Method and device for determining safety state index of battery pack and electronic equipment

Abstract

The invention discloses a method and a device for determining a safety state index of a battery pack and electronic equipment. The method comprises the following steps: acquiring battery data of a battery pack; determining a plurality of feature items used for evaluating the safety state of the battery under the environment parameters; determining a feature sequence according to the subjective evaluation data corresponding to the plurality of feature items; determining information utility values respectively corresponding to the plurality of feature items according to the plurality of feature values respectively corresponding to the plurality of feature items; determining subjective weights respectively corresponding to the plurality of feature items according to the feature sequence, and determining objective weights respectively corresponding to the plurality of feature items according to the adjustment coefficient item and the information utility value; and determining the safety state index of the battery pack according to the subjective weight, the objective weight and the plurality of feature values. The technical problem that the safety state of the battery pack cannot be accurately detected when the safety state of the battery pack is detected in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the field of data processing, and in particular to a method, device and electronic device for determining a safety status index of a battery pack. Background Art

[0002] In the field of new energy, the safety of battery pack applications has received increasing attention. For example, battery packs generate a lot of heat during operation. If the temperature inside the battery pack is too high or the heat dissipation is poor, thermal runaway may occur, leading to battery pack failure or even explosion. How to accurately detect the safety status of the battery pack has become a challenge. Although traditional methods can monitor basic operating parameters, there is a problem that the safety status of the battery pack cannot be accurately detected during the safety status detection of the battery pack.

[0003] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0004] Embodiments of the present invention provide a method, device and electronic device for determining a safety status index of a battery pack, so as to at least solve the technical problem in the related art that the safety status of the battery pack cannot be accurately detected during the safety status detection of the battery pack.

[0005] According to one aspect of an embodiment of the present invention, a method for determining a safety status index of a battery pack is provided, comprising: acquiring battery data of a battery pack, wherein the battery data comprises environmental parameters, and the battery pack comprises a plurality of target batteries; determining a plurality of feature items for evaluating the safety status of the battery under the environmental parameters; determining a feature sequence according to subjective evaluation data corresponding to the plurality of feature items of the battery pack, wherein the feature sequence comprises the plurality of feature items sorted by importance index; determining information utility values ​​corresponding to the plurality of feature items of the battery pack according to a plurality of feature values ​​corresponding to the plurality of target batteries under the plurality of feature items, wherein the information utility values ​​are used to indicate the importance of the feature items, wherein the plurality of feature values ​​correspond one-to-one to the plurality of feature items; determining subjective weights corresponding to the plurality of feature items of the battery pack according to the feature sequence, and determining objective weights corresponding to the plurality of feature items of the battery pack according to adjustment coefficient items and the information utility values ​​corresponding to the plurality of feature items of the battery pack; determining the safety status index of the battery pack according to the subjective weights, objective weights and a plurality of feature values ​​corresponding to the plurality of feature items of the battery pack.

[0006] Optionally, the safety status index of the battery pack is determined based on the subjective weights, objective weights and multiple characteristic values ​​respectively corresponding to the battery pack under the multiple characteristic items, including: determining a subjective weight variable and an objective weight variable; linearly combining the subjective weights and objective weights respectively corresponding to the battery pack under the multiple characteristic items based on the subjective weight variable and the objective weight variable to obtain a linear weight function; determining the balance weights respectively corresponding to the battery pack under the multiple characteristic items based on the linear weight function; determining the safety status index of the battery pack based on the balance weights and multiple characteristic values ​​respectively corresponding to the battery pack under the multiple characteristic items.

[0007] Optionally, based on the subjective weight variable and the objective weight variable, the subjective weights and objective weights corresponding to the battery pack under the multiple feature items are linearly combined to obtain a linear weight function, including: determining the product of the subjective weight variable and a first transposed vector to obtain a first sub-function, wherein the first transposed vector is a vector obtained by transposing the vectors corresponding to the subjective weights of the battery pack under the multiple feature items; determining the product of the objective weight variable and a second transposed vector to obtain a second sub-function, wherein the second transposed vector is a vector obtained by transposing the vectors corresponding to the objective weights of the battery pack under the multiple feature items; determining a target vector, wherein the target vector includes one of the following: vectors corresponding to the subjective weights of the battery pack under the multiple feature items, vectors corresponding to the objective weights of the battery pack under the multiple feature items; obtaining the linear weight function based on the first sub-function, the second sub-function and the target vector.

