Battery module / battery cluster internal health state scoring method, system, storage medium and terminal

Abstract

The application provides a battery module / battery cluster health state scoring method, system, storage medium and terminal, the method comprises the following steps: obtaining performance data of battery cells in a battery module / battery cluster; performing normalization processing on the performance data to obtain normalized data; calculating the standard score of the performance data based on the normalized data; calculating the performance score corresponding to the battery module / battery cluster based on the standard score; and calculating the health state score of the battery module / battery cluster based on the performance score. The battery module / battery cluster health state scoring method, system, storage medium and terminal can evaluate the health state of the battery module / battery cluster in real time, effectively improving the safety and reliability of the battery module / battery cluster.

Description

Technical Field

[0001] This invention relates to the technical field of battery modules / battery clusters, and in particular to a method, system, storage medium, and terminal for scoring the health status of a battery module / battery cluster. Background Technology

[0002] Battery module health status assessment is crucial for battery system performance optimization, fault prediction, and safety assurance. Existing battery health status assessment methods mainly include the following two approaches:

[0003] (1) Monitoring and statistical analysis based on discrete battery parameters

[0004] However, the methods mentioned above typically focus only on monitoring simple parameters such as voltage and temperature of a single battery, failing to provide a comprehensive assessment of detailed information about the battery's internal structure. This may result in inaccurate judgment of the battery's health status and the overlooking of potential hidden faults. They often rely on periodic, discrete measurements, failing to provide continuous and real-time monitoring of battery health status, thus limiting the ability to accurately track battery status and predict faults, and making it impossible to take timely measures to prevent potential faults. Furthermore, they often lack comprehensive health assessment indicators and algorithms, making it difficult to consider multiple parameters comprehensively, resulting in limited accuracy and reliability of the assessment results.

[0005] To address the aforementioned issues, existing technologies have proposed several improved solutions, such as model-based prediction algorithms, high-frequency sampling, and data mining. However, existing technologies still face challenges, including model complexity, computational resource requirements, and the real-time performance of the algorithms.

[0006] (2) Based on battery capacity detection and fixed-cycle charge-discharge cycle

[0007] However, the above methods only focus on the overall battery capacity assessment and cannot provide detailed monitoring of the health status of individual batteries within the module. This may result in some batteries remaining in the module even if their capacity has decreased or they have failed, thus affecting the performance of the entire system. They often rely on fixed-cycle charge-discharge to estimate battery capacity and health status, which limits the accuracy and reliability of the assessment results to time and the number of cycles. They also typically ignore other factors related to battery health status, such as changes in internal resistance and temperature, which have a significant impact on battery performance and lifespan.

[0008] To address the aforementioned issues, existing technologies have proposed several improved solutions, such as real-time monitoring based on battery management systems (BMS), electrochemical models, and data analysis algorithms. However, existing technologies still face challenges, such as complex algorithms and models, and the cost and reliability of sensors. Summary of the Invention

[0009] In view of the shortcomings of the prior art described above, the purpose of this invention is to provide a method, system, storage medium and terminal for scoring the health status of a battery module / battery cluster, which can evaluate the health status of the battery module / battery cluster in real time and effectively improve the safety and reliability of the battery module / battery cluster.

[0010] In a first aspect, the present invention provides a method for scoring the health status of a battery module / battery cluster, the method comprising the following steps: acquiring performance data of cells in the battery module / battery cluster; normalizing the performance data to obtain normalized data; calculating a standard score of the performance data based on the normalized data; calculating a performance score corresponding to the battery module / battery cluster based on the standard score; and calculating a health status score of the battery module / battery cluster based on the performance score.

[0011] In one implementation of the first aspect, obtaining the performance data of the cells in the battery module / battery cluster includes the following steps:

[0012] Acquire basic data of the cells in the battery module / battery cluster collected by the battery management system; the basic data includes one or more combinations of voltage, current, and temperature of the cells in the battery module / battery cluster;

[0013] Based on the aforementioned basic data, the indicator data of the cells in the battery module / battery cluster are calculated. The indicator data includes one or more combinations of the internal resistance, capacity, state of charge, and state of health of the cells in the battery module / battery cluster.

