real-time power of the lithium battery and calculate the actual discharge efficiency of the lithium battery according to the change in power. The actual discharge efficiency = (battery discharge capacity change / battery rated capacity) * 100%, wherein the battery discharge capacity change represents the energy actually released by the battery during a discharge process, and the battery rated capacity represents the design capacity of the battery;

[0048] A deviation discharge efficiency calculation module is used to calculate the deviation discharge efficiency by comparing the preset discharge efficiency with the actual discharge efficiency, wherein the deviation discharge efficiency = the preset discharge efficiency - the actual discharge efficiency, wherein the preset discharge efficiency is the expected discharge efficiency preset based on the lithium battery design parameters;

[0049] The temperature variable recording module is used to obtain the temperature changes of the battery during charging and discharging, record the temperature variables of different charging and discharging time, and analyze the correlation between the temperature changes and the working time of the lithium battery;

[0050] The self-discharge acquisition module is used to obtain the self-discharge of lithium batteries at different temperatures, build the temperature-self-discharge relationship, and analyze the self-discharge efficiency of lithium batteries at different temperatures;

[0051] an actual power consumption efficiency calculation module, used to calculate the actual power consumption efficiency based on the actual discharge efficiency, the deviation discharge efficiency and the self-discharge efficiency, the formula is: P1=P2-P3, wherein P1 is the actual power consumption efficiency, P2 is the actual discharge efficiency, and P3 is the self-discharge efficiency;

[0052] The modified charge and discharge suspension strategy generation module is used to generate a modified charge and discharge suspension strategy according to the actual power consumption efficiency. The modified charge and discharge suspension strategy includes the charge and discharge duration and the power value for suspending charge and discharge. When the real-time power of the lithium battery reaches the power value for suspending charge and discharge, the charge and discharge operation is stopped.

[0053] By adopting the above technical scheme, the actual discharge efficiency, temperature change and self-discharge of the battery are monitored in real time, and the actual power consumption efficiency is calculated based on these parameters and a corrected charge and discharge termination strategy is generated. Compared with the existing charge and discharge strategy that is only set according to factory parameters, this scheme predicts the actual power consumption of the battery and judges the power situation. Based on the actual power consumption and the prediction results, a corrected charge and discharge termination strategy is generated to more accurately control the charge and discharge process of the battery, avoid excessive charge and discharge, reduce battery loss, and thus extend the service life of the battery; based on the deviation discharge efficiency and the self-discharge efficiency, a corrected charge and discharge termination strategy is formulated to ensure that the battery does not exceed a safe range during the charging and discharging process. The specific charge and discharge termination strategy is determined according to actual needs, for example, whether to terminate the charge and discharge process is determined based on a preset threshold or algorithm. Compared with the existing charge and discharge termination strategy, this scheme is more flexible and practical.

[0054] Preferably, it also includes: a correlation database construction module, which is used to obtain temperature data corresponding to different working hours of the battery and construct a temperature-working hour correlation database;

[0055] A temperature-working time correlation calculation module, used to preset a temperature-working time correlation calculation model and calculate a temperature-working time correlation factor based on temperature data in a temperature-working time correlation database;

[0056] The correlation verification module is used to preset a correlation verification model and analyze the correlation between temperature and working time based on the temperature data in the temperature-working time correlation database. The correlation includes a linear relationship and a nonlinear relationship. Specifically, the calculation formula of the temperature-working time correlation coefficient is as follows: Where, T is the temperature and t is the working time;

[0057] The abnormal temperature data backup module is used to back up the abnormal temperature data if ρ does not reach a preset reference value, then the temperature data is abnormal.

[0058] By adopting the above technical scheme, the preset temperature-working time correlation calculation model calculates the temperature-working time correlation factor based on the temperature data in the associated database, which is used for quantitative evaluation of the relationship between temperature and working time, so that this scheme has the ability to predict stable changes; the correlation between temperature and working time is verified through the preset correlation verification model to determine whether there is a linear relationship or a nonlinear relationship between temperature and working time, and further confirm the degree of influence of temperature on working time, and whether there are other factors. The correlation coefficient ρ is used to check the correlation degree of temperature data. If the preset baseline value is not reached, it can be judged that the temperature data is abnormal, which helps to timely discover and deal with temperature abnormalities, improve the safety and reliability of the battery system, and help optimize the design and operation of the battery system, improve the working efficiency and life of the battery, and reduce the risk of overcharging and over-discharging failures.

[0059] On the third aspect, the above-mentioned purpose of the present application is achieved through the following technical solutions:

[0060] An electronic device includes 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 the above-mentioned lithium battery BMS board control method based on power detection protection are implemented.

[0061] Fourthly, the above-mentioned purpose of the present application is achieved through the following technical solutions:

[0062] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned lithium battery BMS board control method based on power detection protection are implemented.

[0063] In summary, the present application includes at least one of the following beneficial technical effects:

[0064] 1. Real-time monitoring of the actual discharge efficiency, temperature change and self-discharge of the battery, as well as calculation of the actual power consumption efficiency and generation of a modified charge and discharge termination strategy based on these parameters. Compared with the existing charge and discharge strategy that is only set according to factory parameters, this solution predicts the actual power consumption of the battery and determines the power situation. Based on the actual power consumption and the prediction results, a modified charge and discharge termination strategy is generated to more accurately control the charge and discharge process of the battery, avoid over-charge and discharge, reduce battery loss, and thus extend the service life of the battery; based on the deviation discharge efficiency and the self-discharge efficiency, a modified charge and discharge termination strategy is formulated to ensure that the battery does not exceed a safe range during the charging and discharging process. The specific charge and discharge termination strategy is determined according to actual needs, such as judging whether to terminate the charge and discharge process based on a preset threshold or algorithm. Compared with the existing charge and discharge termination strategy, this solution is more flexible and practical;

