Battery safety state evaluation method and device and electronic equipment

Abstract

The invention discloses a battery safety state evaluation method and device and electronic equipment. The method comprises the following steps: acquiring a plurality of external operation parameters of a to-be-tested battery; obtaining a first safety weight of the to-be-tested battery based on the plurality of external operation parameters; multiple internal operation parameters of the to-be-detected battery are obtained, the multiple internal operation parameters comprise multi-dimensional impedance characteristic parameters, the multi-dimensional impedance characteristic parameters are obtained by applying an active diagnosis signal to the to-be-detected battery, and the active diagnosis signal is used for controlling instantaneous interruption of current; obtaining a second safety weight of the to-be-tested battery based on the plurality of internal operation parameters; and according to the first safety weight and the second safety weight, obtaining a safety state evaluation result of the to-be-tested battery. According to the invention, the technical problem of low accuracy of battery safety state assessment caused by incomplete consideration factors in battery safety state assessment in the prior art is solved.

Description

Technical Field

[0001] This invention relates to the field of battery technology, and more specifically, to a method, apparatus, and electronic device for assessing battery safety status. Background Technology

[0002] In the fields of new energy and energy-saving technologies, batteries play a crucial role as core components in power systems and energy storage systems. However, the complex internal structure of batteries and the variability of their external operating environment make their safety status assessment a challenge. The safety monitoring strategies of battery management systems (BMS) in related technologies mainly rely on monitoring external operating parameters such as voltage, current, and temperature. These parameters only trigger warnings when significant abnormalities occur, often indicating that the fault has already progressed to a more serious stage, failing to provide early warning and reducing the overall safety of the system. Especially in battery safety status assessment, related technologies often neglect the influence of the battery's internal electrochemical state and the correlation between external abuse (such as mechanical abuse, thermal abuse, and electrical abuse) and changes in internal parameters. This limitation of the assessment mechanism leads to low accuracy in battery safety status assessment, failing to effectively identify faults in their early stages and increasing the risk of safety events such as battery thermal runaway.

[0003] There is currently no effective solution to the above problems. Summary of the Invention

[0004] This invention provides a battery safety status assessment method, apparatus, and electronic device to at least solve the technical problem in related technologies where the factors considered in battery safety status assessment are not comprehensive, resulting in low accuracy of battery safety status assessment.

[0005] According to one aspect of the present invention, a battery safety status assessment method is provided, comprising: acquiring multiple external operating parameters of a battery under test, wherein the multiple external operating parameters include temperature values ​​corresponding to multiple monitoring points on the battery under test, voltage values ​​corresponding to multiple cells, and deformation amounts corresponding to multiple deformation sampling points; obtaining a first safety weight of the battery under test based on the multiple external operating parameters; acquiring multiple internal operating parameters of the battery under test, wherein the multiple internal operating parameters include multi-dimensional impedance characteristic parameters, the multi-dimensional impedance characteristic parameters being obtained by applying an active diagnostic signal to the battery under test, the active diagnostic signal being used to control the instantaneous interruption of current; obtaining a second safety weight of the battery under test based on the multiple internal operating parameters; and obtaining a safety status assessment result of the battery under test according to the first safety weight and the second safety weight.

[0006] According to another aspect of the present invention, a battery safety status assessment device is also provided, comprising: an external parameter acquisition module for acquiring multiple external operating parameters of the battery under test, wherein the multiple external operating parameters include temperature values ​​corresponding to multiple monitoring points on the battery under test, voltage values ​​corresponding to multiple cells, and deformation values ​​corresponding to multiple deformation sampling points; a first weight determination module for obtaining a first safety weight of the battery under test based on the multiple external operating parameters; an internal parameter acquisition module for acquiring multiple internal operating parameters of the battery under test, wherein the multiple internal operating parameters include multi-dimensional impedance characteristic parameters, the multi-dimensional impedance characteristic parameters being obtained by applying an active diagnostic signal to the battery under test, the active diagnostic signal being used to control the instantaneous interruption of current; a second weight determination module for obtaining a second safety weight of the battery under test based on the multiple internal operating parameters; and a safety status assessment module for obtaining a safety status assessment result of the battery under test according to the first safety weight and the second safety weight.

[0007] According to another aspect of the present invention, a non-volatile storage medium is also provided, which stores a plurality of instructions adapted for a battery safety status assessment method, any one of which can be loaded and executed by a processor.

[0008] According to another aspect of the present invention, an electronic device is also provided, including one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement any one of the battery safety status assessment methods.

[0009] According to another aspect of the present invention, a computer program product is also provided, including a computer program that, when executed by a processor, implements the steps of any one of the battery safety status assessment methods.

[0010] In this embodiment of the invention, multiple external operating parameters of the battery under test are acquired, including temperature values ​​corresponding to multiple monitoring points on the battery under test, voltage values ​​corresponding to multiple cells, and deformation values ​​corresponding to multiple deformation sampling points. Based on these multiple external operating parameters, a first safety weight of the battery under test is obtained. Multiple internal operating parameters of the battery under test are also acquired, including multi-dimensional impedance characteristic parameters obtained by applying an active diagnostic signal to the battery under test, which is used to control the instantaneous interruption of current. Based on these multiple internal operating parameters, a second safety weight of the battery under test is obtained. According to the first and second safety weights, the safety status assessment result of the battery under test is obtained. This achieves the goal of comprehensively assessing the battery safety status by combining external operating parameter monitoring with active diagnosis of internal multi-dimensional impedance characteristic parameters, calculating the first and second safety weights respectively, and then fusing them. This improves the accuracy and comprehensiveness of the battery safety status assessment, thereby solving the technical problem in related technologies where incomplete consideration of factors in battery safety status assessment leads to low accuracy. Attached Figure Description

[0011] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0012] Figure 1 This is a flowchart of a battery safety status assessment method according to an embodiment of the present invention;

[0013] Figure 2 This is an optional current interruption identification schematic diagram according to an embodiment of the present invention;