[0014] The basic data and the indicator data constitute the performance data.

[0015] In one implementation of the first aspect, the basic data is further cleaned to calculate the indicator data based on the cleaned basic data.

[0016] In one implementation of the first aspect, the performance data is normalized to obtain normalized data using any of the following methods:

[0017] 1) Calculate the normalized data according to X_scaled = (X-X_min) / (X_max-X_min), where X_scaled represents the normalized data, X represents the performance data, and X_max and X_min represent the maximum and minimum values ​​of the performance data.

[0018] 2) Calculate the normalized data based on X_scaled = (X - mean) / std_dev, where X_scaled represents the normalized data, X represents the performance data, mean represents the mean of the performance data, and std_dev represents the standard deviation of the performance data.

[0019] In one implementation of the first aspect, calculating the performance score corresponding to the battery module / battery cluster based on the standard score includes the following steps:

[0020] Obtain the maximum absolute value of the standard score of the performance data of each cell;

[0021] The cumulative probability corresponding to the maximum value is obtained based on the cumulative distribution function;

[0022] The performance score is calculated as score = 100 - 2(P*100 - 50), where P represents the cumulative probability.

[0023] In one implementation of the first aspect, the health status score of the battery module / battery cluster is calculated based on the performance score using any of the following methods:

[0024] 1) According to Calculate the health status score, where This represents the i-th performance score. This represents the weight of the i-th performance score, and n represents the number of performance scores;

[0025] 2) According to Calculate the health status score.

[0026] In one implementation of the first aspect, a radar chart is also drawn based on the performance score to determine the status of each performance based on the radar chart.

[0027] Secondly, the present invention provides a health status scoring system within a battery module / battery cluster, the system comprising an acquisition module, a normalization module, a first calculation module, a second calculation module, and a scoring module;

[0028] The acquisition module is used to acquire the performance data of the cells in the battery module / battery cluster;

[0029] The normalization module is used to normalize the performance data to obtain normalized data;

[0030] The first calculation module is used to calculate the standard score of the performance data based on the normalized data;

[0031] The second calculation module is used to calculate the performance score corresponding to the battery module / battery cluster based on the standard score;

[0032] The scoring module is used to calculate the health status score of the battery module / battery cluster based on the performance score.

[0033] Thirdly, the present invention provides a storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described method for scoring the health status of a battery module / battery cluster.

[0034] Fourthly, the present invention provides a health status scoring terminal within a battery module / battery cluster, comprising: a processor and a memory;

[0035] The memory is used to store computer programs;

[0036] The processor is used to execute the computer program stored in the memory, so that the battery module / battery cluster health status scoring terminal performs the above-described battery module / battery cluster health status scoring method.

[0037] As described above, the battery module / battery cluster health status scoring method, system, storage medium, and terminal of the present invention have the following beneficial effects:

[0038] (1) It can obtain multiple key parameters of battery modules / battery clusters, such as voltage, temperature, current, capacity, internal resistance, etc., and calculate the corresponding health status score through comprehensive algorithms and models;

[0039] (2) Through continuous parameter monitoring and comprehensive evaluation, abnormal conditions and health changes of battery modules / battery clusters can be detected in a timely manner, providing accurate health status scores and giving corresponding alarms and suggestions to optimize battery usage and maintenance strategies.

[0040] (3) It can take corresponding measures based on the actual health status of the battery to reduce the risk of failure and improve the stability and reliability of the battery system;

[0041] (4) Applicable to batteries of various models, manufacturers and operating conditions, with a wide range of applications and applicable to the entire life cycle of batteries;

[0042] (5) Using radar charts allows for a direct and convenient comparison of the performance of different battery modules / battery clusters;

[0043] (6) In addition to being applicable to a single battery module, it is also applicable to multiple battery modules in series operation, thereby enabling the determination of performance differences between different battery modules in series mode and avoiding complex operations such as unpacking. Attached Figure Description

[0044] Figure 1 The flowchart shown is an embodiment of the battery module / battery cluster health status scoring method of the present invention;

[0045] Figure 2 A schematic diagram showing the health status score of a single battery module / battery cluster in one embodiment;

[0046] Figure 3 This is a schematic diagram showing the health status scores of multiple battery modules / battery clusters in one embodiment;

[0047] Figure 4 The diagram shown is a structural schematic of the battery module / battery cluster health status scoring system of the present invention in one embodiment.