[0065] 2. The preset temperature-working time correlation calculation model calculates the temperature-working time correlation factor based on the temperature data in the associated database, which is used to quantitatively evaluate the relationship between temperature and working time, so that this solution has the ability to predict stable changes; the preset correlation verification model is used to verify the correlation between temperature and working time to determine whether there is a linear or nonlinear relationship between temperature and working time, and further confirm the degree of influence of temperature on working time, and whether there are other factors; the correlation coefficient ρ is used to check the degree of correlation of temperature data. If the preset benchmark value is not reached, it can be judged that the temperature data is abnormal, which helps to timely discover and deal with abnormal temperature conditions, improve the safety and reliability of the battery system, and help optimize the design and operation of the battery system, improve the working efficiency and life of the battery, and reduce the risk of overcharge and over-discharge failures;

[0066] 3. According to the influence of ambient temperature data and ambient humidity data, a scenario factor K is generated to represent the influence of these factors on the temperature change efficiency. The scenario factor K is calculated according to the changes in ambient temperature data and ambient humidity data. This solution considers the influence of ambient temperature and humidity on the temperature change efficiency and represents it through the scenario factor K. Such analysis more comprehensively evaluates the temperature change efficiency of lithium batteries in different usage scenarios, helps to optimize the design and use strategy of lithium battery systems, and improves the performance and reliability of the system.

[0067] 4. Obtain the location data and usage time data when the battery is working, and associate them with the usage scenarios to build a usage scenario portrait. Based on the temperature change efficiency of the usage scenario, analyze the location data and usage time to generate a location scenario factor d related to the location data and a usage time factor x related to the usage time. Finally, calculate the scenario factor K (T = d*x / v, where v is a preset reference value) to evaluate the calculation accuracy of the scenario factor. This series of steps helps to understand the efficiency of temperature changes under different usage scenarios and associate the usage scenarios with the temperature change efficiency. Therefore, the beneficial effect of this solution is that it provides a comprehensive evaluation of usage scenarios, helps optimize the design and operation of the battery system, improves working efficiency and life, and reduces the risk of failure, thereby bringing significant benefits in practical applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 It is a flow chart of a lithium battery BMS board control method based on power detection protection in an embodiment of the present application;

[0069] Figure 2 It is a flowchart of the steps before step S10 in a lithium battery BMS board control method based on power detection protection in an embodiment of the present application;

[0070] Figure 3 It is a flowchart of the steps in step S30 in a lithium battery BMS board control method based on power detection protection in an embodiment of the present application;

[0071] Figure 4 It is a flowchart of the steps after step S30 in a lithium battery BMS board control method based on power detection protection in an embodiment of the present application;

[0072] Figure 5 It is a flowchart of the steps in step S302 in a lithium battery BMS board control method based on power detection protection in an embodiment of the present application;

[0073] Figure 6 It is a principle block diagram of a lithium battery BMS board control device based on power detection protection in an embodiment of the present application;

[0074] Figure 7 It is a schematic diagram of an electronic device in an embodiment of the present application.

[0075] Figure Number:

[0076] 1. Actual discharge efficiency calculation module; 2. Deviation discharge efficiency calculation module; 3. Temperature variable recording module; 4. Self-discharge acquisition module; 5. Actual power consumption efficiency calculation module; 6. Correction charge and discharge termination strategy generation module; 7. Association database construction module; 8. Temperature-working time correlation calculation module; 9. Correlation verification module; 10. Abnormal temperature data backup module. DETAILED DESCRIPTION

[0077] The present application is further described in detail below in conjunction with the accompanying drawings.

[0078] In one embodiment, if Figure 1-5 As shown, the present application discloses a lithium battery BMS board control method based on power detection protection, which specifically includes the following steps:

[0079] S10: Acquire the real-time power of the lithium battery, and calculate the actual discharge efficiency of the lithium battery according to the change in power, the actual discharge efficiency = (battery discharge capacity change / battery rated capacity) * 100%, wherein the battery discharge capacity change represents the energy actually released by the battery during a discharge process, and the battery rated capacity represents the design capacity of the battery;

[0080] Specifically, it is necessary to obtain the real-time power of the lithium battery. In the embodiment of the present application, the real-time power is detected by the power sensor in the battery management system (BMS board), and the actual discharge efficiency of the lithium battery is calculated according to the change in power. For example: if a lithium battery with a rated capacity of 1000mAh releases 800mAh of energy during a discharge process, the actual discharge efficiency is 80%.

[0081] S20: Calculate the deviation discharge efficiency by comparing the preset discharge efficiency with the actual discharge efficiency, wherein the deviation discharge efficiency=the preset discharge efficiency-the actual discharge efficiency, wherein the preset discharge efficiency is the expected discharge efficiency preset based on the lithium battery design parameters;

[0082] Specifically, the preset discharge efficiency is an expected discharge efficiency preset based on the lithium battery design parameters. In the embodiment of the present application, 75% is used as the preset discharge efficiency and 80% is used as the actual discharge efficiency. According to the formula: deviation discharge efficiency = preset discharge efficiency - actual discharge efficiency, in the embodiment of the present application, deviation discharge efficiency = 75% - 80% = -5%.

[0083] S30: Obtaining temperature changes of the battery during charging and discharging, recording temperature variables at different charging and discharging times, and analyzing the correlation between the temperature changes and the working time of the lithium battery;

[0084] Specifically, the steps include: collecting data: using a temperature sensor to record the temperature data of the lithium battery during the charge and discharge process, and simultaneously recording the working time of the lithium battery; data processing: organizing and processing the collected temperature and working time data to ensure the accuracy and consistency of the data; drawing a graph: using the processed temperature and working time data to draw a temperature-working time graph, with the horizontal axis representing the working time and the vertical axis representing the temperature; analyzing the correlation: by analyzing the temperature-working time graph, determining the correlation between temperature changes and the working time of the lithium battery.

