A method, apparatus, device and medium for evaluating battery state of health

Abstract

The application discloses a battery state of health evaluation method, device, equipment and medium, and relates to the field of automobile electronics, and the method comprises the following steps: acquiring the real-time running state of a battery pack to be detected; determining the change rate of the battery pack to be detected in a first time scale and the change rate in a second time scale; respectively determining a current difference index, a voltage difference index and a power difference index according to the deviation degree between the same change rates; and compensating the battery state of health by using the real-time current change rate, the real-time voltage change rate and the real-time power change rate to obtain the compensated battery state of health of the battery pack to be detected. The application describes the battery state from three aspects of external load change, battery internal response and overall energy change, and improves the accuracy and robustness of SOH evaluation under complex dynamic working conditions and high-noise environments.

Description

Technical Field

[0001] This invention relates to the field of automotive electronics, and more specifically to a method, apparatus, device, and medium for assessing battery health status. Background Technology

[0002] In a battery management system (BMS), the state of health (SOH) characterizes the degree of battery performance degradation and is an important indicator affecting BMS life assessment, range capability, power capability analysis, and safety control strategies.

[0003] Currently, commonly used SOH (State of Health) assessment methods in BMS mainly fall into three categories: the first is the capacity decay-based estimation method, which determines SOH based on the ratio of the battery's current usable capacity to its nominal capacity; the second is the internal resistance growth-based identification method, which determines SOH based on the degree of increase in the battery's internal resistance relative to its initial internal resistance; and the third is the rule-based method based on voltage difference or voltage characteristics, which calculates SOH according to preset rules based on characteristic quantities such as voltage difference and voltage plateau during charging and discharging. However, the operating state of the battery pack varies greatly under different vehicle usage scenarios. Since the above-mentioned SOH assessment methods all rely on single or low-dimensional static characteristic quantities (such as capacity, internal resistance, or a single voltage characteristic quantity), they all suffer from insufficient assessment accuracy and stability under complex dynamic operating conditions.

[0004] Therefore, how to provide a SOH assessment method that can adapt to the dynamic operating conditions of vehicle load and improve the accuracy and robustness of battery health status assessment is an important issue that the industry urgently needs to address. Summary of the Invention

[0005] In view of this, embodiments of the present invention provide a method, apparatus, device and medium for assessing battery health status, thereby solving the problem that existing SOH assessment methods based on single or low-dimensional static characteristics are insufficient in terms of accuracy and stability under complex dynamic operating conditions.

[0006] According to a first aspect, embodiments of the present invention provide a method for assessing the health status of a battery, the method comprising: Obtain the real-time operating status of the battery pack under test; the real-time operating status includes real-time battery voltage, battery current, and battery temperature; Based on the battery voltage and battery current, the first current change rate, the first voltage change rate, and the first power change rate of the battery pack under test are determined at the first time scale, and the second current change rate, the second voltage change rate, and the second power change rate of the battery pack under test are determined at the second time scale. Based on the degree of deviation between the same rate of change, the current difference index, voltage difference index, and power difference index are determined respectively. The first and second current change rates are processed based on the current difference index to obtain the real-time current change rate. The first and second voltage change rates are processed based on the voltage difference index to obtain the real-time voltage change rate; The first and second power change rates are processed based on the power difference index to obtain the real-time power change rate; The battery health status is compensated by real-time current change rate, real-time voltage change rate, and real-time power change rate to obtain the compensated battery health status of the battery pack under test.

[0007] In conjunction with the first aspect, and in the first embodiment of the first aspect, the method of compensating for the battery health state using real-time current change rate, real-time voltage change rate, and real-time power change rate to obtain the compensated battery health state of the battery pack under test specifically includes: The real-time current change rate is normalized based on the preset current change rate reference value to obtain the current change rate characteristics. The real-time voltage change rate is normalized based on a preset voltage change rate reference value to obtain the voltage change rate characteristics. The real-time power change rate is normalized based on the preset power change rate reference value to obtain the power change rate characteristics. The real-time battery health status of the battery pack under test is determined based on the real-time operating status, and the real-time battery health status is compensated based on the battery temperature to obtain the basic battery health status of the battery pack under test. The health status of the base battery is compensated by using the characteristics of current change rate, voltage change rate, and power change rate to obtain the compensated battery health status.

[0008] In conjunction with the first embodiment of the first aspect, in the second embodiment of the first aspect, the formula for calculating the compensated battery health state is: ; in, Indicates the battery health status after compensation; Indicates the basic battery health status; Indicates the first weighting coefficient; Indicates the characteristic of the rate of change of current; This represents the second weighting coefficient; Indicates the characteristic of voltage change rate; Indicates the third weighting coefficient; This indicates the characteristic of the rate of change of power.

[0009] In conjunction with the first aspect, in the third embodiment of the first aspect, the formula for calculating the current difference index is: ; The formula for calculating the voltage difference index is: ; The formula for calculating the power difference index is: ; in, Indicates the current difference index; Indicates the first rate of change of current; Indicates the rate of change of the second current; Indicates the first stabilizing factor; Indicates voltage difference index; Indicates the second stabilizing factor; Indicates the first rate of change of voltage; Indicates the second voltage change rate; Indicates power difference index; Indicates the third stability factor; Indicates the first power change rate; This represents the second power change rate.

[0010] In conjunction with the first aspect, in the fourth embodiment of the first aspect, the step of processing the first and second current change rates according to the current difference index to obtain the real-time current change rate specifically includes: Divide the current difference index by the sum of the current difference index and 1 to obtain the first fusion weight; Assign a first fusion weight to the first current change rate, and perform weighted fusion on the first and second current change rates to obtain the real-time current change rate.

[0011] In conjunction with the first aspect, in the fifth embodiment of the first aspect, the step of processing the first and second voltage change rates according to the voltage difference index to obtain the real-time voltage change rate specifically includes: Divide the voltage difference index by the sum of the voltage difference index and 1 to obtain the second fusion weight; The first voltage change rate is assigned a second fusion weight, and the first and second voltage change rates are weighted and fused to obtain the real-time voltage change rate.