[0048] Figure 5 The diagram shown is a structural schematic of a health status scoring terminal within a battery module / battery cluster according to an embodiment of the present invention. Detailed Implementation

[0049] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, unless otherwise specified, the following embodiments and features described therein can be combined with each other.

[0050] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0051] The battery module / battery cluster health status scoring method, system, storage medium and terminal of the present invention can evaluate the health status of the battery module / battery cluster in real time by collecting the performance data of each cell in the battery module / battery cluster, and can take corresponding measures according to the actual health status of the battery to reduce the risk of failure and improve the stability and reliability of the battery system, thus making it highly practical.

[0052] like Figure 1 As shown, in one embodiment, the battery module / battery cluster health status scoring method of the present invention includes the following steps:

[0053] Step S1: Obtain the performance data of the cells in the battery module / battery cluster.

[0054] Specifically, obtaining the performance data of the cells in a battery module / battery cluster includes the following steps:

[0055] 11) Obtain basic data of the cells in the battery module / battery cluster collected by the Battery Management System (BMS) over a period of time. The basic data includes one or more combinations of voltage, current, and temperature of the cells in the battery module / battery cluster.

[0056] Preferably, the method further includes data cleaning of the basic data, such as removing abnormal data and duplicate data.

[0057] 12) Calculate the performance indicators of the cells in the battery module / battery cluster based on the aforementioned basic data. These performance indicators include one or more combinations of the following: internal resistance, capacity, state of charge (SOC), and state of health (SOH) of the cells in the battery module / battery cluster.

[0058] A battery cluster contains multiple battery modules connected in series, and each battery module contains multiple cells connected in series. Therefore, the current in each cell is the same, but the temperature and voltage of each cell may differ. Thus, based on the aforementioned basic data, data such as internal resistance, capacity, state of charge (SOC), and state of equilibrium (SOH) can be calculated. To ensure data accuracy, preferably, cleaned basic data is used to calculate these performance indicators.

[0059] 13) The basic data and the indicator data constitute the performance data.

[0060] Step S2: Normalize the performance data to obtain normalized data.

[0061] Specifically, the performance data is normalized using any of the following methods to obtain normalized data:

[0062] 1) Calculate the normalized data according to X_scaled = (X-X_min) / (X_max-X_min), where X_scaled represents the normalized data, X represents the performance data, and X_max and X_min represent the maximum and minimum values ​​of the performance data.

[0063] The normalized data falls within the interval [0, 1].

[0064] 2) Calculate the normalized data based on X_scaled = (X - mean) / std_dev, where X_scaled represents the normalized data, X represents the performance data, mean represents the mean of the performance data, and std_dev represents the standard deviation of the performance data.

[0065] This method is called Z-score standardization. Z-score standardization transforms the original data into a standard normal distribution, making the mean 0 and the standard deviation 1. It should be noted that when the normalization result encounters 0 and 1, it needs to be converted to 0.01 and 0.99 respectively to prevent subsequent calculation errors. All results can be retained to two decimal places.

[0066] Step S3: Calculate the standard score of the performance data based on the normalized data.

[0067] Specifically, according to Calculate the standard score, where express, The standard score represents the feature data of the i-th cell, and the feature data of the i-th cell are... and These represent the mean and standard deviation of the feature data, respectively.

[0068] Step S4: Calculate the performance score corresponding to the battery module / battery cluster based on the standard score.

[0069] Specifically, calculating the performance score corresponding to the battery module / battery cluster based on the standard score includes the following steps:

[0070] 41) Obtain the maximum absolute value of the standard score of the performance data of each cell.

[0071] 42) Obtain the cumulative probability corresponding to the maximum value based on the cumulative distribution function.