[0085] Furthermore, in the embodiment of the present application, according to the heat dissipation factor, the temperature of the battery increases with the increase of the working time, and in the embodiment of the present application, the correlation is calculated by a calculation model, and the calculation model calculates the temperature-working time curve. The calculation model includes linear regression, polynomial regression, and exponential function. The functional relationship p(t) between temperature and working time is obtained through the calculation model, and the functional relationship p(t) is used as the basis for predicting the temperature change.

[0086] S40: Obtaining the self-discharge amount of the lithium battery at different temperatures, and constructing a temperature-self-discharge amount correlation to analyze the self-discharge efficiency of the lithium battery at different temperatures;

[0087] Specifically, when a lithium battery is not in a working state (charging and discharging), it will self-discharge, that is, its own power will decrease. However, the existing power calculation only records the power up to the last working state, while ignoring the power loss of self-discharge, resulting in inaccurate power calculation. This solution improves the prediction accuracy of battery power by detecting and calculating the self-discharge power. The self-discharge amount of the battery is different at different temperatures. The self-discharge amount of the battery at different temperatures is recorded and input into a database. The calculation model calculates the functional relationship f(e) of temperature-self-discharge amount according to the temperature-self-discharge amount in the database, and predicts the self-discharge amount of the battery according to the functional relationship f(e).

[0088] S50: Calculating actual power consumption efficiency based on the actual discharge efficiency, the deviation discharge efficiency and the self-discharge efficiency, the formula is: P1=P2-P3, where P1 is the actual power consumption efficiency, P2 is the actual discharge efficiency, and P3 is the self-discharge efficiency;

[0089] Specifically, in the embodiment of the present application, the actual discharge efficiency within the time interval is: 80%; the deviation discharge efficiency is: 5%; the self-discharge efficiency is: 2%, where the actual discharge efficiency = the preset discharge efficiency - the deviation discharge efficiency. Based on the above data, we calculate the actual power consumption efficiency: the actual power consumption efficiency = the actual discharge efficiency - the self-discharge efficiency (P1 = P2-P3), the actual power consumption efficiency = 80%-2%; the actual power consumption efficiency = 78%. In this example, the actual power consumption efficiency is 78%. This means that in actual use, after considering the self-discharge efficiency and the deviation discharge efficiency, the actual power consumption efficiency of the lithium battery is 78%, and the factors affecting the actual power consumption efficiency include temperature, working time and self-discharge amount;

[0090] S60: generating a modified charge-discharge suspension strategy according to the actual power consumption efficiency, wherein the modified charge-discharge suspension strategy includes a charge-discharge duration and a charge value for suspending charge-discharge, and when the real-time charge reaches the charge value for suspending charge-discharge, stopping the charge-discharge operation;

[0091] Specifically, the modified charge and discharge termination strategy in the present application includes: also including stopping charging and discharging when the charge and discharge time of the lithium battery reaches a preset time. In other embodiments, the modified charge and discharge termination strategy can formulate other usage strategies related to battery use.

[0092] The power consumption of the battery is calculated according to time, temperature and self-discharge, which is convenient for accurately predicting the usage conditions that can be satisfied by the remaining power of the battery, such as the remaining usage time of the battery at different temperatures. Compared with the existing charge and discharge termination strategy based on power and rated discharge efficiency, the usage time (charging and discharging time) prediction of this scheme is calculated from multiple factors to improve the accuracy of the prediction, thereby avoiding overcharging or over-discharging caused by prediction errors and further improving the service life of the battery.

[0093] In S10: obtaining the real-time power of the lithium battery, and calculating the actual discharge efficiency of the lithium battery according to the change in power, the actual discharge efficiency = (battery discharge capacity change / battery rated capacity) * 100%, wherein the battery discharge capacity change represents the energy actually released by the battery during a discharge process, and the battery rated capacity represents the battery design capacity. Before this step, the following steps are included:

[0094] S101: Record the number of times the lithium battery is charged and discharged as n, detect the real-time power of the battery and determine whether the maximum power has been reached;

[0095] Specifically, when using lithium batteries, we record the number of charge and discharge times n through the system for subsequent calculations. At the same time, we detect the battery power in real time and compare it with the rated maximum power of the battery. When the real-time power of the battery reaches or approaches the rated maximum power, we believe that the battery has reached the maximum power.

[0096] S102: if the real-time power of the battery reaches the maximum power, obtain the real-time terminal voltage OCV of the battery, and use the real-time terminal voltage OCV at this time as the actual maximum terminal voltage;

[0097] Specifically, when the real-time power of the battery reaches the maximum power, we obtain the real-time terminal voltage OCV of the battery. The real-time terminal voltage refers to the voltage measurement value of the battery when it is not affected by the external load. We use this real-time terminal voltage OCV as the actual maximum terminal voltage for subsequent calculations.

[0098] In the embodiment of the present application, the system records that the battery has undergone 10 charge and discharge cycles. When the real-time power of the battery reaches the maximum power, we obtain the real-time terminal voltage OCV of the battery. It is assumed that the measured real-time terminal voltage is 4.1V.

[0099] S103: Calculating a battery loss rate m based on the actual maximum terminal voltage. Specifically, the calculation formula of the battery loss rate is: m=OCV / U0, where m is the battery loss rate, OCV is the actual maximum terminal voltage, and U0 is the rated terminal voltage of the battery;

[0100] Specifically, by calculating the ratio between the actual maximum terminal voltage OCV and the rated terminal voltage U0 of the battery, that is, m=OCV / U0, we obtain the battery loss rate m. This loss rate represents the ratio of the actual maximum terminal voltage to the rated terminal voltage.