[0014] Figure 3 This is a flowchart of an optional battery safety status assessment method according to an embodiment of the present invention;

[0015] Figure 4 This is a flowchart of an optional first security weight determination according to an embodiment of the present invention;

[0016] Figure 5 This is a schematic diagram of a battery safety status assessment device according to an embodiment of the present invention. Detailed Implementation

[0017] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0018] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0019] According to an embodiment of the present invention, a method embodiment for battery safety status assessment is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0020] Figure 1 This is a flowchart of a battery safety status assessment method according to an embodiment of the present invention, such as... Figure 1 As shown, the method includes the following steps:

[0021] Step S102: Obtain multiple external operating parameters of the battery under test, including the temperature value corresponding to each of the multiple monitoring points on the battery under test, the voltage value corresponding to each of the multiple cells, and the deformation value corresponding to each of the multiple deformation sampling points.

[0022] Optionally, temperature sensors deployed at different locations within the battery under test (such as a battery pack) can be used to monitor the battery's temperature distribution in real time. Both excessively high and low temperatures can trigger battery safety issues. By monitoring the voltage of each cell within the battery under test, internal health problems (or early warning signs) caused by uneven voltage distribution can be detected promptly. Pressure or displacement sensors can be used to monitor the deformation of the battery under test (or battery pack) under mechanical stress, especially when the battery is subjected to external impact or compression, as deformation can lead to internal structural damage and safety hazards.

[0023] Step S104: Based on multiple external operating parameters, obtain the first safety weight of the battery under test;

[0024] Optionally, after collecting external operating parameters, they can be converted into a unified quantitative indicator—the first safety weight. This weight can be understood as an external comprehensive safety weight, used to reflect the risk level of the battery being affected by external abuse (such as excessive temperature, mechanical damage, electrical overload, etc.), providing a measure of the impact of external conditions on the battery's safety status for subsequent comprehensive assessments.

[0025] In one optional embodiment, a first safety weight of the battery under test is obtained based on multiple external operating parameters, including: obtaining multiple external safety weights based on multiple external operating parameters, wherein the multiple external safety weights include a temperature safety weight, a voltage safety weight, and a deformation safety weight; and multiplying the multiple external safety weights to obtain the first safety weight.

[0026] Optionally, the temperature safety weight can be used to assess whether the battery under test is operating within a safe temperature range based on the temperature values ​​collected from multiple monitoring points. Excessively high or low temperatures can affect battery performance and even cause safety issues. This weight can be determined by comparing the measured temperature with preset safety and failure thresholds. The voltage safety weight can be used to assess the voltage balance within the battery by analyzing the voltage values ​​of multiple cells. Abnormal voltage fluctuations or uneven distributions may be signs of internal battery failure; this weight reflects the safety of the battery's voltage state. The deformation safety weight can be used to monitor the deformation of the battery under test under mechanical stress, especially deformation caused by external impact. Physical deformation of the battery may affect the integrity of its internal structure, thus posing a threat to battery safety. This weight is determined based on a comparison of the deformation amount and a safety threshold. Considering that the battery's safety state is the result of the combined effect of multiple external factors, any abnormality in a single factor may threaten overall safety. Therefore, through multiplication, even if only one weight decreases (i.e., the corresponding parameter is abnormal), the first safety weight will significantly decrease, promptly reflecting the external risks faced by the battery. This approach ensures that the primary safety weight comprehensively reflects the combined impact of the external environment on the battery's safety status, providing crucial reference for subsequent internal parameter evaluations and the final safety status assessment. Through such meticulous monitoring and quantification of external parameters, combined with the evaluation of internal parameters, the overall safety status of the battery can be assessed more accurately and comprehensively, thereby enabling early warnings and timely protective measures.

[0027] In one optional embodiment, multiple external safety weights are obtained based on multiple external operating parameters, including: obtaining temperature safety weights based on the temperature values ​​corresponding to each of the multiple monitoring points by determining the maximum temperature value among the temperature values ​​corresponding to each of the multiple monitoring points; and obtaining the temperature safety weight based on the maximum temperature value by: ;in, Indicates temperature safety weight. Indicates the maximum temperature value. This indicates the preset safe temperature, which is the highest temperature at which the battery under test can operate safely. The preset failure temperature represents the lowest temperature at which the battery under test will fail. The voltage safety weight is obtained based on the voltage values ​​of each of the multiple cells, using the same method as the temperature safety weight. The deformation safety weight is obtained based on the deformation values ​​of each of the multiple deformation sampling points, using the same method as the temperature safety weight.

[0028] Optionally, first, identify the highest temperature value from the temperature data collected at each monitoring point. Based on actual measurements With the preset safe temperature and failure temperature The relationship is calculated using piecewise linear functions. .when Less than or equal to safe temperature hour: = 1 indicates that the battery temperature is within a safe range, and the weight is the largest. When greater than safe temperature But below the failure temperature hour: Linear interpolation is used here, with the weights decreasing linearly as temperature increases, reflecting the decrease in safety status as the temperature approaches the failure temperature. greater than or equal to failure temperature hour, This indicates that the battery temperature has exceeded the safe operating range, with a weight of 0, signifying a serious safety risk. Based on the voltage values ​​corresponding to multiple cells, the same calculation method as for temperature safety weighting is used to identify abnormal voltage ranges. These ranges are then compared with preset voltage safety thresholds and failure thresholds, and a piecewise linear function is used to calculate... Based on the deformation variables corresponding to multiple deformation sampling points, and using a piecewise linear function consistent with the safety weight calculation logic for temperature and voltage, the measured deformation variables are compared with the preset deformation safety threshold and failure threshold to obtain... The calculated , and The results are multiplied to derive the first safety weight. This calculation logic reflects that any anomaly in any single external factor will significantly reduce the overall safety status of the battery, ensuring the comprehensiveness and sensitivity of the evaluation results.