[0012] In conjunction with the first aspect, in the sixth embodiment of the first aspect, the step of processing the first and second power change rates according to the power difference index to obtain the real-time power change rate specifically includes: Divide the power difference index by the sum of the power difference index and 1 to obtain the third fusion weight; The first power change rate is assigned a third fusion weight, and the first and second power change rates are weighted and fused to obtain the real-time power change rate.

[0013] According to a second aspect, embodiments of the present invention also provide a battery health status assessment device, the device comprising: The data acquisition module is used to acquire the real-time operating status of the battery pack under test; the real-time operating status includes real-time battery voltage, battery current and battery temperature; The parameter calculation module is used to determine the first current change rate, the first voltage change rate, and the first power change rate of the battery pack under test at the first time scale, and the second current change rate, the second voltage change rate, and the second power change rate of the battery pack under test at the second time scale, based on the battery voltage and the battery current. The difference determination module is used to determine the current difference index, voltage difference index, and power difference index respectively based on the degree of deviation between the same rate of change. The first fusion module is used to process the first and second current change rates according to the current difference index to obtain the real-time current change rate. The second fusion module is used to process the first and second voltage change rates according to the voltage difference index to obtain the real-time voltage change rate. The third fusion module is used to process the first and second power change rates according to the power difference index to obtain the real-time power change rate; The battery evaluation module is used to compensate for the battery health status using real-time current change rate, real-time voltage change rate, and real-time power change rate, so as to obtain the compensated battery health status of the battery pack under test.

[0014] According to a third aspect, embodiments of the present invention also provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the battery health status assessment method as described above.

[0015] According to a fourth aspect, embodiments of the present invention also provide a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the battery health status assessment method as described above.

[0016] The battery health status assessment method, apparatus, device, and medium of the present invention, by determining the first current change rate, first voltage change rate, and first power change rate of the battery pack under test at a first time scale, and the second current change rate, second voltage change rate, and second power change rate of the battery pack under test at a second time scale, respectively, can describe the battery state from three levels: external load change, internal battery response, and overall energy change. This differs from relying solely on single or low-dimensional static feature quantities to assess SOH, improving the feature dimensions and information expression capabilities used for SOH assessment. Furthermore, the change rate at the first time scale can capture the battery's transient dynamic response, and the change rate at the second time scale can characterize the battery's change trend and suppress noise, thereby resolving the contradiction between rapid response and noise resistance stability within a single time window. By determining the degree of deviation between the same change rates, the current difference index and the power difference index are obtained. The system calculates the voltage and power difference indices, and then determines the real-time rate of change based on these indices. When a difference index increases, the fusion result automatically shifts towards the rate of change at the first time scale, enhancing the response to transient shocks and strong dynamic disturbances. Conversely, when a difference index decreases, the fusion result automatically shifts towards the rate of change at the second time scale, enhancing noise suppression. This eliminates the need for manual weight adjustments for different battery types and operating conditions, achieving online self-balancing between dynamic response speed and noise resistance stability. This helps improve the accuracy and robustness of SOH assessment in complex dynamic conditions and high-noise environments. Finally, the real-time current, voltage, and power change rates are used to compensate for the battery health status, resulting in a compensated battery health status that promptly reflects the degradation of the battery's dynamic response capability. Attached Figure Description

[0017] The features and advantages of the invention will be more clearly understood by referring to the accompanying drawings, which are schematic and should not be construed as limiting the invention in any way. In the drawings: Figure 1 A flowchart illustrating the battery health status assessment method provided by the present invention is shown. Figure 2 A schematic diagram of the structure of the battery health status assessment device provided by the present invention is shown; Figure 3 A schematic diagram of the hardware structure of the electronic device provided in an embodiment of this application is shown. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] In a battery management system (BMS), the state of battery (SOH) is used to characterize the degree of battery performance degradation and is an important indicator affecting BMS life assessment, range capability, power capability analysis, and safety control strategies.

[0020] Currently, commonly used SOH (State of Health) assessment methods in BMS mainly fall into three categories: the first is the capacity decay-based estimation method, which determines SOH based on the ratio of the battery's current usable capacity to its nominal capacity; the second is the internal resistance growth-based identification method, which determines SOH based on the degree of increase in the battery's internal resistance relative to its initial internal resistance; and the third is the rule-based method based on voltage difference or voltage characteristics, which calculates SOH according to preset rules based on characteristic quantities such as voltage difference and voltage plateau during charging and discharging. However, the operating state of the battery pack varies greatly under different vehicle usage scenarios. Since the above-mentioned SOH assessment methods all rely on single or low-dimensional static characteristic quantities (such as capacity, internal resistance, or a single voltage characteristic quantity), they all have significant limitations under complex dynamic operating conditions.

[0021] Specifically, under dynamic conditions such as vehicle start-up, rapid acceleration, regenerative braking, and high-power charging at low temperatures, the battery pack's current, voltage, and power change rates fluctuate dramatically. The battery pack's true dynamic response capability is contained within the changes in these physical quantities over time. However, the aforementioned State of Health (SOH) assessment methods, relying only on single or low-dimensional static features, cannot capture these dynamic behavioral characteristics and therefore fail to reflect the battery's dynamic response capability. Furthermore, fixed weighting coefficients cannot adapt to the diverse operating conditions: under stable conditions, fixed weights are insufficient to suppress sampling noise interference, leading to fluctuating SOH estimates or even misjudgments; under highly dynamic conditions, fixed weights cannot keep pace with the degradation of battery dynamic response capability, failing to dynamically adapt to different battery types, aging stages, and operating conditions, resulting in SOH assessment results lagging behind the battery's true aging state.

[0022] Meanwhile, battery pack behavior exhibits both short-term dynamic response and long-term variation trends. None of the aforementioned SOH assessment methods differentiate and model the physical characteristics at different time scales, leading to unstable estimation results under dynamic operating conditions or high-noise environments, which can easily result in misjudgments.

[0023] In summary, how to provide a SOH assessment method that can adapt to the dynamic operating conditions of vehicle load and improve the accuracy and robustness of battery health status assessment is an important issue that the industry urgently needs to address.