[0101] In the embodiment of the present application, according to the formula m=OCV / U0, we calculate the battery loss rate m. Assuming that the rated terminal voltage U0 of the battery is 4.2V, then according to the measured real-time terminal voltage OCV=4.1V, we can calculate the battery loss rate m=4.1V / 4.2V≈0.976.

[0102] S104: establishing a charge and discharge times-battery loss rate correlation curve based on the battery loss rate and the charge and discharge times, wherein the charge and discharge times-battery loss rate correlation curve is used to calculate the battery loss caused by battery charging and discharging;

[0103] Specifically, according to multiple groups of charge and discharge times and corresponding power loss rates, a charge and discharge times-battery loss rate correlation curve is established through a linear regression model. In the embodiment of the present application, the linear relationship between the charge and discharge times-battery loss rate is: m=1-n / 10*(1-0.976), and in other embodiments it may be a neural network model.

[0104] S105: Acquire the actual maximum power of the battery based on the charge and discharge times-battery loss rate correlation curve, where the actual maximum power is used to calibrate the actual battery capacity of the battery;

[0105] Specifically, in the embodiment of the present application, the calculation formula for the actual maximum power is: Q max =Q1*m, where Q max is the actual maximum capacity, and Q1 is the rated maximum capacity.

[0106] In step S30: obtaining the temperature change of the battery during charging and discharging, recording the temperature variables at different charging and discharging times, and analyzing the correlation between the temperature change and the working time of the lithium battery, the following steps are included:

[0107] S31: Obtain temperature data corresponding to different working hours of the battery, and build a temperature-working hour association database;

[0108] Specifically, a time interval is set to collect data on the battery temperature. In the embodiment of the present application, the time interval is 5 minutes, that is, the temperature data of the battery is collected once every 5 minutes of the battery working time, and the collected temperature data is associated with the corresponding time interval, and the associated time interval and temperature data are input into a preset associated database to construct a temperature-working time associated database to provide a data basis for subsequent analysis.

[0109] S32: The preset temperature-working time correlation calculation model calculates the temperature-working time correlation factor based on the temperature data in the temperature-working time correlation database;

[0110] Specifically, in an embodiment of the present application, a linear regression model is selected to analyze and calculate the data in the temperature-working time association database, and generate a functional relationship p(t)=α+β*t, wherein α is the initial temperature of the battery when it is working, β is the correlation factor calculated by the linear regression model, and t is the working time.

[0111] S33: The preset correlation verification model analyzes the correlation between temperature and working time based on the temperature data in the temperature-working time correlation database, wherein the correlation includes a linear relationship and a nonlinear relationship. Specifically, the calculation formula of the temperature-working time correlation coefficient is as follows: Where, T is the temperature and t is the working time;

[0112] Specifically, the correlation coefficient formula of temperature-working time is used to perform correlation check on the functional relationship p(t) to improve the accuracy of data prediction.

[0113] S34: If ρ does not reach the preset reference value, the temperature data is abnormal, and the abnormal temperature data is backed up;

[0114] Specifically, in the calculation of the correlation coefficient, the closer the absolute value of ρ is to 1, the stronger the correlation is, and the closer the absolute value of ρ is to 0, the weaker the correlation is. In the embodiment of the present application, the baseline value of ρ is set to 0.5, that is, when the absolute value of ρ is less than 0.5, the data correlation of temperature-working time fails, then abnormal temperature values ​​are screened, and the screened temperature data are backed up and recorded.

[0115] After the step of S30: obtaining the temperature change of the battery during charging and discharging, recording the temperature variables at different charging and discharging times, and analyzing the correlation between the temperature change and the working time of the lithium battery, the following steps are included:

[0116] S301: Acquire ambient temperature data and ambient humidity data, and input the ambient temperature data and ambient humidity data into a preset usage scenario database, and define different ambient temperature data and ambient humidity data in the usage scenario database as different usage scenarios;

[0117] Specifically, different usage scenarios are divided according to different ambient temperatures and ambient humidity. In the embodiment of the present application, a temperature interval of 3°C and a humidity interval of 10% are set as different usage scenarios, and different usage scenarios are labeled. For example: a temperature of 25-28°C and a humidity of 80-90% are usage scenario 1; a temperature of 28-31°C and a humidity of 80-90% are usage scenario 2.

[0118] S302: Obtain the temperature change efficiency corresponding to different usage scenarios, associate the usage scenarios with the temperature change efficiency, and generate a scenario factor K corresponding to the usage scenarios, wherein the scenario factor K is used to represent the influence of the ambient temperature data and the ambient humidity data on the temperature change efficiency.

[0119] The temperature change efficiency = ΔT / Δt = (T2-T1) / (t2-t1), wherein ΔT is the temperature change, Δt is the time change, T1 and T2 are temperature values ​​at two different times, and t1 and t2 are time values ​​at two different times.

[0120] In the step of S302: obtaining the temperature change efficiency corresponding to different usage scenarios, associating the usage scenarios with the temperature change efficiency, and generating the scenario factor K corresponding to the usage scenarios, the following steps are included:

[0121] S3021: Acquire location data and usage time data when the battery is working, and associate the location data and the usage time data with the usage scenario;

[0122] Specifically, the location data of the battery when it is working is obtained based on GPS or other positioning technologies, and the usage time data is recorded at the same time. Each location data point and usage time is associated with the corresponding usage scenario to ensure that each data point is associated with the correct usage scenario.