[0029] In the above methods, by setting boundary conditions for safety and failure and using piecewise linear functions to quantify safety weights, the accuracy and reliability of external operating parameter evaluation can be effectively improved, laying a solid foundation for the comprehensive safety status evaluation of the battery under test.

[0030] Step S106: Obtain multiple internal operating parameters of the battery under test. The multiple internal operating parameters include multi-dimensional impedance characteristic parameters. The multi-dimensional impedance characteristic parameters are obtained by applying an active diagnostic signal to the battery under test. The active diagnostic signal is used to control the instantaneous interruption of the current.

[0031] Optionally, active diagnostic techniques can be employed, which involve applying a specific electrical signal (such as a momentary interruption of the control current) to the battery under test to elicit its internal response and extract multi-dimensional impedance characteristic parameters. These impedance characteristic parameters may include, but are not limited to, the constant-current equivalent DC internal resistance, ohmic internal resistance, electrochemical polarization internal resistance, and concentration polarization internal resistance of the battery under test. These parameters reflect the state of the electrochemical active materials inside the battery, the performance of the electrolyte, the integrity of the separator, and other factors, providing in-depth insights into the internal health of the battery under test.

[0032] In one optional embodiment, multiple internal operating parameters of the battery under test are obtained, including: during the constant current charging phase of the battery under test, obtaining the constant current equivalent DC internal resistance of the battery under test; at the interruption moment when an active diagnostic signal is applied to the battery under test, causing a current interruption, obtaining the ohmic internal resistance of the battery under test; during a preset voltage recovery period after the interruption moment, obtaining the electrochemical polarization internal resistance and concentration polarization internal resistance of the battery under test, wherein the electrochemical polarization internal resistance represents the internal resistance increment generated by the battery under test during the electrochemical reaction, and the concentration polarization internal resistance represents the internal resistance increment caused by the uneven distribution of ion concentration inside the battery under test; wherein the multi-dimensional impedance characteristic parameters include the constant current equivalent DC internal resistance, the ohmic internal resistance, the electrochemical polarization internal resistance, and the concentration polarization internal resistance.

[0033] Optionally, the constant current charging stage refers to the phase during battery charging where the charging current remains constant. During this stage, by monitoring the input current I and terminal voltage U of the battery under test, and obtaining the theoretical open-circuit voltage OCV from the open-circuit voltage-state-of-charge (OCV-SOC) lookup table, the constant current equivalent DC internal resistance of the battery under test can be calculated. This step provides a preliminary assessment of the instantaneous impedance state of the battery under test. The magnitude of the resistance can indirectly reflect the state of the electrochemically active materials inside the battery. Applying an active diagnostic signal refers to observing the battery's instantaneous response during charging by suddenly interrupting the current (or changing the current mode). At the moment of current interruption, the battery terminal voltage will experience a step drop; this voltage change can be used to quickly estimate the ohmic internal resistance of the battery under test. Ohmic internal resistance reflects the resistive characteristics of the internal conductors and contact surfaces of a battery, and is another important indicator of battery health. The electrochemical polarization internal resistance of the battery under test is obtained during a preset voltage recovery period after an interruption. and concentration polarization internal resistance Specifically, during the electrochemical reaction process, due to phenomena such as charge transfer and interfacial reactions, an additional increase in internal resistance is generated in the battery. This internal resistance is called electrochemical polarization resistance. It reflects the reaction rate and interfacial stability of the active materials inside the battery. Concentration polarization resistance is caused by the uneven distribution of ion concentration inside the battery. This unevenness leads to a decrease in battery performance, manifested as an increase in battery internal resistance. Measuring concentration polarization resistance helps to determine the uniformity of the distribution of electrolyte and active materials inside the battery under test. During a period of time after current interruption (preset voltage recovery period), by collecting the relaxation curve V(t) of the battery terminal voltage changing with time, a second-order RC equivalent circuit model can be used for fitting, thereby identifying the electrochemical polarization resistance. and concentration polarization internal resistance In this embodiment, multi-dimensional impedance characteristic parameters are set, including the constant current equivalent DC internal resistance, ohmic internal resistance, electrochemical polarization internal resistance, and concentration polarization internal resistance mentioned above. These parameters together constitute a feature vector that comprehensively reflects the internal state of the battery, providing rich information for the subsequent calculation of the second safety weight.

[0034] The method described in this embodiment creates conditions outside of normal battery operation to assess the dynamic characteristics inside the battery, particularly the stability of electrochemical reactions and ion transport processes. The measurement and analysis of these internal parameters fills a gap in battery management strategies related to battery internal state monitoring, providing strong data support for a comprehensive assessment of battery safety status. Combined with the assessment of external operating parameters, it enables precise monitoring and early warning of battery safety status.

[0035] Optionally, an active diagnostic approach can be used to delve deeper into and identify the core characteristic parameters representing the internal electrochemical state of the battery to obtain a comprehensive internal state feature vector. First, the algorithm calculates the constant-current equivalent DC internal resistance RDC online. During the constant-current charging phase, based on the real-time input charging current I, terminal voltage U, and the theoretical open-circuit voltage OCV retrieved from the preset OCV-SOC lookup table, RDC is calculated using the following formula. DC : Secondly, the core parameters are identified based on the current interruption method. Figure 2 This is an optional current interruption identification diagram according to an embodiment of the present invention, the process of which can be referred to Figure 2 This will be explained. The algorithm's input is high-frequency voltage sampling data during the instant of current interruption and for a period of time thereafter, i.e., the voltage relaxation curve V(t). (Refer to...) Figure 2 At time t0, the charging current is instantaneously cut off, based on the step drop in voltage at this moment. (i.e., the instantaneous drop from V0 to V1), calculate the ohmic internal resistance R. ohm The formula is as follows: .