[0024] To address the aforementioned issues, this specification provides a method for assessing battery health status, aiming to describe battery condition from three perspectives: external load changes, internal battery response, and overall energy changes. This improves the accuracy and robustness of SOH (State of Health) assessment under complex dynamic operating conditions and high-noise environments. The battery health status assessment method provided in this specification can be applied to electronic devices, including laptops, desktop computers, smartphones, smart wearable devices, and tablets. Furthermore, the battery health status assessment method provided in this specification can also be applied to applications running on the aforementioned electronic devices. Figure 1 This is a flowchart illustrating a battery health status assessment method according to an embodiment of the present invention, as shown below. Figure 1 As shown, the method may include the following steps: S101. Obtain the real-time operating status of the battery pack to be tested. The real-time operating status includes the real-time battery voltage, battery current, and battery temperature.

[0025] In this embodiment of the application, the BMS can collect information such as battery voltage, battery current and battery temperature of the battery pack in real time at a fixed frequency (fixed frequency, for example, 1kHz-5kHz, corresponding to a sampling period of 1ms-0.2ms) as the real-time operating status.

[0026] S102. Based on the battery voltage and battery current, determine the first rate of change of current, the first rate of change of voltage, and the first rate of change of power of the battery pack under test at the first time scale, and the second rate of change of current, the second rate of change of voltage, and the second rate of change of power of the battery pack under test at the second time scale. The time window corresponding to the first time scale is shorter than the time window corresponding to the second time scale.

[0027] Specifically, the formulas for calculating each of the above rates of change are as follows: ; ; ; ; ; ; in, Indicates the first rate of change of current; Indicates in Battery current at any given moment; Indicates the first time scale; Indicates the first rate of change of voltage; Indicates in Battery voltage at any given moment; Indicates the first power change rate; Indicates in The battery power at any given time, and ; Indicates the rate of change of the second current; Indicates the second time scale; Indicates the second voltage change rate; This represents the second power change rate.

[0028] In this embodiment, the first time scale is a short time scale relative to the second time scale. The first current change rate, the first voltage change rate, and the first power change rate under the first time scale are used to capture transient dynamic changes and characterize the transient dynamic response characteristics of the BMS. Correspondingly, the second time scale is a long time scale relative to the first time scale. The second current change rate, the second voltage change rate, and the second power change rate under the second time scale are used to characterize trend changes or steady-state characteristics and characterize the historical behavior or inertia of the BMS.

[0029] Preferably, the first time scale is between 10-40 ms, and the second time scale is between 200-1000 ms. Simultaneously, the two time scales must satisfy the scale separation characteristic, meaning the value of the second time scale must be at least 5 times that of the first time scale, thereby ensuring a significant difference in the rate of change between different time scales and effectively characterizing the dynamic behavior of the battery pack under test.

[0030] In this embodiment, both the first and second current change rates are used to characterize the rate of change of load current, reflecting the degree of dynamic response of the battery. The higher the degree of battery aging, the smaller the state of equilibrium (SOH), the greater the fluctuation of current response, and the worse the dynamic characteristics of the system. The first current change rate can be used to characterize the current load change of the battery pack under test, while the second current change rate can be used to characterize the load change trend of the battery pack under test.

[0031] Both the first and second voltage change rates are used to characterize the rate of change of battery terminal voltage, reflecting the battery's internal resistance and polarization characteristics. The higher the degree of battery aging, the lower the state of equilibrium (SOH), the greater the battery's internal resistance, and the more drastic the voltage fluctuations. The first voltage change rate can be used to characterize the immediate response of the battery pack under test, while the second voltage change rate can be used to characterize the battery state trend of the battery pack under test.

[0032] Both the first and second power change rates are used to characterize the rate of energy change in the BMS, combining voltage and current characteristics. The higher the battery aging level, the smaller the state of energy (SOH), and the lower the power response capability, indicating lag or abnormal changes. The first power change rate can be used to characterize the intensity of energy change in the battery pack under test, while the second power change rate can be used to characterize the trend of energy change in the battery pack under test.

[0033] That is, the first current change rate, the first voltage change rate, and the first power change rate of the battery pack under test at a preset first time scale are used to reflect the transient dynamic response characteristics of the BMS and characterize the intensity of the current load change of the battery pack under test. The second current change rate, the second voltage change rate, and the second power change rate of the battery pack under test at a preset second time scale are used to reflect the trend change and stability characteristics of the BMS and serve as a reference baseline for the dynamic changes of the battery pack under test.

[0034] It should be noted that if a BMS is to have a fast response, it needs to use a shorter time window to calculate the three rates of change of current, voltage, and power. However, the current, voltage, and power calculated in a shorter time window are sensitive to sampling jitter and are easily mixed with large noise. If a BMS is to have noise immunity and stability, it needs to use a longer time window to calculate the three rates of change of current, voltage, and power. However, the current, voltage, and power calculated in a longer time window have a delayed response and cannot capture sudden changes.

[0035] In this embodiment, by pre-setting a first and a second time scale, and respectively determining the first current change rate, the first voltage change rate, and the first power change rate of the battery pack under test at the preset first time scale, and the second current change rate, the second voltage change rate, and the second power change rate of the battery pack under test at the preset second time scale, the contradiction between response speed and noise resistance stability of a single time scale is effectively resolved. By using the difference between the change rates at different time scales, the dynamic behavior characteristics of the signal are characterized, enabling effective differentiation between transient changes and trend changes, and providing dynamic operating condition characterization variables for subsequent adaptive fusion and parameter adjustment, thereby improving the accuracy and robustness of SOH evaluation.

[0036] By combining the above multiple rate-of-change parameters and multiple time scales, the battery state can be described from three levels: external load change (battery current), battery internal response (battery voltage), and overall energy change (battery power), providing rich and physically meaningful feature inputs for subsequent SOH assessment.

[0037] In particular, a third to Nth time scale can be set that are different from both the first and second time scales. The value range of the third to Nth time scales exceeds that of the first time scale but does not exceed that of the second time scale. By using more time scales to describe the signal change characteristics through multiple time analysis windows, higher-precision dynamic modeling can be achieved.

[0038] S103. Based on the degree of deviation between the same rate of change, the current difference index, voltage difference index, and power difference index are determined respectively.

[0039] In step S103, the current difference index, voltage difference index, and power difference index are obtained based on the degree of deviation between the same type of change rate under the two time scales, that is, based on the degree of deviation between the first and second current change rate, the degree of deviation between the first and second voltage change rate, and the degree of deviation between the first and second power change rate.