[0123] S3022: constructing a usage scenario portrait based on the location data and the usage time data, and associating the usage scenario with the usage scenario portrait;

[0124] Specifically, based on the collected location data and usage time data, a usage scenario profile is constructed, including the characteristics of location and usage time. For example, for a certain location data point, its longitude, latitude, and altitude information are recorded; for usage time data, specific date, time, and duration information can be recorded. The usage scenario is associated with the corresponding usage scenario profile for subsequent analysis and calculation.

[0125] S3023: Analyze the location data based on the temperature change efficiency of the usage scenario, and generate a location scenario factor d related to the location data;

[0126] Specifically, the location data is analyzed based on known usage scenarios and corresponding temperature change efficiency data. Statistical methods, machine learning or other related technologies can be used to establish a relationship model between location data and temperature change efficiency. Based on the model, the location scenario factor d related to the location data is calculated to indicate the degree of influence of the location on the temperature change efficiency.

[0127] S3024: Analyze the usage time based on the temperature change efficiency of the usage scenario, and generate a usage time factor x related to the usage time;

[0128] Specifically, the usage time data is analyzed based on known usage scenarios and corresponding temperature change efficiency data. A relationship model between usage time data and temperature change efficiency is established using statistical methods, machine learning or other related technologies. Based on the model, a usage time factor x related to the usage time is calculated to indicate the degree of influence of the usage time on the temperature change efficiency.

[0129] S3025: Calculating the scene factor K based on the location scene factor d and the usage time factor x. Specifically, the scene factor K=d*x / v, where v is a preset reference value. The larger the value of K, the higher the calculation accuracy of the scene factor.

[0130] Specifically, in the embodiment of the present application, taking the use scenario of lithium batteries in electric vehicles as an example, the temperature change efficiency of lithium batteries is recorded so as to optimize the design and use of battery systems according to different use scenarios. In the embodiment of the present application, a large amount of location data and usage time data are collected, and the location scenario factor d and the usage time factor x have been calculated for each usage scenario.

[0131] Among them, the calculation of the location scenario factor d: Assume that we have a specific usage scenario, which corresponds to driving in urban congested traffic. We have concluded through data analysis that the location scenario factor d in this usage scenario is 0.8. This means that when driving in urban congested traffic, the degree of influence of location on the temperature change efficiency is 0.8.

[0132] Calculation of the usage time factor x: Continuing with the usage scenario of urban congestion, assume that we have calculated the usage time factor x to be 0.9. This means that the driving time in urban congestion has an impact on the temperature change efficiency of 0.9. It should be noted that in urban congestion, the battery usage is in a high energy consumption state for a long time, and the energy consumption is relatively stable.

[0133] Calculation of scene factor K: Now, we can use the formula K = d*x / v to calculate the scene factor K. Assume that the base value v we choose is 1.0. According to the formula, we can calculate:

[0134] K = 0.8*0.9 / 1.0 = 0.72.

[0135] This means that when driving in urban congestion, the scenario factor K calculated by our model is 0.72. This value is regarded as the comprehensive impact of the usage scenario on the temperature change efficiency. The larger the value, the higher the calculation accuracy of the scenario factor.

[0136] At S60: generating a modified charge and discharge suspension strategy according to the actual power consumption efficiency, wherein the modified charge and discharge suspension strategy includes a charge and discharge duration and a charge value for suspending charge and discharge. When the real-time charge of the lithium battery reaches the charge value for suspending charge and discharge, the charge and discharge operation is stopped;

[0137] In this step, the modified charge and discharge termination strategy also includes a buffer charge and discharge threshold, including the following steps:

[0138] S61: When the real-time power level of the battery reaches the buffer charge and discharge threshold, generating a charge and discharge buffer instruction, wherein the charge and discharge buffer instruction is used to shunt the charge and discharge of the battery;

[0139] S62: When responding to the charge and discharge buffer instruction, the preset buffer unit works and performs charge and discharge.

[0140] Specifically, when the real-time power in the charging process reaches the buffer charge and discharge threshold, the user-defined current is shunted to the buffer unit to reduce the charging efficiency of the battery, so that the rate at which the battery approaches full load is reduced, so as to facilitate the detection of whether the battery power has reached the full load state. In the embodiment of the present application, the user-defined current shunted to the buffer unit is 70%, and the remaining 30% is used for continued charging, thereby achieving the purpose of slowing down the charging efficiency of the battery;

[0141] When the buffer charge and discharge threshold is reached during the discharge process, the buffer unit discharges to provide a custom current, reducing the discharge of the battery and slowing down the rate at which the battery approaches no-load, making it easier to detect whether the battery has reached a no-load state.

[0142] The application of modified charge and discharge termination strategy and buffer charge and discharge threshold can more accurately control the battery charge and discharge process, avoid over-charge and discharge, extend battery life and improve safety. By shunting and adjusting the charge and discharge current, the rate at which the battery approaches full charge or no-load state can be reduced, improving the accurate monitoring of the battery status, helping to optimize battery management and improve the performance and reliability of the battery system.

[0143] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0144] In one embodiment, a lithium battery BMS board control device based on power detection protection is provided, and the lithium battery BMS board control device based on power detection protection corresponds to the lithium battery BMS board control method based on power detection protection in the above embodiment. Figure 6 As shown, the lithium battery BMS board control device based on power detection protection includes an actual discharge efficiency calculation module, a deviation discharge efficiency calculation module, a temperature variable recording module, a self-discharge acquisition module, an actual power consumption efficiency calculation module, a modified charge and discharge suspension strategy generation module, a correlation database construction module, a temperature-working time correlation calculation module, a correlation verification module and an abnormal temperature data backup module. The functional modules are described in detail as follows:

[0145] The actual discharge efficiency calculation module 1 is used to obtain the real-time power of the lithium battery and calculate the actual discharge efficiency of the lithium battery according to the change in power. The actual discharge efficiency = (battery discharge capacity change / battery rated capacity) * 100%, wherein the battery discharge capacity change represents the energy actually released by the battery during a discharge process, and the battery rated capacity represents the design capacity of the battery;