[0036] In one optional embodiment, during a preset voltage recovery period after the interruption, the electrochemical polarization internal resistance and concentration polarization resistance of the battery under test are acquired, including: acquiring the voltage curve of the battery under test during the preset voltage recovery period; and fitting the voltage curve using a nonlinear least squares method based on a second-order RC equivalent circuit model to obtain an equivalent model of the voltage curve in the following form: ;in, This represents the actual voltage value of the battery under test at time t after the current interruption. This indicates the voltage value of the battery under test when it reaches a steady state. This indicates the electrochemical polarization voltage drop of the battery under test. This represents the relaxation time constant related to electrochemical polarization. This represents the concentration polarization voltage drop. The relaxation time constant related to concentration polarization is represented; the electrochemical polarization internal resistance is obtained based on the electrochemical polarization voltage drop and the current applied to the cell under test; the concentration polarization resistance is obtained based on the concentration polarization voltage drop and the current applied to the cell under test.

[0037] Optional, as before Figure 2 As shown, after time t1, a corresponding 20-second period can be taken. The collected voltage natural recovery (relaxation) curve V(t) (i.e. Figure 2 The slow recovery curve segment marked as "polarization resistance" is fitted using a nonlinear least squares method based on a second-order RC equivalent circuit model, resulting in the equivalent model shown in the above equation. Through fitting calculations, the total voltage drop representing electrochemical polarization and concentration polarization can be accurately identified. and The algorithm then calculates the polarization resistance R of the two cores. p1 and R p2 The calculation formulas are as follows: The final output is a feature vector [R] containing the core state of the battery's internal structure. DC , Rohm , R p1 , R p2 This provides rich and in-depth input information for subsequent fusion evaluation.

[0038] By utilizing the voltage relaxation characteristics in active diagnostics and combining them with a second-order RC equivalent circuit model, the electrochemical polarization and concentration polarization effects within the battery can be analyzed and quantified in depth. These internal resistance parameters provide direct information on the battery's internal electrochemical reaction characteristics and ion transport efficiency, which is crucial for constructing a multi-dimensional feature vector for battery safety status assessment. Combined with the evaluation of external operating parameters, this comprehensive analysis method can more comprehensively and accurately assess the overall health status and safety risks of the battery, providing strong support for battery safety management and fault prediction.

[0039] Step S108: Based on multiple internal operating parameters, obtain the second safety weight of the battery under test;

[0040] Optionally, by analyzing multi-dimensional impedance characteristic parameters, these parameters can be transformed into a quantitative evaluation of the battery's internal safety state—a second safety weight. This weight can be understood as an internal comprehensive safety weight, which can be used to reveal the stability of the battery's internal electrochemical processes and whether there are potential failure risks.

[0041] In one optional embodiment, obtaining the second safety weight of the battery under test based on multiple internal operating parameters includes: performing an equivalent transformation on the multi-dimensional impedance characteristic parameters based on a preset benchmark operating condition to obtain multiple equivalent resistance values ​​under the preset benchmark operating condition; obtaining multiple internal safety weights based on the multiple equivalent resistance values, wherein the multiple internal safety weights correspond one-to-one with the multiple equivalent resistance values; and performing a multiplication operation on the multiple internal safety weights to obtain the second safety weight.

[0042] Optionally, multi-dimensional impedance characteristic parameters obtained through active diagnostics (such as constant current equivalent DC internal resistance, ohmic internal resistance, electrochemical polarization internal resistance, concentration polarization internal resistance, etc.) are converted to a pre-set standard operating condition, such as SOC=50%, charge rate C=1, and temperature T=25°C. This conversion ensures the comparability of impedance parameter assessments under different operating conditions, avoiding safety assessment deviations due to changes in operating conditions. After conversion to the baseline operating condition, each impedance characteristic parameter corresponds to an equivalent resistance value. These equivalent resistance values ​​reflect the impedance state of each electrochemical stage within the battery under the baseline operating condition and form the basis for subsequent calculations of internal safety weights. For each equivalent resistance value, it is converted into an internal safety weight between 0 and 1. The calculation logic for the weight is similar to that of the external safety weight, where 0 indicates severe anomaly and 1 indicates complete normality. Thus, each equivalent resistance value corresponds to an internal safety weight, which describes the safety state of a specific electrochemical process within the battery. Furthermore, by multiplying all internal safety weights, a second safety weight that comprehensively reflects the overall internal safety status of the battery can be obtained. This method can improve the accuracy and reliability of battery safety status assessment, effectively monitor the internal health status of the battery, and provide a scientific basis for battery safety management and fault early warning.

[0043] In one optional embodiment, when the preset reference operating condition includes a preset state of charge, a preset ambient temperature, and a preset charging rate, the multi-dimensional impedance characteristic parameters are equivalently transformed based on the preset reference operating condition to obtain multiple equivalent resistance values ​​of the preset reference operating condition. This includes: equivalently transforming any impedance characteristic parameter among the multi-dimensional impedance characteristic parameters in the following manner to obtain the equivalent resistance value of any impedance characteristic parameter:

[0044] ;in, This represents the equivalent resistance value of any impedance characteristic parameter. This represents the reference voltage value of the battery under test under preset reference operating conditions. Indicates the preset state of charge. Indicates the preset ambient temperature. This indicates the preset charging rate. This represents the actual state of charge of the battery under test at the time of acquisition of any impedance characteristic parameter. This represents the actual ambient temperature of the battery under test at the time of acquisition of any impedance characteristic parameter. This represents the actual charging rate of the battery under test when any impedance characteristic parameter is acquired; multiple equivalent resistance values ​​are obtained by using the method of obtaining the equivalent resistance value of any impedance characteristic parameter.