[0040] Specifically, the calculation formulas for the above-mentioned difference indicators are as follows: ; ; ; in, Indicates the current difference index; This represents the first stability factor, which is also the current change rate stability factor. The unit is ampere per second. The smallest rate of change or noise level that the BMS can recognize, that is, the boundary between meaningful current changes and noise that the BMS can distinguish; Indicates voltage difference index; This represents the second stability factor, also known as the voltage change rate stability factor. The unit is volts per second. This is the minimum effective resolution scale or noise level for the rate of voltage change; Indicates power difference index; This represents the third stability factor, also known as the power change rate stability factor. The unit is watts per second. The minimum effective resolution used to characterize the rate of change of power in a BMS is also the noise floor for the rate of change of energy.

[0041] In the embodiments of this application, parameters The parameter is used to characterize the relative difference in the rate of change of current between a first time scale and a second time scale, and this relative difference is expressed as a multiple. It is also used to characterize the degree of deviation of the current transient load change of the BMS from the overall trend of change.

[0042] When parameter The smaller the value, the more stable the BMS operation, indicating that the short-term current change of the battery pack under test is basically consistent with the long-term trend; when the parameter... The larger the value, the more significant the short-term change in current deviates from the trend change, indicating that there is strong dynamic disturbance or transient impact in the BMS, thus reflecting the stronger fluctuation of the operating state of the battery pack under test.

[0043] parameter The value range is not lower than 0, for example, between 0 and 10.

[0044] Used to calculate parameters parameters Used to avoid parameters The calculation process addresses numerical instability caused by a denominator approaching zero and suppresses the amplification effect of noise on difference calculations under low dynamic conditions. Parameters Its value is preferably 1%-10% of the typical current change rate, and can be calibrated, for example, according to the BMS noise level. The value ranges from 2 to 5 A / s.

[0045] parameter Its value can also be adaptively determined based on the historical current data of the battery pack under test, thereby improving its adaptability to different operating conditions and different battery systems. For example, for energy storage systems, The value ranges from 1 to 3 A / s; for passenger vehicles, The value ranges from 2 to 5 A / s; this is for high-dynamic vehicles (such as racing cars). The value ranges from 5 to 10 A / s.

[0046] In the embodiments of this application, parameters The parameter is used to characterize the relative difference in the rate of change of voltage between a first time scale and a second time scale, and this relative difference is also presented in the form of a multiple. It is also used to characterize the degree of deviation of the transient response of battery voltage from the trend response, thereby reflecting the consistency and stability of the electrochemical state inside the battery pack under test.

[0047] When parameter The smaller the value, the more stable and consistent the voltage change of the battery pack under test is, indicating that the battery pack is in a stable operating state; when the parameter... A higher value indicates that the voltage transient response of the battery pack under test deviates significantly from the trend change, reflecting a strong polarization effect or internal resistance change in the battery, thus indicating that the SOH may decrease.

[0048] parameter The value range is also no less than 0, for example, between 0 and 3.

[0049] Used to calculate parameters parameters Used to avoid parameters The near-zero denominator leads to numerical instability, and this suppresses the amplification effect of noise on difference calculations under low dynamic conditions. Parameters Its value is affected by the voltage measurement accuracy, sampling period, and system noise characteristics, and is preferably 1%-10% of the typical voltage change rate, specifically a constant in the range of 0.001-0.01 V / s, for example... The value is 0.005 V / s.

[0050] parameter Its value can also be adaptively determined based on the historical voltage data of the battery pack under test, so as to improve the adaptability and stability under different operating conditions and different battery states.

[0051] In the embodiments of this application, parameters The parameter is used to characterize the relative difference in the rate of change of power between a first time scale and a second time scale, and this relative difference is expressed as a multiple. It is also used to characterize the degree of deviation of the transient response of battery energy changes from the trend change. Since power is the product of voltage and current, the parameters... It is used to reflect both external load changes and the battery's internal response characteristics.

[0052] When parameter When the value is small, it indicates that the energy change of the battery pack under test is stable and the response is consistent; when the parameter is small... A large value indicates that the energy change of the battery pack under test deviates significantly from the trend, and also indicates that the BMS has strong dynamic disturbances or abnormal energy response, thus reflecting that the SOH may have decreased.

[0053] parameter The value range is also no less than 0, for example, between 0 and 3.

[0054] Used to calculate parameters parameters This is used to avoid numerical instability caused by the rate of power change approaching zero on the second time scale. Parameter Its value is affected by factors such as current measurement noise, voltage measurement accuracy, system power level, and sampling period. It is preferably 1%-10% of the typical power change rate, specifically a constant within the range of 10-1000 W / s. The value ranges from 200 to 500 W / s.

[0055] parameter Its value can also be adaptively determined based on the historical power data of the battery pack under test, so as to improve the adaptability and stability under different operating conditions and different battery states.

[0056] S104. Process the first and second current change rates according to the current difference index to obtain the real-time current change rate.

[0057] In this embodiment of the application, the current difference index is first divided by the sum of the current difference index and 1 to obtain the first fusion weight. Then, the first current change rate is assigned the first fusion weight, and the first and second current change rates are weighted and fused to obtain the real-time current change rate.

[0058] It is understandable that in the weighted fusion process of the first and second current change rates, since the first current change rate is assigned a first fusion weight, the corresponding weight assigned to the second current change rate is 1 minus the first fusion weight.

[0059] S105. Process the first and second voltage change rates according to the voltage difference index to obtain the real-time voltage change rate.

[0060] In this embodiment, the voltage difference index is first divided by the sum of the voltage difference index and 1 to obtain the second fusion weight. Then, the first voltage change rate is assigned the second fusion weight, and the first and second voltage change rates are weighted and fused to obtain the real-time voltage change rate.

[0061] It is understandable that in the weighted fusion process of the first and second voltage change rates, since the first voltage change rate is assigned a second fusion weight, the corresponding weight assigned to the second voltage change rate is 1 minus the second fusion weight.

[0062] S106. Process the first and second power change rates according to the power difference index to obtain the real-time power change rate.