[0146] Deviation discharge efficiency calculation module 2, used for calculating deviation discharge efficiency by comparing preset discharge efficiency with actual discharge efficiency, wherein deviation discharge efficiency = preset discharge efficiency - actual discharge efficiency, wherein the preset discharge efficiency is the expected discharge efficiency preset based on lithium battery design parameters;

[0147] The temperature variable recording module 3 is used to obtain the temperature change of the battery during charging and discharging, record the temperature variables of different charging and discharging time, and analyze the correlation between the temperature change and the working time of the lithium battery;

[0148] The self-discharge amount acquisition module 4 is used to obtain the self-discharge amount of the lithium battery at different temperatures, and to construct a temperature-self-discharge amount correlation relationship to analyze the self-discharge efficiency of the lithium battery at different temperatures;

[0149] The actual power consumption efficiency calculation module 5 is used to calculate the actual power consumption efficiency based on the actual discharge efficiency, the deviation discharge efficiency and the self-discharge efficiency, and the formula is: P1=P2-P3, wherein P1 is the actual power consumption efficiency, P2 is the actual discharge efficiency, and P3 is the self-discharge efficiency;

[0150] A modified charge and discharge suspension strategy generating module 6 is used to generate a modified charge and discharge suspension strategy according to the actual power consumption efficiency, wherein the modified charge and discharge suspension strategy includes a charge and discharge duration and a charge value for suspending charge and discharge. When the real-time charge of the lithium battery reaches the charge value for suspending charge and discharge, the charge and discharge operation is stopped;

[0151] The associated database construction module 7 is used to obtain the temperature data corresponding to different working hours of the battery and construct an associated database of temperature-working hours;

[0152] The temperature-working time correlation calculation module 8 is used to preset a temperature-working time correlation calculation model and calculate a temperature-working time correlation factor based on the temperature data in the temperature-working time correlation database;

[0153] The correlation verification module 9 is used to preset a correlation verification model and analyze the correlation between temperature and working time based on the temperature data of the temperature-working time correlation database. The correlation includes a linear relationship and a nonlinear relationship. Specifically, the calculation formula of the temperature-working time correlation coefficient is as follows:

[0154] The abnormal temperature data backup module 10 is used to back up the abnormal temperature data if ρ does not reach a preset reference value, then the temperature data is abnormal.

[0155] Specifically, in the embodiment of the present application, a buffer unit is provided, the signal end of the buffer unit is electrically connected to the modified charge and discharge suspension strategy generation module, the input end of the buffer unit is electrically connected to the charging input end of the battery, and the output end of the buffer unit is electrically connected to the discharge output end of the battery. Specifically, when the real-time power in the charging process reaches the buffer charge and discharge threshold, the customized current is shunted to the buffer unit to reduce the charging efficiency of the battery, so that the rate at which the battery approaches full load is reduced, so as to facilitate the detection of whether the power of the battery has reached the full load state;

[0156] When the real-time power during the discharge process reaches the buffer charge and discharge threshold, the buffer unit discharges to provide a custom current, reducing the discharge of the battery and slowing down the rate at which the battery approaches no-load, making it easier to detect whether the battery power has reached the no-load state.

[0157] For the specific definition of a lithium battery BMS board control device based on power detection protection, please refer to the definition of the lithium battery BMS board control method based on power detection protection mentioned above, which will not be repeated here. Each module in the above-mentioned lithium battery BMS board control device based on power detection protection can be implemented in whole or in part through software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the electronic device in the form of hardware, or can be stored in the memory of the electronic device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0158] In one embodiment, an electronic device is provided. The electronic device may be a server, and its internal structure diagram may be as follows: Figure 7As shown. The electronic device includes a processor, a memory, a network interface and a database connected via a system bus. Among them, the processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the electronic device is used to store a database. The network interface of the electronic device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a lithium battery BMS board control method based on power detection protection is implemented.

[0159] In one embodiment, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program:

[0160] Obtain the real-time power of the lithium battery, and calculate the actual discharge efficiency of the lithium battery according to the change in power, the actual discharge efficiency = (battery discharge capacity change / battery rated capacity) * 100%, wherein the battery discharge capacity change represents the energy actually released by the battery during a discharge process, and the battery rated capacity represents the design capacity of the battery;

[0161] Compare the preset discharge efficiency with the actual discharge efficiency to calculate the deviation discharge efficiency, wherein the deviation discharge efficiency = the preset discharge efficiency - the actual discharge efficiency, wherein the preset discharge efficiency is the expected discharge efficiency preset based on the lithium battery design parameters;

[0162] Obtain the temperature changes of the battery during charging and discharging, record the temperature variables at different charging and discharging times, and analyze the correlation between temperature changes and lithium battery working time;

[0163] Obtain the self-discharge amount of lithium batteries at different temperatures, and build the correlation between temperature and self-discharge amount to analyze the self-discharge efficiency of lithium batteries at different temperatures;

[0164] The actual power consumption efficiency is calculated based on the actual discharge efficiency, the deviation discharge efficiency and the self-discharge efficiency, and the formula is: P1=P2-P3, wherein P1 is the actual power consumption efficiency, P2 is the actual discharge efficiency, and P3 is the self-discharge efficiency;

[0165] A modified charge and discharge suspension strategy is generated according to the actual power consumption efficiency. The modified charge and discharge suspension strategy includes the charge and discharge duration and the charge and discharge suspension power value. When the real-time power of the lithium battery reaches the charge and discharge suspension power value, the charge and discharge operation is stopped.