[0072] Calculating the cumulative probability of a specific z-score in the standard normal distribution using the cumulative distribution function (CDF) formula is entirely feasible. The CDF of the standard normal distribution is an integral expression, but it typically requires computational tools or numerical methods to calculate. The expression for the CDF of the standard normal distribution is as follows:

[0073]

[0074] Where erf is the error function and z is the z-score of the standard normal distribution. For z=1.5, the cumulative probability value is calculated to be 0.933192; for z=2, the cumulative probability value is calculated to be 0.97725; for z=1, the cumulative probability value is calculated to be 0.841344; and for z=0, the cumulative probability value is calculated to be 0.5.

[0075] 43) Calculate the performance score score = 100-2(P*100-50), where P represents the cumulative probability.

[0076] Therefore, when the maximum absolute value of the standard score is 1, the corresponding performance score is score = 100 - 2(P*100 - 50) = 32, where P is the cumulative probability that the maximum absolute value of the standard score is 1. The smaller the maximum absolute value of the standard score, the higher the performance score, indicating better consistency between the battery module and battery cluster; conversely, the larger the maximum absolute value of the standard score, the lower the performance score, indicating poorer consistency between the battery module and battery cluster.

[0077] Preferably, a radar chart is generated based on the performance scores to determine the status of each performance characteristic. For example... Figure 2 As shown, the health scores for each item are plotted on a radar chart, providing a clear visual representation of the performance of each component. The chart clearly shows that, except for voltage consistency, all other performance metrics score above 60. Figure 3 As shown, plotting data from multiple battery modules or battery clusters onto a single radar chart provides a simple and intuitive way to distinguish between good and bad battery clusters and modules, as well as the quality of their internal performance. The chart clearly shows that one module's performance weakness is voltage consistency, while another module's weakness is temperature consistency.

[0078] Step S5: Calculate the health status score of the battery module / battery cluster based on the performance score.

[0079] Specifically, the health status score of the battery module / battery cluster can be calculated based on the performance score using any of the following methods:

[0080] 1) According to Calculate the health status score, where This represents the i-th performance score. represents the weight of the i-th performance score, and n represents the number of performance scores.

[0081] 2) According to Different performance indicators are weighted according to the calculated health status scores. Preferably, when the number of performance scores is no more than 10, method 2 is used.

[0082] Preferably, the weights corresponding to each performance metric are set to be the same.

[0083] The following specific embodiments further illustrate the health status scoring method within the battery module / battery cluster of the present invention.

[0084] In this embodiment, at a certain site, the temperature and voltage collected by the BMS are as follows:

[0085] Voltage: [2.932, 3.052, 3.095, 2.996, 2.928, 2.799, 2.933, 2.83, 3.039, 3.011, 2.754, 2.965, 3.006, 2.904, 3.083, 3.029, 3.011, 2.984, 3.032, 3.091, 2.97, 3.12, 3.021, 3.013]

[0086] The normalized results are as follows:

[0087] Voltage: [0.49, 0.81, 0.93, 0.66, 0.48, 0.12, 0.49, 0.21, 0.78, 0.7, 0.01, 0.58, 0.69, 0.41,

[0088] 0.9, 0.75, 0.7, 0.63, 0.76, 0.92, 0.59, 0.99, 0.73, 0.71]

[0089] The calculated standard scores are as follows:

[0090] Voltage: [-0.55, 0.73, 1.21, 0.13, -0.59, -2.03, -0.55, -1.67, 0.61, 0.29, -2.47,

[0091] -0.19, 0.25, -0.87, 1.09, 0.49, 0.29, 0.01, 0.53, 1.17, -0.15, 1.49, 0.41, 0.33]

[0092] That is, z=2.03, the corresponding performance score is 100 – 2*(97.98-50)=4.04.

[0093] The calculated performance score is 4.04. Therefore, the performance scores for capacitance, SOC, voltage, temperature, and internal resistance are 90, 96, 4.04, 90, and 82, respectively. When the weight of each performance score is 1, the final health status score is 72.41 based on the individual performance scores.

[0094] The scope of protection of the battery module / battery cluster health status scoring method described in this embodiment is not limited to the execution order of the steps listed in this embodiment. Any solution implemented by adding, subtracting, or replacing steps in the prior art based on the principle of this invention is included within the scope of protection of this invention.