[0045] Optionally, for the equivalent transformation of any impedance characteristic parameter, the above transformation method is used. The basic idea of ​​this equivalent transformation is to adjust the actual measured impedance characteristic parameter value to a set standard operating condition, thereby eliminating the influence of differences in battery operating conditions. The selection of the standard operating condition should reflect the typical operating state of the battery as much as possible to facilitate subsequent safety weight calculation and analysis. According to the above equivalent transformation formula, each multi-dimensional impedance characteristic parameter is subjected to the same standardization process to obtain a set of equivalent resistance values ​​under the preset benchmark operating conditions. These equivalent resistance values ​​will be used to calculate the internal safety weight because they eliminate the influence of different states of charge, temperatures, and charging rates on impedance measurements, providing a fairer and more consistent evaluation basis. Through the above standardization process, it can be ensured that the evaluation results of the multi-dimensional impedance characteristic parameters of the battery under test under different operating conditions can be compared with each other, avoiding deviations in safety status evaluation caused by changes in operating conditions. The obtained equivalent resistance values ​​are further used to calculate the internal safety weight, which, combined with the evaluation of external operating parameters, constitutes a comprehensive evaluation of the battery safety status. This can improve the accuracy and reliability of battery health management and provide a scientific basis for early warning and preventive maintenance of the battery system.

[0046] In one optional embodiment, multiple internal security weights are obtained based on multiple equivalent resistance values, including: obtaining any internal security weight based on any one of the multiple equivalent resistance values ​​in the following manner: ;in, Represents any internal security weight, reflecting the basis of The safety of the internal electrochemical state of the battery; Represents any equivalent resistance value. This indicates the preset safety resistance value, meaning that the battery is considered to be in a safe operating range below this resistance value. The preset safety resistance value is the highest temperature that supports the safe operation of the battery under test. A preset failure resistance value is set, meaning that above this resistance value, the battery is considered to have a serious electrochemical problem that may lead to battery failure. The preset failure resistance value is the lowest resistance value that will cause the battery under test to fail. Multiple internal safety weights are obtained by using any internal safety weight.

[0047] Optional, if Less than or equal to ,but A value of 1 indicates The battery is within a safe range and its internal electrochemical state is good. If Between and Between, A linearly decreasing value between 1 and 0, depending on... and and The distance between them. This linearly decreasing weight value reflects... The degree of deterioration of the battery's internal safety condition as it approaches its failure resistance value. If Greater than or equal to ,but A value of 0 indicates The battery has exceeded its safe operating range, indicating a serious internal problem that requires immediate attention. For each impedance characteristic parameter, the equivalent resistance value is calculated using the same method to obtain the corresponding internal safety weight. This yields a set of internal safety weights, each reflecting the safety status of a specific electrochemical process within the battery under test.

[0048] By employing the aforementioned piecewise linear mapping function, a method for quantitatively assessing the internal electrochemical state of a battery is provided. This method transforms multi-dimensional impedance characteristic parameters into internal safety weights, which are then integrated into a comprehensive assessment of the battery's safety state. This process not only considers the current impedance state of the battery under test but also incorporates standardized operating conditions, thereby ensuring the comparability and objectivity of the assessment results for the internal state of the battery under test under different operating conditions. This provides crucial information for the health management of the battery under test.

[0049] Step S110: Based on the first safety weight and the second safety weight, obtain the safety status assessment result of the battery under test.

[0050] Optionally, the first safety weight and the second safety weight can be combined using a comprehensive evaluation strategy (which may include, but is not limited to, weighted averaging, fuzzy logic fusion, or other statistical methods) to generate a comprehensive assessment result reflecting the battery's safety status, namely, a State of Safety (SOS) score. This SOS score integrates information on external abuse and internal electrochemical state, providing precise guidance for the safety management and maintenance of the battery under test. Based on different SOS score levels, corresponding levels of safety warnings and protective measures can be automatically triggered, effectively preventing serious safety events such as battery thermal runaway.

[0051] Through the above steps S102 to S110, the goal of comprehensively assessing the battery safety status can be achieved by combining external operating parameter monitoring with active diagnosis of internal multi-dimensional impedance characteristic parameters, calculating the first safety weight and the second safety weight respectively, and merging them. This improves the accuracy and comprehensiveness of the battery safety status and solves the technical problem in related technologies where the factors considered in battery safety status assessment are not comprehensive, resulting in low accuracy of battery safety status assessment.

[0052] Based on the above embodiments and optional embodiments, the present invention proposes an optional implementation method. Figure 3This is a flowchart of an optional battery safety status assessment method according to an embodiment of the present invention, such as... Figure 3 As shown, the method includes:

[0053] S1. Based on the degree of influence of different factors on the battery safety status and their ease of measurement, explicit abuse parameters characterizing the external risks of the battery are first selected. In this embodiment, the battery deformation is selected based on whether the battery under test has undergone continued mechanical abuse, the battery temperature parameter is selected based on whether thermal abuse has occurred, and voltage, current, etc. are selected as explicit abuse parameters (i.e., the external operating parameters of the battery under test) based on whether electrical abuse has occurred.

[0054] S2 represents a set of real-time physical quantity data from routine monitoring of the battery system (battery under test), such as an array of temperature values ​​from multiple monitoring points, an array of voltage values ​​from multiple cells of the battery under test, and signals characterizing physical deformation. The core logic of the algorithm is to transform these physical quantities into a dimensionless safety weight between 0 and 1 through a standardized risk mapping function. This function performs piecewise linear calculations based on preset "safety thresholds" and "failure thresholds" for various parameters.

[0055] Figure 4 This is an optional flowchart for determining the first safety weight according to an embodiment of the present invention. The purpose of this step is to quantify external, directly observable physical risks into a unified risk weight (i.e., the first safety weight). The input of this algorithm comes from a set of real-time physical quantity data routinely monitored by the battery management system of the battery under test, such as an array of temperature values ​​from multiple monitoring points, an array of voltage values ​​from multiple cells, and signals characterizing physical deformation (i.e., the deformation values ​​corresponding to each of the multiple deformation sampling points). The core logic of this algorithm is to transform these physical quantities into a dimensionless safety weight between 0 and 1 through a standardized risk mapping function. This function is based on piecewise linear calculations based on preset "safety thresholds" and "failure thresholds" (such as preset safe temperature and preset failure temperature) for various parameters. Taking temperature as an example, the maximum value is taken for multiple temperature points. The formula is as follows.