[0063] In this embodiment of the application, the power difference index is first divided by the sum of the power difference index and 1 to obtain the third fusion weight. Then, the first power change rate is assigned the third fusion weight, and the first and second power change rates are weighted and fused to obtain the real-time power change rate.

[0064] It is understandable that in the weighted fusion process of the first and second power change rates, since the first power change rate is assigned a third fusion weight, the corresponding weight assigned to the second power change rate is 1 minus the third fusion weight.

[0065] Specifically, the formula for calculating the real-time current change rate is: ; ; ; in, Indicates the real-time rate of change of current; Indicates the first fusion weight; Indicates the real-time voltage change rate; Indicates the second fusion weight; Indicates the real-time power change rate; This represents the third fusion weight.

[0066] In the embodiments of this application, parameters The weighting factor describes whether the battery pack under test is currently more inclined towards a fast dynamic mode or a stable operating mode. ,and .

[0067] parameter Similarly, this is a weighting factor used to describe whether the battery pack under test is currently operating more in a fast dynamic mode or a stable operating mode. ,and .

[0068] parameter Similarly, this is a weighting factor used to describe whether the battery pack under test is currently operating more in a fast dynamic mode or a stable operating mode. ,and .

[0069] In this embodiment, when a certain difference index is small, it indicates that the battery pack under test is in a steady state or a slow change phase. In this case, the fusion weight of the rate of change corresponding to the first time scale should be reduced, and the fusion weight of the rate of change corresponding to the second time scale should be increased to enhance system stability. When a certain difference index is large, it indicates that the battery pack under test has obvious dynamic disturbances. In this case, the fusion weight of the rate of change corresponding to the first time scale should be increased, and the fusion weight of the rate of change corresponding to the second time scale should be reduced to enhance the system's dynamic response capability.

[0070] The smaller the values ​​of the three fusion weights mentioned above, such as close to or equal to 0, the more the BMS trusts the second time scale and requires extremely high stability; conversely, the larger the values ​​of the three fusion weights mentioned above, such as close to or equal to 1, the more the BMS trusts the first time scale and requires a fast response.

[0071] Through the weighted fusion in steps S104 to S106, the trust weights between transient and trend information are dynamically adjusted based on the determined difference indicators. This allows for a balance between response speed and stability under different operating conditions, achieving optimal estimation of the rate of change of multiple physical quantities. This further enables the BMS to achieve a dynamic balance between dynamic response (the time window corresponding to the first time scale) and noise resistance stability (the time window corresponding to the second time scale), resulting in a more accurate real-time rate of change estimate.

[0072] S107. The battery health status is compensated by real-time current change rate, real-time voltage change rate and real-time power change rate to obtain the compensated battery health status of the battery pack under test.

[0073] When the battery pack under test is in the early stage of aging and the dynamic response is normal, the real-time current change rate, real-time voltage change rate, and real-time power change rate are relatively small, and the compensation for the battery health status is also relatively small, so that the compensated battery health status is close to the basic battery health status. As the battery ages more, the fluctuation amplitude of current, voltage, and power under the same load impact increases, and the real-time current change rate, real-time voltage change rate, and real-time power change rate gradually increase. The compensation for the battery health status also increases accordingly, so that the compensated battery health status is corrected downward relative to the basic battery health status, thereby reflecting the degradation of the battery's dynamic response capability in a timely manner.

[0074] The battery health status assessment method of the present invention determines the first rate of change of current, the first rate of change of voltage, and the first rate of change of power of the battery pack under test at a first time scale, and the second rate of change of current, the second rate of change of voltage, and the second rate of change of power of the battery pack under test at a second time scale. This allows for the description of the battery state from three levels: external load change, internal battery response, and overall energy change. This differs from relying solely on single or low-dimensional static features for SOH assessment, improving the feature dimensionality and information expression capability for SOH assessment. Furthermore, the rate of change at the first time scale can capture the transient dynamic response of the battery, while the rate of change at the second time scale can characterize the battery's change trend and suppress noise, thus resolving the contradiction between rapid response and noise resistance stability within a single time window. By determining the degree of deviation between the same rate of change, current difference indicators and voltage difference indicators are obtained. The system calculates the power difference index and then determines the real-time rate of change based on each index. When a difference index increases, the fusion result automatically shifts towards the rate of change at the first time scale, enhancing the response to transient impacts and strong dynamic disturbances. Conversely, when a difference index decreases, the fusion result automatically shifts towards the rate of change at the second time scale, enhancing noise suppression. This eliminates the need for manual weight adjustments for different battery types and operating conditions, achieving online self-balancing between dynamic response speed and noise resistance stability. This helps improve the accuracy and robustness of SOH assessment in complex dynamic conditions and high-noise environments. Finally, the real-time current rate of change, real-time voltage rate of change, and real-time power rate of change are used to compensate for the battery health status, obtaining the compensated battery health status of the battery pack under test. This compensated battery health status can promptly reflect the degradation of the battery's dynamic response capability.

[0075] In this embodiment of the application, step S107 specifically includes: S1071. Normalize the real-time current change rate according to the preset current change rate reference value to obtain the current change rate characteristics.

[0076] Specifically, the formula for calculating the current change rate characteristic is: ; in, Indicates the characteristic of the rate of change of current; This indicates the reference value for the rate of change of current.

[0077] parameter A scale parameter used to characterize the typical maximum change level of the rate of change of current or the effective dynamic range. Its value ranges from 200 to 500 A / s. To preserve the main dynamic variation characteristics while suppressing the impact of individual outliers on SOH assessment, It can be determined based on the 95th percentile of historical data. For example, selecting the 95th percentile value within a recent period can cover 95% of the operating conditions within that period, thereby improving the stability and robustness of the normalization process.

[0078] S1072. Normalize the real-time voltage change rate according to the preset voltage change rate reference value to obtain the voltage change rate characteristics.

[0079] Specifically, the formula for calculating the voltage change rate characteristic is: ; in, Indicates the characteristic of voltage change rate; This indicates the reference value for the rate of change of voltage.