[0166] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0167] Obtain the real-time power of the lithium battery, and calculate the actual discharge efficiency of the lithium battery according to the change in power, the actual discharge efficiency = (battery discharge capacity change / battery rated capacity) * 100%, wherein the battery discharge capacity change represents the energy actually released by the battery during a discharge process, and the battery rated capacity represents the design capacity of the battery;

[0168] Compare the preset discharge efficiency with the actual discharge efficiency to calculate the deviation discharge efficiency, wherein the deviation discharge efficiency = the preset discharge efficiency - the actual discharge efficiency, wherein the preset discharge efficiency is the expected discharge efficiency preset based on the lithium battery design parameters;

[0169] Obtain the temperature changes of the battery during charging and discharging, record the temperature variables at different charging and discharging times, and analyze the correlation between temperature changes and lithium battery working time;

[0170] Obtain the self-discharge amount of lithium batteries at different temperatures, and build the correlation between temperature and self-discharge amount to analyze the self-discharge efficiency of lithium batteries at different temperatures;

[0171] The actual power consumption efficiency is calculated based on the actual discharge efficiency, the deviation discharge efficiency and the self-discharge efficiency, and the formula is: P1=P2-P3, wherein P1 is the actual power consumption efficiency, P2 is the actual discharge efficiency, and P3 is the self-discharge efficiency;

[0172] A modified charge and discharge suspension strategy is generated according to the actual power consumption efficiency. The modified charge and discharge suspension strategy includes the charge and discharge duration and the charge and discharge suspension power value. When the real-time power of the lithium battery reaches the charge and discharge suspension power value, the charge and discharge operation is stopped.

[0173] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synch link) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0174] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0175] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A lithium battery BMS board control method based on power detection protection, characterized in that: The method comprises the steps of: Obtain the real-time power of the lithium battery, and calculate the actual discharge efficiency of the lithium battery according to the change in power, the actual discharge efficiency = (battery discharge capacity change / battery rated capacity) * 100%, wherein the battery discharge capacity change represents the energy actually released by the battery during a discharge process, and the battery rated capacity represents the design capacity of the battery; Compare the preset discharge efficiency with the actual discharge efficiency to calculate the deviation discharge efficiency, wherein the deviation discharge efficiency = the preset discharge efficiency - the actual discharge efficiency, wherein the preset discharge efficiency is the expected discharge efficiency preset based on the lithium battery design parameters; Obtain the temperature changes of the battery during charging and discharging, record the temperature variables at different charging and discharging times, and analyze the correlation between temperature changes and lithium battery working time; Obtain the self-discharge amount of lithium batteries at different temperatures, and build the correlation between temperature and self-discharge amount to analyze the self-discharge efficiency of lithium batteries at different temperatures; The actual power consumption efficiency is calculated based on the actual discharge efficiency, the deviation discharge efficiency and the self-discharge efficiency, and the formula is: P1=P2-P3, wherein P1 is the actual power consumption efficiency, P2 is the actual discharge efficiency, and P3 is the self-discharge efficiency; Generate a modified charge and discharge suspension strategy according to the actual power consumption efficiency, wherein the modified charge and discharge suspension strategy includes a charge and discharge duration and a charge value for suspending charge and discharge, and when the real-time charge of the lithium battery reaches the charge value for suspending charge and discharge, the charge and discharge operation is stopped; Specifically, in the step of obtaining the temperature change of the battery during charging and discharging, recording the temperature variables of different charging and discharging durations, and analyzing the correlation between the temperature change and the working duration of the lithium battery, the steps are as follows: Obtain the temperature data corresponding to different working hours of the battery and build a temperature-working hour correlation database; The preset temperature-working time correlation calculation model calculates the temperature-working time correlation factor based on the temperature data in the temperature-working time correlation database; The preset correlation verification model analyzes the correlation between temperature and working time based on the temperature data of the temperature-working time correlation database, and the correlation includes a linear relationship and a nonlinear relationship. Specifically, the calculation formula of the temperature-working time correlation coefficient is as follows: Where, T is the temperature and t is the working time; If ρ does not reach the preset reference value, the temperature data is abnormal, and the abnormal temperature data is backed up.

2. A lithium battery BMS board control method based on power detection protection according to claim 1, characterized in that: After obtaining the temperature change of the battery during charging and discharging, recording the temperature variables of different charging and discharging durations, and analyzing the correlation between the temperature change and the working duration of the lithium battery, the following steps are included: Acquire ambient temperature data and ambient humidity data, and input the ambient temperature data and ambient humidity data into a preset usage scenario database, and define different ambient temperature data and ambient humidity data in the usage scenario database as different usage scenarios; The temperature change efficiency corresponding to different usage scenarios is obtained, and the usage scenario is associated with the temperature change efficiency, and a scene factor K corresponding to the usage scenario is generated, wherein the scene factor K is used to represent the influence of the ambient temperature data and the ambient humidity data on the temperature change efficiency.

3. A lithium battery BMS board control method based on power detection protection according to claim 2, characterized in that: The step of obtaining the temperature change efficiency corresponding to different usage scenarios, associating the usage scenarios with the temperature change efficiency, and generating the scenario factor K corresponding to the usage scenarios includes the following steps: Acquire location data and usage time data when the battery is working, and associate the location data and the usage time data with the usage scenario; Building a usage scenario portrait based on the location data and the usage time data, and associating the usage scenario with the usage scenario portrait; Analyzing the location data based on the temperature change efficiency of the usage scenario to generate a location scenario factor d related to the location data; Analyzing the usage time based on the temperature change efficiency of the usage scenario to generate a usage time factor x related to the usage time; The scene factor K is calculated based on the location scene factor d and the usage time factor x. Specifically, the scene factor K=d*x / v, wherein v is a preset reference value. The larger the value of K, the higher the calculation accuracy of the scene factor.