[0056] If for the maximum temperature T max Within a safe range: ,So =1;

[0057] If it is within the safe zone and the failure boundary: ,but ;

[0058] If the failure boundary is exceeded: ,So ;

[0059] Among them, the safety boundary is The failure boundary is The corresponding security weight is

[0060] The voltage parameters are obtained using the same method described above. For battery deformation, obtain the safety weight. Subsequently, the first safety weight was calculated by multiplying all independent weights together to reflect the principle that any single risk will affect overall safety. Its formula is: Based on the above steps, the first security weight is obtained. If the boundary is exceeded, the current security state can be determined to be 0, without needing to proceed to step S3 for active diagnosis and probing of internal information, thus reducing the complexity of use.

[0061] S3, and other internal parameters such as battery aging state, can be obtained through implicit characteristic parameters characterizing the battery's internal state. During the charging process of the battery under test, a preset active diagnostic electrical signal sequence is applied to the battery by controlling the charging device, and battery response data under this sequence is collected. Based on the response data, multi-dimensional impedance characteristic parameters that can characterize the state of different electrochemical stages inside the battery are calculated.

[0062] In this step, we delve into and identify the core characteristic parameters representing the internal electrochemical state of the battery to obtain a comprehensive internal state feature vector. First, the algorithm calculates the constant-current equivalent DC internal resistance R online. DC During the constant current charging phase, based on the real-time input charging current I, terminal voltage U, and the theoretical open-circuit voltage OCV retrieved from the preset OCV-SOC lookup table, RDC is calculated using the following formula: ;

[0063] Secondly, the core parameters are identified based on the current interruption method, and the process can be referred to... Figure 2 This will be explained. The algorithm's input is high-frequency voltage sampling data during the instant of current interruption and for a period of time thereafter, i.e., the voltage relaxation curve V(t). (Refer to...) Figure 2 At time t0, the charging current is instantaneously cut off, and the voltage drops by a step ΔV at this moment. ohm (i.e., the instantaneous drop from V0 to V1), calculate the ohmic internal resistance R. ohm The formula is as follows: .

[0064] Next, after time t1, a period of approximately 20 seconds is typically taken. The collected voltage natural recovery (relaxation) curve V(t) (i.e. Figure 2 The slow recovery curve segment marked as "polarization resistance" is fitted using a nonlinear least squares method based on a second-order RC equivalent circuit model. The mathematical expression of this model is: .

[0065] Through fitting calculations, the total voltage drop ΔV, representing electrochemical polarization and concentration polarization, can be accurately identified. p1 With ΔV p2 The algorithm then calculates the polarization resistance of the two cores. and The calculation formulas are as follows: The final output is a feature vector containing the core state of the battery's internal structure. , , , This provides rich and in-depth input information for subsequent fusion evaluation.

[0066] S4. To address the impact of different ambient temperatures and charging rates on the battery's current state of charge (SOC), and to achieve a unified measurement across operating conditions, this embodiment first normalizes the calculated multi-dimensional impedance characteristic parameters based on a preset healthy battery benchmark model to eliminate the influence of operating conditions. Subsequently, the normalized implicit characteristic parameters are transformed into safety sub-indicators characterizing specific internal safety dimensions.

[0067] In this step, the internal state feature vector [R] DC , R ohm , R p1 , R p2 Standardization conversion is performed to eliminate interference from operating conditions such as battery SOC, charge rate (C-rate), and real-time temperature (T), ensuring the longitudinal comparability of evaluation results. The core of this conversion algorithm is the need to pre-establish a multi-dimensional healthy battery benchmark model in the storage module. This model accurately describes the benchmark values ​​of various internal resistances of the battery under different combinations of battery SOC, charge rate, and real-time temperature conditions. The algorithm first obtains the current time... , , The measured resistance value is used, and a unified comparison benchmark is preset, such as the standard reference state of charge. =0.5, ambient temperature =25, charging rate =1C. The algorithm converts the currently measured resistance value to the equivalent resistance value under standard reference operating conditions using the following formula:

[0068]

[0069] This conversion will be applied to the resistance vector obtained in the second step, ultimately outputting an equivalent eigenvector that completely eliminates the influence of operating conditions: [ , , , ].

[0070] S5, the multiple internal safety sub-indicators obtained in the previous step are fused together to calculate the second safety weight characterizing the overall internal state of the battery. Finally, through a specific fusion strategy, the first security weight representing external risk ( ) and the second security weight representing the internal state ( By combining these factors, a final and comprehensive State of Safety (SOS) assessment value is generated. Based on this SOS value, the system classifies the battery into a refined safety level (e.g., safe, concern, warning, danger) and triggers corresponding response measures.

[0071] In this step, these physically meaningful equivalent resistance values ​​are converted into safety scores between 0 and 1. The calculation method here is logically identical to the piecewise linear mapping function used in the first step to calculate the explicit risk weights. Taking RDC as an example, safety and failure boundaries are set. If for R... DC Within a safe range: ,So =1;

[0072] If it is within the safe zone and the failure boundary: ,but ;

[0073] If the failure boundary is exceeded: ,So .

[0074] Finally, by calculating the safety index corresponding to different resistances within the resistance vector, the internal comprehensive safety weight can be obtained. The calculation method is the same as that for explicit parameters. Finally, the algorithm applies the external risk weights obtained in the first step. With internal security weights The data is then integrated to obtain the final State of Security (SOS) score, which is calculated using the following formula: .

[0075] The final SOS output from this step is a comprehensive security status value in the range [0, 1]. This value will be directly used for subsequent security policy classification and handling.

[0076] Compared with related technologies, this embodiment combines passive monitoring of external risks with active diagnosis of internal conditions, which helps to achieve battery safety assessment and early safety warning.