[0080] parameter A scale parameter used to characterize the typical maximum change level of the rate of voltage change or the effective dynamic range. Its value ranges from 0.5 to 10 V / s. Similarly, in order to retain the main dynamic change characteristics while suppressing the impact of individual outliers on the SOH assessment, It can be determined based on the 95th percentile of historical data. For example, selecting the 95th percentile value within a recent period can cover 95% of the operating conditions during that period, thereby improving the stability and robustness of the normalization process. For example, in energy storage systems... The value ranges from 0.5 to 2V / s for passenger vehicles. The value ranges from 1 to 5 V / s for high-dynamic vehicles. The value ranges from 5 to 10 V / s.

[0081] S1073. Normalize the real-time power change rate according to the preset power change rate reference value to obtain the power change rate characteristics.

[0082] Specifically, the formula for calculating the power change rate characteristic is: ; in, Indicates the characteristic of power change rate; This represents a reference value for the rate of change of power.

[0083] parameter A scale parameter used to characterize the typical maximum level of change in the rate of power change or the effective dynamic range. Its value ranges from 1 to 50 kW / s. Similarly, in order to suppress the impact of individual outliers on SOH assessment while retaining the main dynamic change characteristics, It can be determined based on the 95th percentile of historical data. For example, selecting the 95th percentile value within a recent period can cover 95% of the operating conditions during that period, thereby improving the stability and robustness of the normalization process. For example, in low-power systems... Values ​​range from 1-5 kW / s for passenger vehicles. Values ​​range from 5-15 kW / s, for high-performance vehicles. The value ranges from 10 to 50 kW / s.

[0084] In this embodiment, considering that the units of current change rate, voltage change rate, and power change rate are different, the change rates are normalized by their respective reference values. At the same time, each reference value is determined based on covering a typical dynamic range. This can convert each change rate into a unified dimensionless feature, providing a comparable basis for subsequent SOH compensation, thereby eliminating the influence of dimensional differences on the SOH fusion process.

[0085] S1074. Determine the real-time battery health status of the battery pack to be tested based on the real-time operating status, and compensate for the real-time battery health status based on the battery temperature to obtain the basic battery health status of the battery pack to be tested.

[0086] In this embodiment, the real-time State of Health (SOH) can be determined using the capacity decay method based on the real-time operating status. The capacity decay method calculates the capacity retention rate by comparing the current actual usable capacity of the battery pack with its nominal rated capacity, thereby obtaining the real-time SOH. By recording the cumulative ampere-hour data from each charge-discharge cycle, the current usable capacity is fitted to the data. Then, based on the nominal rated capacity of the battery pack at the time of manufacture, the current usable capacity is divided by the nominal rated capacity to obtain the real-time SOH.

[0087] Furthermore, considering the impact of battery temperature on usable capacity and aging process, the real-time battery health status is compensated based on battery temperature to obtain the basic battery health status of the battery pack under test. Compensation can be achieved using correction coefficients, correction functions, or lookup tables, converting the usable capacity measured at non-reference temperatures to the equivalent capacity at the reference temperature.

[0088] It should be noted that battery temperature is only used for estimating the basic battery health status and is not involved in the calculation of the rate of change, the calculation of the difference index, or the calculation of the final compensated battery health status. That is, temperature correction and rate of change fusion are two decoupled processes. By concentrating the impact of temperature in the basic battery health status process, the influence of temperature differences on SOH assessment is taken into account while maintaining the simplicity of the rate of change calculation. This avoids the scale mismatch between the slow variable of temperature and current and voltage interfering with the dynamic feature extraction.

[0089] S1075. The health status of the base battery is compensated by using the current change rate characteristics, voltage change rate characteristics, and power change rate characteristics to obtain the compensated battery health status.

[0090] Specifically, the formula for calculating the compensated battery health status is: ; in, Indicates the battery health status after compensation; Indicates the basic battery health status; Indicates the first weighting coefficient; This represents the second weighting coefficient; This represents the third weighting coefficient.

[0091] It should be noted that, That is, if the calculated result is If it is less than 0, then If the calculated value is 0, If it is greater than 1, then The value is 1.

[0092] In the embodiments of this application, parameters It is also a weighting coefficient for the rate of change of current, used to characterize the degree of impact of dynamic changes in external load on the battery's health status. (Parameter) The value range is between 0 and 1, for example Its value ranges from 0.2 to 0.4.

[0093] parameter It is also a weighting coefficient for the rate of voltage change, used to characterize the degree to which the battery's internal voltage response characteristics affect its health status. (Parameter) The value range is also between 0 and 1, for example... Its value ranges from 0.3 to 0.5.

[0094] parameter It is also a weighting coefficient for the rate of power change, used to characterize the comprehensive impact of system energy change behavior on SOH. (Parameter) The value range is also between 0 and 1, for example... Its value ranges from 0.2 to 0.4.

[0095] In the embodiments of this application, parameters This parameter usually plays a dominant role. This parameter is used to demonstrate the dominant role of voltage variation characteristics in battery health assessment. and These are used to characterize the auxiliary effects of load disturbances and energy changes on SOH, respectively. , ,and This can prevent parameters Overcorrection during the compensation process improves the stability of SOH assessment.

[0096] It should be noted that the parameters , , All parameters can be adaptively adjusted based on battery operating conditions or dynamic characteristic indicators to enhance the model's adaptability and robustness under different operating conditions. , , The impact of load excitation, battery internal response, and system energy behavior on SOH are characterized from three dimensions. These three factors work together to evaluate SOH using a multi-physical-quantitative fusion approach. Within a reasonable range, they work synergistically to achieve a stable and accurate assessment of battery health status.

[0097] The battery health status assessment device provided in the embodiments of the present invention will be described below. The battery health status assessment device and battery health status assessment method described below can be referred to in correspondence with each other.

[0098] To address the aforementioned issues, this specification provides a battery health status assessment device, designed to describe battery status from three perspectives: external load changes, internal battery response, and overall energy changes, thereby improving the accuracy and robustness of SOH assessment under complex dynamic operating conditions and high-noise environments. Figure 2 This is a schematic diagram of the structure of a battery health status assessment device according to an embodiment of the present invention, as shown below. Figure 2 As shown, the device may include: The data acquisition module 10 is used to acquire the real-time operating status of the battery pack under test. This real-time operating status includes real-time battery voltage, battery current, and battery temperature.