4. A lithium battery BMS board control method based on power detection protection according to claim 1, characterized in that: Before obtaining the real-time power of the lithium battery and calculating the actual discharge efficiency of the lithium battery according to the power change, the actual discharge efficiency = (battery discharge capacity change / battery rated capacity) * 100%, wherein the battery discharge capacity change represents the energy actually released by the battery during a discharge process, and the battery rated capacity represents the battery design capacity, the following steps are included: Record the number of times the lithium battery is charged and discharged as n, detect the real-time power of the battery and determine whether it has reached the maximum power; If the real-time power of the battery reaches the maximum power, the real-time terminal voltage OCV of the battery is obtained, and the real-time terminal voltage OCV at this time is used as the actual maximum terminal voltage; Calculating the battery loss rate m based on the actual maximum terminal voltage. Specifically, the calculation formula of the battery loss rate is: m=OCV / U0, where m is the battery loss rate, OCV is the actual maximum terminal voltage, and U0 is the rated terminal voltage of the battery; Based on the battery loss rate and the charge and discharge times, a charge and discharge times-battery loss rate correlation curve is established, wherein the charge and discharge times-battery loss rate correlation curve is used to calculate the battery loss caused by battery charging and discharging; The actual maximum power of the battery is obtained based on the charge and discharge times-battery loss rate correlation curve, and the actual maximum power is used to calibrate the actual battery capacity of the battery.

5. A lithium battery BMS board control method based on power detection protection according to claim 4, characterized in that: In the step of generating a modified charge and discharge suspension strategy according to the actual power consumption efficiency, the modified charge and discharge suspension strategy includes the charge and discharge duration and the power value for suspending charge and discharge. When the real-time power of the lithium battery reaches the power value for suspending charge and discharge, the charge and discharge operation is stopped. The modified charge and discharge suspension strategy also includes a buffer charge and discharge threshold, including the following steps: When the real-time power level of the battery reaches the buffer charge and discharge threshold, a charge and discharge buffer instruction is generated, wherein the charge and discharge buffer instruction is used to shunt the charge and discharge of the battery; When responding to the charge and discharge buffer instruction, the preset buffer unit works and performs charge and discharge. Specifically, when the real-time power in the charging process reaches the buffer charge and discharge threshold, the user-defined current is diverted to the buffer unit to reduce the charging efficiency of the battery, so that the rate at which the battery approaches full load is reduced, which is convenient for detecting whether the battery power has reached the full load state; When the real-time power during the discharge process reaches the buffer charge and discharge threshold, the buffer unit discharges to provide a custom current, reducing the discharge of the battery and slowing down the rate at which the battery approaches no-load, making it easier to detect whether the battery power has reached the no-load state.

6. A lithium battery BMS board control device based on power detection protection, applied to a lithium battery BMS board control method based on power detection protection according to any one of claims 1 to 5, characterized in that: The device comprises: The actual discharge efficiency calculation module (1) is used to obtain the real-time power of the lithium battery and calculate the actual discharge efficiency of the lithium battery according to the change of power, the actual discharge efficiency = (battery discharge capacity change / battery rated capacity) * 100%, wherein the battery discharge capacity change represents the energy actually released by the battery during a discharge process, and the battery rated capacity represents the design capacity of the battery; A deviation discharge efficiency calculation module (2) is used to compare a preset discharge efficiency with an actual discharge efficiency to calculate a deviation discharge efficiency, wherein the deviation discharge efficiency = the preset discharge efficiency - the actual discharge efficiency, wherein the preset discharge efficiency is an expected discharge efficiency preset based on the lithium battery design parameters; A temperature variable recording module (3) is used to obtain the temperature change of the battery during charging and discharging, record the temperature variables of different charging and discharging durations, and analyze the correlation between the temperature change and the working duration of the lithium battery; A self-discharge amount acquisition module (4) is used to acquire the self-discharge amount of the lithium battery at different temperatures, and to construct a temperature-self-discharge amount correlation relationship to analyze the self-discharge efficiency of the lithium battery at different temperatures; an actual power consumption efficiency calculation module (5), used for calculating the actual power consumption efficiency based on the actual discharge efficiency, the deviation discharge efficiency and the self-discharge efficiency, the formula being: P1=P2-P3, wherein P1 is the actual power consumption efficiency, P2 is the actual discharge efficiency, and P3 is the self-discharge efficiency; A modified charge and discharge suspension strategy generation module (6) is used to generate a modified charge and discharge suspension strategy according to the actual power consumption efficiency, wherein the modified charge and discharge suspension strategy includes a charge and discharge duration and a charge value for suspending charge and discharge, and when the real-time charge of the lithium battery reaches the charge value for suspending charge and discharge, the charge and discharge operation is stopped; A correlation database construction module (7), used to obtain temperature data corresponding to different working hours of the battery and construct a temperature-working hour correlation database; A temperature-working time correlation calculation module (8), used for presetting a temperature-working time correlation calculation model and calculating a temperature-working time correlation factor based on temperature data in the temperature-working time correlation database; The correlation verification module (9) is used to preset a correlation verification model and analyze the correlation between temperature and working time based on the temperature data in the temperature-working time correlation database, wherein the correlation includes a linear relationship and a nonlinear relationship. Specifically, the calculation formula of the temperature-working time correlation coefficient is as follows: Where, T is the temperature and t is the working time; The abnormal temperature data backup module (10) is used to determine that the temperature data is abnormal if ρ does not reach a preset reference value, and to back up the abnormal temperature data.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of a lithium battery BMS board control method based on power detection protection as described in any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by the processor, the steps of a lithium battery BMS board control method based on power detection protection as described in any one of claims 1 to 5 are implemented.

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