[0095] This invention also provides a battery module / battery cluster health status scoring system. The battery module / battery cluster health status scoring system can implement the battery module / battery cluster health status scoring method described in this invention. However, the implementation device of the battery module / battery cluster health status scoring system described in this invention includes, but is not limited to, the structure of the battery module / battery cluster health status scoring system listed in this embodiment. All structural modifications and substitutions of the prior art made according to the principles of this invention are included within the protection scope of this invention.

[0096] like Figure 4 As shown, in one embodiment, the battery module / battery cluster health status scoring system of the present invention includes an acquisition module 41, a normalization module 42, a first calculation module 43, a second calculation module 44, and a scoring module 45.

[0097] The acquisition module 41 is used to acquire the performance data of the cells in the battery module / battery cluster.

[0098] The normalization module 42 and the acquisition module 41 are used to normalize the performance data to obtain normalized data.

[0099] The first calculation module 43 is connected to the normalization module 42 and is used to calculate the standard score of the performance data based on the normalized data.

[0100] The second calculation module 44 is connected to the first calculation module 43 and is used to calculate the performance score corresponding to the battery module / battery cluster based on the standard score.

[0101] The scoring module 45 is connected to the second calculation module 44 and is used to calculate the health status score of the battery module / battery cluster based on the performance score.

[0102] The structure and principle of the acquisition module 41, normalization module 42, first calculation module 43, second calculation module 44 and scoring module 45 correspond one-to-one with the steps in the above-mentioned battery module / battery cluster health status scoring method, so they will not be described again here.

[0103] It should be noted that the division of the various modules in the above device is merely a logical functional division. In actual implementation, they can be fully or partially integrated into a single physical entity, or they can be physically separated. Furthermore, these modules can be implemented entirely in software via processing element calls, entirely in hardware, or partially in software calls via processing elements and partially in hardware. For example, module x can be a separate processing element or integrated into a chip within the device. Additionally, module x can be stored as program code in the device's memory, invoked and executed by a processing element. The implementation of other modules is similar. These modules can be fully or partially integrated together or implemented independently. The processing element mentioned here can be an integrated circuit with signal processing capabilities. In the implementation process, each step of the above method or each of the above modules can be completed through integrated logic circuits in the hardware of the processor element or through software instructions. These modules can be one or more integrated circuits configured to implement the above methods, such as one or more Application Specific Integrated Circuits (ASICs), one or more Digital Signal Processors (DSPs), one or more Field Programmable Gate Arrays (FPGAs), etc. When a module is implemented through processing element scheduler code, the processing element can be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor capable of calling program code. These modules can be integrated together to form a System-on-a-Chip (SOC).

[0104] The storage medium of this invention stores a computer program, which, when executed by a processor, implements the aforementioned method for scoring the health status of a battery module / battery cluster. Preferably, the storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disk, USB flash drive, memory card, or optical disk.

[0105] like Figure 5 As shown, in one embodiment, the health status scoring terminal within the battery module / battery cluster of the present invention includes: a processor 51 and a memory 52.

[0106] The memory 52 is used to store computer programs. The memory 52 includes various media capable of storing program code, such as ROM, RAM, magnetic disk, USB flash drive, memory card, or optical disk.

[0107] The processor 51 is connected to the memory 52 and is used to execute the computer program stored in the memory so that the battery module / battery cluster health status scoring terminal performs the above-described battery module / battery cluster health status scoring method.

[0108] Preferably, the processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0109] In summary, the battery module / battery cluster health status scoring method, system, storage medium, and terminal of this invention can acquire multiple key parameters of the battery module / battery cluster, such as voltage, temperature, current, capacity, and internal resistance, and calculate the corresponding health status score through comprehensive algorithms and models. Through continuous parameter monitoring and comprehensive evaluation, it can promptly detect abnormal conditions and health changes in the battery module / battery cluster, provide accurate health status scores, and offer corresponding alarms and suggestions to optimize battery usage and maintenance strategies. It can take corresponding measures based on the actual health status of the battery to reduce failure risks and improve the stability and reliability of the battery system. It is applicable to batteries of various models, manufacturers, and operating conditions, with a wide range of applications and applicable to the entire battery lifecycle. The use of radar charts allows for intuitive and convenient comparison of the performance of different battery modules / battery clusters. In addition to being applicable to a single battery module, it is also applicable to multiple battery modules in series operation, thereby enabling the determination of performance differences between different battery modules in series mode and avoiding complex operations such as unpacking. Therefore, this invention effectively overcomes the various shortcomings of the prior art and has high industrial application value.