[0008] Optionally, based on the multiple characteristic values ​​respectively corresponding to the multiple target batteries under the multiple characteristic items, the information utility values ​​respectively corresponding to the battery pack under the multiple characteristic items are determined, including: based on the multiple characteristic values ​​respectively corresponding to the multiple target batteries under the multiple characteristic items, the multiple trend indicators respectively corresponding to the multiple target batteries under the multiple characteristic items are determined, wherein the trend indicators are determined based on the current indicator values ​​of the corresponding target batteries under the corresponding characteristic items, and the maximum indicator values ​​and the minimum indicator values ​​of the multiple target batteries under the corresponding characteristic items; based on the multiple trend indicators respectively corresponding to the multiple target batteries under the multiple characteristic items, the information utility values ​​respectively corresponding to the battery pack under the multiple characteristic items are determined.

[0009] Optionally, according to the multiple trend indicators respectively corresponding to the multiple target batteries under the multiple feature items, the information utility values ​​respectively corresponding to the battery pack under the multiple feature items are determined, including: according to the multiple trend indicators respectively corresponding to the multiple target batteries under the multiple feature items, the information entropy values ​​respectively corresponding to the battery pack under the multiple feature items are determined, wherein the information entropy values ​​are used to represent the discrete degree of the feature value under the corresponding feature item; according to the information entropy values ​​respectively corresponding to the battery pack under the multiple feature items, the information utility values ​​respectively corresponding to the battery pack under the multiple feature items are determined.

[0010] Optionally, based on the feature sequence, determining the subjective weights of the battery pack respectively corresponding to the multiple feature items, including: determining the importance ratio between two adjacent feature items in the feature sequence; determining the subjective weights of the battery pack respectively corresponding to the multiple feature items based on the importance ratio between two adjacent feature items in the feature sequence.

[0011] Optionally, after determining the safety status index of the battery pack according to the subjective weights, objective weights and multiple characteristic values ​​corresponding to the multiple characteristic items of the battery pack, the method further includes: when the safety status index is lower than a predetermined threshold, determining an alarm indicator item from the multiple characteristic items; and sending an alarm message to a predetermined terminal, wherein the alarm message includes the safety status index, the alarm indicator item, and the indicator value corresponding to the alarm indicator item.

[0012] According to one aspect of an embodiment of the present invention, a device for determining a safety status index of a battery pack is provided, comprising: an acquisition module for acquiring battery data of a battery pack, wherein the battery data comprises environmental parameters, and the battery pack comprises a plurality of target batteries; a first determination module for determining a plurality of feature items for evaluating the safety status of the battery under the environmental parameters; a second determination module for determining a feature sequence according to subjective evaluation data corresponding to the plurality of feature items of the battery pack, wherein the feature sequence comprises the plurality of feature items sorted by importance index; and a third determination module for determining the safety status of the battery pack according to a plurality of feature values ​​corresponding to the plurality of target batteries under the plurality of feature items. The information utility values ​​corresponding to the battery pack under the multiple feature items are respectively used, wherein the information utility values ​​are used to indicate the importance of the feature items, and wherein the multiple feature values ​​correspond one-to-one to the multiple feature items; a fourth determination module is used to determine the subjective weights corresponding to the battery pack under the multiple feature items according to the feature sequence, and to determine the objective weights corresponding to the battery pack under the multiple feature items according to the adjustment coefficient item and the information utility values ​​corresponding to the battery pack under the multiple feature items; a fifth determination module is used to determine the safety status index of the battery pack according to the subjective weights, objective weights and multiple feature values ​​corresponding to the battery pack under the multiple feature items.

[0013] According to one aspect of an embodiment of the present invention, an electronic device is provided, comprising: a processor; and a memory for storing instructions executable by the processor; wherein the processor is configured to execute the instructions to implement the method for determining the safety status index of a battery pack as described in any one of the above.

[0014] According to one aspect of an embodiment of the present invention, a computer-readable storage medium is provided. When instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute any of the above-mentioned methods for determining a safety status index of a battery pack.