[0077] This embodiment also provides a battery safety status assessment device, which is used to implement the above embodiments and preferred embodiments, and will not be repeated as already described. As used below, the terms "module" and "device" can refer to a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0078] According to an embodiment of the present invention, an apparatus embodiment for implementing the above-described battery safety status assessment method is also provided. Figure 5 This is a schematic diagram of a battery safety status assessment device according to an embodiment of the present invention, as shown below. Figure 5 As shown, the battery safety status assessment device includes: an external parameter acquisition module 500, a first weight determination module 502, an internal parameter acquisition module 504, a second weight determination module 506, and a safety status assessment module 508, wherein:

[0079] The external parameter acquisition module 500 is used to acquire multiple external operating parameters of the battery under test. These multiple external operating parameters include the temperature values ​​corresponding to multiple monitoring points on the battery under test, the voltage values ​​corresponding to multiple cells, and the deformation values ​​corresponding to multiple deformation sampling points.

[0080] The first weight determination module 502 is connected to the external parameter acquisition module 500 and is used to obtain the first safety weight of the battery under test based on multiple external operating parameters.

[0081] The internal parameter acquisition module 504 is connected to the first weight determination module 502 and is used to acquire multiple internal operating parameters of the battery under test. Among them, the multiple internal operating parameters include multi-dimensional impedance characteristic parameters. The multi-dimensional impedance characteristic parameters are obtained by applying an active diagnostic signal to the battery under test. The active diagnostic signal is used to control the instantaneous interruption of the current.

[0082] The second weight determination module 506 is connected to the internal parameter acquisition module 504 and is used to obtain the second safety weight of the battery under test based on multiple internal operating parameters.

[0083] The safety status assessment module 508 is connected to the second weight determination module 506 and is used to obtain the safety status assessment result of the battery under test based on the first safety weight and the second safety weight.

[0084] It should be noted that the above modules can be implemented by software or hardware. For example, for the latter, it can be implemented in the following ways: the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0085] It should be noted that the external parameter acquisition module 500, the first weight determination module 502, the internal parameter acquisition module 504, the second weight determination module 506, and the security status assessment module 508 correspond to steps S102 to S110 in the embodiments. The instances and application scenarios implemented by the above modules and corresponding steps are the same, but are not limited to the content disclosed in the above embodiments. It should be noted that the above modules, as part of the device, can run in a computer terminal.

[0086] It should be noted that the optional or preferred implementation methods of this embodiment can be found in the relevant descriptions in the embodiments, and will not be repeated here.

[0087] The aforementioned battery safety status assessment device may further include a processor and a memory. The aforementioned external parameter acquisition module 500, first weight determination module 502, internal parameter acquisition module 504, second weight determination module 506, safety status assessment module 508, etc., are all stored in the memory as program modules, and the processor executes the aforementioned program modules stored in the memory to realize the corresponding functions.

[0088] The processor contains a core that retrieves the corresponding program modules from memory. One or more cores may be configured. Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory includes at least one memory chip.

[0089] According to an embodiment of this application, an embodiment of a non-volatile storage medium is also provided. Optionally, in this embodiment, the non-volatile storage medium includes a stored program, wherein, when the program runs, it controls the device containing the non-volatile storage medium to execute any of the battery safety status assessment methods described above.

[0090] Optionally, in this embodiment, the non-volatile storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals, and the non-volatile storage medium includes stored programs.

[0091] Optionally, a program that controls the device containing the non-volatile storage medium to execute any of the battery safety status assessment method steps described above during program execution.

[0092] According to an embodiment of this application, an embodiment of a processor is also provided. Optionally, in this embodiment, the processor is used to run a program, wherein the program executes any of the battery safety status assessment methods described above.

[0093] According to an embodiment of this application, an embodiment of a computer program product is also provided, which, when executed on a data processing device, is adapted to execute a program that initializes the battery safety status assessment method steps described above.

[0094] Optionally, when the above-mentioned computer program product is executed on a data processing device, it is suitable for executing a program that initializes the battery safety status assessment method steps described above.

[0095] This invention provides an electronic device, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps of any of the above-described battery safety status assessment methods.

[0096] The order of the above embodiments of the present invention is merely for description and does not represent the superiority or inferiority of the embodiments.

[0097] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0098] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of modules described above can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between modules, and may be electrical or other forms.

[0099] The modules described above as separate components may or may not be physically separate. Similarly, the components shown as modules may or may not be physical modules; they may be located in one place or distributed across multiple modules. Some or all of the modules can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0100] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0101] If the aforementioned integrated modules are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable non-volatile storage medium. Based on this understanding, the technical solution of this invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a non-volatile 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 of the various embodiments of this invention. The aforementioned non-volatile storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0102] The above are merely preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for assessing the safety status of a battery, characterized in that, include: Acquire multiple external operating parameters of the battery under test, wherein the multiple external operating parameters include the temperature value corresponding to each of the multiple monitoring points on the battery under test, the voltage value corresponding to each of the multiple cells, and the deformation value corresponding to each of the multiple deformation sampling points. Based on the aforementioned multiple external operating parameters, the first safety weight of the battery under test is obtained; Multiple internal operating parameters of the battery under test are obtained, including multi-dimensional impedance characteristic parameters. These multi-dimensional impedance characteristic parameters are obtained by applying an active diagnostic signal to the battery under test. The active diagnostic signal is used to control the instantaneous interruption of the current. Based on the aforementioned multiple internal operating parameters, the second safety weight of the battery under test is obtained; The safety status assessment result of the battery under test is obtained based on the first safety weight and the second safety weight.

2. The method according to claim 1, characterized in that, The first safety weight of the battery under test is obtained based on the multiple external operating parameters, including: Based on the multiple external operating parameters, multiple external safety weights are obtained, including temperature safety weight, voltage safety weight, and deformation safety weight. The first security weight is obtained by multiplying the multiple external security weights together.