[0110] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A method for state of health scoring within a battery module / battery string, the method comprising: The method includes the following steps: ​ Obtain performance data of cells in battery modules / battery clusters; The performance data is normalized to obtain normalized data; Based on the normalized data, calculate the standard score of the performance data; Calculate the performance score corresponding to the battery module / battery cluster based on the standard score; Calculate the health status score of the battery module / battery cluster based on the performance score; Calculating the performance score corresponding to the battery module / battery cluster based on the standard score includes the following steps: Obtain the maximum absolute value of the standard score of the performance data of each cell; The cumulative probability corresponding to the maximum value is obtained based on the cumulative distribution function; The performance score is calculated as score = 100 - 2(P*100 - 50), where P represents the cumulative probability.

2. The battery module / cluster internal state of health scoring method of claim 1, wherein: Obtaining performance data of cells in a battery module / battery cluster includes the following steps: Acquire basic data of the cells in the battery module / battery cluster collected by the battery management system; the basic data includes one or more combinations of voltage, current, and temperature of the cells in the battery module / battery cluster; Based on the aforementioned basic data, the indicator data of the cells in the battery module / battery cluster are calculated. The indicator data includes one or more combinations of the internal resistance, capacity, state of charge, and state of health of the cells in the battery module / battery cluster. The basic data and the indicator data constitute the performance data.

3. The battery module / cluster internal state of health scoring method of claim 2, wherein: It also includes data cleaning of the basic data, in order to calculate the indicator data based on the cleaned basic data.

4. The battery module / cluster health state score method of claim 1, wherein: The performance data is normalized using any of the following methods to obtain normalized data: 1) Calculate the normalized data according to X_scaled = (X-X_min) / (X_max-X_min), where X_scaled represents the normalized data, X represents the performance data, and X_maxE and X_min distributions represent the maximum and minimum values ​​of the performance data; 2) Calculate the normalized data based on X_scaled = (X - mean) / std_dev, where X_scaled represents the normalized data, X represents the performance data, mean represents the mean of the performance data, and std_dev represents the standard deviation of the performance data.

5. The battery module / battery pack intra-state of health scoring method of claim 1, wherein: The health status score of the battery module / battery cluster is calculated based on the performance score using any of the following methods: 1) according to calculating the health status score, wherein represents the i-th performance score, represents the weight of the i-th performance score, n represents the number of performance scores; 2) according to calculating the health status score.

6. The battery module / cluster health state score method of claim 1, wherein: It also includes generating a radar chart based on the performance score to determine the status of each performance metric based on the radar chart.

7. A state of health scoring system within a battery module / battery string, characterized by: The system includes an acquisition module, a normalization module, a first calculation module, a second calculation module, and a scoring module; The acquisition module is used to acquire the performance data of the cells in the battery module / battery cluster; The normalization module is used to normalize the performance data to obtain normalized data; The first calculation module is used to calculate the standard score of the performance data based on the normalized data; The second calculation module is used to calculate the performance score corresponding to the battery module / battery cluster based on the standard score; The scoring module is used to calculate the health status score of the battery module / battery cluster based on the performance score; Calculating the performance score corresponding to the battery module / battery cluster based on the standard score includes the following steps: Obtain the maximum absolute value of the standard score of the performance data of each cell; The cumulative probability corresponding to the maximum value is obtained based on the cumulative distribution function; The performance score is calculated as score = 100 - 2(P*100 - 50), where P represents the cumulative probability.

8. A storage medium having stored thereon a computer program, characterized in that When executed by the processor, the program implements the health status scoring method within the battery module / battery cluster as described in any one of claims 1 to 6. 9.A terminal for state of health scoring within a battery module / battery cluster, the terminal comprising: include: Processor and memory; The memory is used to store computer programs; The processor is used to execute the computer program stored in the memory to cause the battery module / battery cluster health status scoring terminal to perform the battery module / battery cluster health status scoring method according to any one of claims 1 to 6.

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