[0099] In this embodiment of the application, the BMS can collect information such as battery voltage, battery current and battery temperature of the battery pack in real time at a fixed frequency (fixed frequency, for example, 1kHz-5kHz, corresponding to a sampling period of 1ms-0.2ms) as the real-time operating status.

[0100] The parameter calculation module 20 is used to determine, based on the battery voltage and battery current, the first rate of change of current, the first rate of change of voltage, and the first rate of change of power of the battery pack under test at a first time scale, and the second rate of change of current, the second rate of change of voltage, and the second rate of change of power of the battery pack under test at a second time scale. The time window corresponding to the first time scale is smaller than the time window corresponding to the second time scale.

[0101] The difference determination module 30 is used to determine the current difference index, voltage difference index and power difference index respectively based on the degree of deviation between the same rate of change.

[0102] In this embodiment of the application, the current difference index, voltage difference index and power difference index are obtained based on the degree of deviation between the same type of change rate under two time scales, that is, based on the degree of deviation between the first and second current change rate, the degree of deviation between the first and second voltage change rate, and the degree of deviation between the first and second power change rate.

[0103] The first fusion module 40 is used to process the first and second current change rates according to the current difference index to obtain the real-time current change rate.

[0104] In this embodiment of the application, the current difference index is first divided by the sum of the current difference index and 1 to obtain the first fusion weight. Then, the first current change rate is assigned the first fusion weight, and the first and second current change rates are weighted and fused to obtain the real-time current change rate.

[0105] It is understandable that in the weighted fusion process of the first and second current change rates, since the first current change rate is assigned a first fusion weight, the corresponding weight assigned to the second current change rate is 1 minus the first fusion weight.

[0106] The second fusion module 50 is used to process the first and second voltage change rates according to the voltage difference index to obtain the real-time voltage change rate.

[0107] In this embodiment, the voltage difference index is first divided by the sum of the voltage difference index and 1 to obtain the second fusion weight. Then, the first voltage change rate is assigned the second fusion weight, and the first and second voltage change rates are weighted and fused to obtain the real-time voltage change rate.

[0108] It is understandable that in the weighted fusion process of the first and second voltage change rates, since the first voltage change rate is assigned a second fusion weight, the corresponding weight assigned to the second voltage change rate is 1 minus the second fusion weight.

[0109] The third fusion module 60 is used to process the first and second power change rates according to the power difference index to obtain the real-time power change rate.

[0110] In this embodiment of the application, the power difference index is first divided by the sum of the power difference index and 1 to obtain the third fusion weight. Then, the first power change rate is assigned the third fusion weight, and the first and second power change rates are weighted and fused to obtain the real-time power change rate.

[0111] It is understandable that in the weighted fusion process of the first and second power change rates, since the first power change rate is assigned a third fusion weight, the corresponding weight assigned to the second power change rate is 1 minus the third fusion weight.

[0112] The battery evaluation module 70 is used to compensate for the battery health status using real-time current change rate, real-time voltage change rate and real-time power change rate, so as to obtain the compensated battery health status of the battery pack under test.

[0113] When the battery pack under test is in the early stage of aging and the dynamic response is normal, the real-time current change rate, real-time voltage change rate, and real-time power change rate are relatively small, and the compensation for the battery health status is also relatively small, so that the compensated battery health status is close to the basic battery health status. As the battery ages more, the fluctuation amplitude of current, voltage, and power under the same load impact increases, and the real-time current change rate, real-time voltage change rate, and real-time power change rate gradually increase. The compensation for the battery health status also increases accordingly, so that the compensated battery health status is corrected downward relative to the basic battery health status, thereby reflecting the degradation of the battery's dynamic response capability in a timely manner.

[0114] The battery health status assessment device of the present invention determines the first rate of change of current, the first rate of change of voltage, and the first rate of change of power of the battery pack under test at a first time scale, and the second rate of change of current, the second rate of change of voltage, and the second rate of change of power of the battery pack under test at a second time scale. This allows for the description of the battery state from three levels: external load change, internal battery response, and overall energy change. This differs from relying solely on single or low-dimensional static feature quantities for SOH assessment, improving the feature dimensions and information expression capabilities used for SOH assessment. Furthermore, the rate of change at the first time scale can capture the transient dynamic response of the battery, while the rate of change at the second time scale can characterize the battery's change trend and suppress noise, thus resolving the contradiction between rapid response and noise resistance stability within a single time window. By determining the degree of deviation between the same rate of change, current difference indicators and voltage difference indicators are obtained. The system calculates the power difference index and then determines the real-time rate of change based on each index. When a difference index increases, the fusion result automatically shifts towards the rate of change at the first time scale, enhancing the response to transient impacts and strong dynamic disturbances. Conversely, when a difference index decreases, the fusion result automatically shifts towards the rate of change at the second time scale, enhancing noise suppression. This eliminates the need for manual weight adjustments for different battery types and operating conditions, achieving online self-balancing between dynamic response speed and noise resistance stability. This helps improve the accuracy and robustness of SOH assessment in complex dynamic conditions and high-noise environments. Finally, the real-time current rate of change, real-time voltage rate of change, and real-time power rate of change are used to compensate for the battery health status, obtaining the compensated battery health status of the battery pack under test. This compensated battery health status can promptly reflect the degradation of the battery's dynamic response capability.

[0115] Figure 3 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 3 As shown, the electronic device may include: a processor 310, a communication interface 320, a memory 330, and a communication bus 340, wherein the processor 310, the communication interface 320, and the memory 330 communicate with each other via the communication bus 340. The processor 310 can call logical commands in the memory 330 to execute a battery health status assessment method, which includes: Obtain the real-time operating status of the battery pack under test; the real-time operating status includes real-time battery voltage, battery current, and battery temperature; Based on the battery voltage and battery current, the first current change rate, the first voltage change rate, and the first power change rate of the battery pack under test are determined at the first time scale, and the second current change rate, the second voltage change rate, and the second power change rate of the battery pack under test are determined at the second time scale. Based on the degree of deviation between the same rate of change, the current difference index, voltage difference index, and power difference index are determined respectively. The first and second current change rates are processed based on the current difference index to obtain the real-time current change rate. The first and second voltage change rates are processed based on the voltage difference index to obtain the real-time voltage change rate; The first and second power change rates are processed based on the power difference index to obtain the real-time power change rate; The battery health status is compensated by real-time current change rate, real-time voltage change rate, and real-time power change rate to obtain the compensated battery health status of the battery pack under test.