3. The method according to claim 2, characterized in that, The multiple external security weights obtained based on the multiple external operating parameters include: Based on the temperature values ​​corresponding to each of the multiple monitoring points, the temperature safety weight is obtained in the following manner: Determine the maximum temperature value among the temperature values ​​corresponding to each of the multiple monitoring points; Based on the maximum temperature value, the temperature safety weight is obtained in the following manner: ； in, This represents the temperature safety weight. This indicates the maximum temperature value. This indicates the preset safe temperature, which is the highest temperature at which the battery under test can operate safely. This indicates the preset failure temperature, which is the lowest temperature at which the battery under test will fail. Based on the voltage values ​​corresponding to each of the multiple battery cells, the voltage safety weight is obtained in the same way as the temperature safety weight. Based on the deformation values ​​corresponding to the multiple deformation sampling points, the deformation safety weight is obtained in the same way as the temperature safety weight.

4. The method according to claim 1, characterized in that, The acquisition of multiple internal operating parameters of the battery under test includes: During the constant current charging phase of the battery under test, the constant current equivalent DC internal resistance of the battery under test is obtained. At the moment of interruption when an active diagnostic signal is applied to the battery under test, causing a current interruption, the ohmic internal resistance of the battery under test is obtained. During the preset voltage recovery period after the interruption time, the electrochemical polarization internal resistance and concentration polarization internal resistance of the battery under test are obtained. The electrochemical polarization internal resistance represents the internal resistance increment generated by the battery under test during the electrochemical reaction, and the concentration polarization internal resistance represents the internal resistance increment caused by the uneven distribution of ion concentration inside the battery under test. The multi-dimensional impedance characteristic parameters include the constant current equivalent DC internal resistance, the ohmic internal resistance, the electrochemical polarization internal resistance, and the concentration polarization internal resistance.

5. The method according to claim 4, characterized in that, During the preset voltage recovery period after the interruption, the electrochemical polarization resistance and concentration polarization resistance of the battery under test are acquired, including: Obtain the voltage curve of the battery under test during the preset voltage recovery period; The voltage curve is fitted using a nonlinear least squares method based on a second-order RC equivalent circuit model, resulting in an equivalent model of the voltage curve in the following form: ； in, This represents the actual voltage value of the battery under test at time t after the current interruption. This represents the voltage value when the voltage of the battery under test reaches a stable state. This indicates the electrochemical polarization voltage drop of the battery under test. This represents the relaxation time constant related to electrochemical polarization. This represents the concentration polarization voltage drop. This represents the relaxation time constant related to concentration polarization; The electrochemical polarization internal resistance is obtained based on the electrochemical polarization voltage drop and the current applied to the battery under test. The concentration polarization resistance is obtained based on the concentration polarization voltage drop and the current applied to the battery under test.

6. The method according to claim 1, characterized in that, The second safety weight of the battery under test, obtained based on the multiple internal operating parameters, includes: The multi-dimensional impedance characteristic parameters are equivalently transformed based on a preset benchmark operating condition to obtain multiple equivalent resistance values ​​under the preset benchmark operating condition. Based on the multiple equivalent resistance values, multiple internal security weights are obtained, wherein each of the multiple internal security weights corresponds one-to-one with the multiple equivalent resistance values; The second security weight is obtained by multiplying the multiple internal security weights.

7. The method according to claim 6, characterized in that, When the preset reference operating condition includes a preset state of charge, a preset ambient temperature, and a preset charging rate, the equivalent transformation of the multi-dimensional impedance characteristic parameters based on the preset reference operating condition yields multiple equivalent resistance values ​​for the preset reference operating condition, including: The equivalent resistance value of any impedance characteristic parameter among the multi-dimensional impedance characteristic parameters is obtained by performing an equivalent transformation on any of the impedance characteristic parameters in the following manner: ； in, This represents the equivalent resistance value of any of the impedance characteristic parameters. This indicates the reference voltage value of the battery under test under the preset reference operating condition. This indicates the preset state of charge. This indicates the preset ambient temperature. This indicates the preset charging rate. This indicates the actual state of charge of the battery under test at the time of acquisition of any of the impedance characteristic parameters. This represents the actual ambient temperature of the battery under test at the time of acquisition of any of the impedance characteristic parameters. This indicates the actual charging rate of the battery under test when any of the impedance characteristic parameters is acquired; The plurality of equivalent resistance values ​​are obtained by using the equivalent resistance value of any of the impedance characteristic parameters.

8. The method according to claim 6, characterized in that, Based on the multiple equivalent resistance values, multiple internal safety weights are obtained, including: Based on any one of the plurality of equivalent resistance values, any internal safety weight is obtained in the following manner: ； in, Represents any of the aforementioned internal security weights. This represents any of the aforementioned equivalent resistance values. This indicates a preset safety resistance value, which is the highest temperature at which the battery under test can operate safely. The preset failure resistance value is the minimum resistance value that would cause the battery under test to fail. The plurality of internal security weights are obtained by using the method of obtaining any one of the internal security weights.

9. A battery safety status assessment device, characterized in that, include: An external parameter acquisition module is used to acquire multiple external operating parameters of the battery under test. The multiple external operating parameters include the temperature values ​​corresponding to multiple monitoring points on the battery under test, the voltage values ​​corresponding to multiple cells, and the deformation values ​​corresponding to multiple deformation sampling points. The first weight determination module is used to obtain the first safety weight of the battery under test based on the multiple external operating parameters. An internal parameter acquisition module is used to acquire multiple internal operating parameters of the battery under test, wherein the multiple internal operating parameters include multi-dimensional impedance characteristic parameters, which are obtained by applying an active diagnostic signal to the battery under test, and the active diagnostic signal is used to control the instantaneous interruption of the current. The second weight determination module is used to obtain the second safety weight of the battery under test based on the multiple internal operating parameters. The safety status assessment module is used to obtain the safety status assessment result of the battery under test based on the first safety weight and the second safety weight.

10. An electronic device, characterized in that, It includes one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the battery safety status assessment method according to any one of claims 1 to 8.

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