[0116] Furthermore, the logical instructions in the aforementioned memory 330 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0117] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the battery health status assessment method provided by the above methods, the method comprising: Obtain the real-time operating status of the battery pack under test; the real-time operating status includes real-time battery voltage, battery current, and battery temperature; Based on the battery voltage and battery current, the first current change rate, the first voltage change rate, and the first power change rate of the battery pack under test are determined at the first time scale, and the second current change rate, the second voltage change rate, and the second power change rate of the battery pack under test are determined at the second time scale. Based on the degree of deviation between the same rate of change, the current difference index, voltage difference index, and power difference index are determined respectively. The first and second current change rates are processed based on the current difference index to obtain the real-time current change rate. The first and second voltage change rates are processed based on the voltage difference index to obtain the real-time voltage change rate; The first and second power change rates are processed based on the power difference index to obtain the real-time power change rate; The battery health status is compensated by real-time current change rate, real-time voltage change rate, and real-time power change rate to obtain the compensated battery health status of the battery pack under test.

[0118] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0119] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0120] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method of estimating a state of health of a battery, characterized by, The method includes: Obtain the real-time operating status of the battery pack under test; the real-time operating status includes real-time battery voltage, battery current, and battery temperature; Based on the battery voltage and battery current, the first current change rate, the first voltage change rate, and the first power change rate of the battery pack under test are determined at the first time scale, and the second current change rate, the second voltage change rate, and the second power change rate of the battery pack under test are determined at the second time scale. Based on the degree of deviation between the same rate of change, the current difference index, voltage difference index, and power difference index are determined respectively. The first and second current change rates are processed based on the current difference index to obtain the real-time current change rate. The first and second voltage change rates are processed based on the voltage difference index to obtain the real-time voltage change rate; The first and second power change rates are processed based on the power difference index to obtain the real-time power change rate; The battery health status is compensated by real-time current change rate, real-time voltage change rate, and real-time power change rate to obtain the compensated battery health status of the battery pack under test.

2. The method of estimating state of health of a battery according to claim 1, wherein The method of compensating for battery health status using real-time current change rate, real-time voltage change rate, and real-time power change rate to obtain the compensated battery health status of the battery pack under test specifically includes: The real-time current change rate is normalized based on the preset current change rate reference value to obtain the current change rate characteristics. The real-time voltage change rate is normalized based on a preset voltage change rate reference value to obtain the voltage change rate characteristics. The real-time power change rate is normalized based on the preset power change rate reference value to obtain the power change rate characteristics. The real-time battery health status of the battery pack under test is determined based on the real-time operating status, and the real-time battery health status is compensated based on the battery temperature to obtain the basic battery health status of the battery pack under test. The health status of the base battery is compensated by using the characteristics of current change rate, voltage change rate, and power change rate to obtain the compensated battery health status.

3. The method for assessing battery health status according to claim 2, characterized in that, The formula for calculating the compensated battery health status is: ； in, Indicates the battery health status after compensation; Indicates the basic battery health status; Indicates the first weighting coefficient; Indicates the characteristic of the rate of change of current; This represents the second weighting coefficient; Indicates the characteristic of voltage change rate; Indicates the third weighting coefficient; This indicates the characteristic of the rate of change of power.

4. The method for assessing battery health status according to claim 1, characterized in that, The formula for calculating the current difference index is: ； The formula for calculating the voltage difference index is: ； The formula for calculating the power difference index is: ； in, Indicates the current difference index; Indicates the first rate of change of current; Indicates the rate of change of the second current; Indicates the first stabilizing factor; Indicates voltage difference index; Indicates the second stabilizing factor; Indicates the first rate of change of voltage; Indicates the second voltage change rate; Indicates power difference index; Indicates the third stability factor; Indicates the first power change rate; This represents the second power change rate.

5. The method for assessing battery health status according to claim 1, characterized in that, The process of processing the first and second current change rates based on the current difference index to obtain the real-time current change rate specifically includes: Divide the current difference index by the sum of the current difference index and 1 to obtain the first fusion weight; Assign a first fusion weight to the first current change rate, and perform weighted fusion on the first and second current change rates to obtain the real-time current change rate.

6. The method for assessing battery health status according to claim 1, characterized in that, The process of processing the first and second voltage change rates based on the voltage difference index to obtain the real-time voltage change rate specifically includes: Divide the voltage difference index by the sum of the voltage difference index and 1 to obtain the second fusion weight; The first voltage change rate is assigned a second fusion weight, and the first and second voltage change rates are weighted and fused to obtain the real-time voltage change rate.

7. The method for assessing battery health status according to claim 1, characterized in that, The process of processing the first and second power change rates based on the power difference index to obtain the real-time power change rate specifically includes: Divide the power difference index by the sum of the power difference index and 1 to obtain the third fusion weight; The first power change rate is assigned a third fusion weight, and the first and second power change rates are weighted and fused to obtain the real-time power change rate.

8. A device for assessing the health status of a battery, characterized in that, The device includes: The data acquisition module is used to acquire the real-time operating status of the battery pack under test; the real-time operating status includes real-time battery voltage, battery current and battery temperature; The parameter calculation module is used to determine the first current change rate, the first voltage change rate, and the first power change rate of the battery pack under test at the first time scale, and the second current change rate, the second voltage change rate, and the second power change rate of the battery pack under test at the second time scale, based on the battery voltage and the battery current. The difference determination module is used to determine the current difference index, voltage difference index, and power difference index respectively based on the degree of deviation between the same rate of change. The first fusion module is used to process the first and second current change rates according to the current difference index to obtain the real-time current change rate. The second fusion module is used to process the first and second voltage change rates according to the voltage difference index to obtain the real-time voltage change rate. The third fusion module is used to process the first and second power change rates according to the power difference index to obtain the real-time power change rate; The battery evaluation module is used to compensate for the battery health status using real-time current change rate, real-time voltage change rate, and real-time power change rate, so as to obtain the compensated battery health status of the battery pack under test.

9. 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 program, it implements the steps of the battery health status assessment method as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the battery health status assessment method as described in any one of claims 1 to 7.

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