[0015] In an embodiment of the present invention, battery data of a battery pack is obtained, wherein the battery data includes environmental parameters, and the battery pack includes multiple target batteries. Multiple feature items for evaluating the safety status of the battery under the environmental parameters are determined. Based on the subjective evaluation data corresponding to the battery pack under the multiple feature items, a feature sequence is determined, wherein the feature sequence includes multiple feature items sorted by importance index. Based on the multiple feature values ​​corresponding to the multiple target batteries under the multiple feature items, the information utility values ​​corresponding to the battery pack under the multiple feature items are determined, wherein the information utility values ​​are used to indicate the importance of the feature items, wherein the multiple feature values ​​correspond to the multiple feature items one by one. Based on the feature sequence, the subjective weights corresponding to the battery pack under the multiple feature items are determined, and based on the adjustment coefficient items and the information utility values ​​corresponding to the battery pack under the multiple feature items, the objective weights corresponding to the battery pack under the multiple feature items are determined. Based on the subjective weights, objective weights and multiple feature values ​​corresponding to the battery pack under the multiple feature items, the safety status index of the battery pack is determined. In this embodiment, based on the battery data of the battery pack, including environmental parameters, multiple feature items for evaluating the battery safety status under environmental parameters are determined. The impact of environmental factors on battery performance and safety assessment is resolved, ensuring the accuracy of battery assessment under different environmental conditions. And according to the battery pack under multiple feature items, the corresponding subjective weights, objective weights and multiple feature values ​​are determined, and the relationship between the subjective level and the objective level is established to ensure the accuracy and comprehensiveness of the evaluation, thereby solving the technical problem in the related technology that the battery pack safety status cannot be accurately detected when the battery pack safety status is detected. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0017] Figure 1 is a flow chart of a method for determining a safety status index of a battery pack according to an embodiment of the present invention;

[0018] Figure 2 is an overall flow chart of a battery safety status assessment system in an optional embodiment of the present invention;

[0019] Figure 3 is a structural diagram of a battery safety status evaluation indicator set in an optional implementation manner of the present invention;

[0020] Figure 4 4 is a structural block diagram of a device for determining a safety status index of a battery pack according to an embodiment of the present invention. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0022] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0023] First, some nouns or terms that appear in the description of the embodiments of the present application are subject to the following explanations:

[0024] Analytic Hierarchy Process (AHP): AHP is a systematic decision support tool that breaks down complex problems into multiple hierarchical structures, including goals, criteria, and alternative plans, and uses a combination of quantitative and qualitative methods to evaluate and compare the importance of elements at each level, thereby helping decision makers to scientifically and systematically analyze and solve complex problems with multi-factor and multi-level characteristics. It is widely used in project management, strategic planning, resource allocation and other fields.

[0025] Entropy method: Entropy method is an objective weighting method based on the principle of information entropy, which is specially used to deal with multi-index evaluation problems. It uses information entropy to measure the amount of information contained in each evaluation index, thereby determining the weight of each index. It does not require artificial setting of weight coefficients and is objective and scientific.

[0026] Example 1

[0027] According to an embodiment of the present invention, an embodiment of a method for determining a safety status index of a battery pack is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in an order different from that shown here.

[0028] Figure 1 is a flow chart of a method for determining a safety status index of a battery pack according to an embodiment of the present invention. Figure 1 As shown, the method comprises the following steps:

[0029] S102, acquiring battery data of a battery pack, wherein the battery data includes environmental parameters, and the battery pack includes a plurality of target batteries;

[0030] In step S102 provided in the present application, battery data of the battery pack is obtained.

[0031] Among them, a battery pack is involved, which is a battery assembly composed of multiple target batteries and used to provide energy. The battery pack can be used in electric vehicles, energy storage systems and various portable electronic devices to provide a more stable and efficient energy supply.

[0032] Among them, battery data is involved, which is parameter data used to reflect the safety status and performance of the battery, such as environmental parameters.

[0033] Among them, environmental parameters are involved, which are environmental data that affect the safety status of the battery pack, such as ambient temperature. The ambient temperature is directly related to the activity and thermal stability of the chemical reactions inside the battery. Too high or too low ambient temperature will have an adverse effect on the safety status of the battery pack.

[0034] Among them, a target battery is involved, which is a battery cell used in a combined battery pack.

[0035] Since the safety status and performance of the battery pack will gradually change during the application of the battery pack, and different environmental conditions have different effects on the safety status of the battery pack, obtaining the battery data of the battery pack will help to fully and accurately grasp the overall safety status of the battery pack, provide a data basis for the subsequent determination of the safety status index of the battery pack, and thus help improve the reliability of the safety status detection of the battery pack.

[0036] S104, determining a plurality of characteristic items for evaluating a battery safety state under environmental parameters;

[0037] In step S104 provided in the present application, a plurality of feature items for evaluating the battery safety status are determined.

[0038] Among them, the battery safety status is involved, and the battery safety status is used to indicate the safety level of the battery pack under environmental parameters.

[0039] Among them, characteristic items are involved, which are items that reflect the battery pack under environmental parameters and are used to evaluate the safety status of the battery pack, such as battery heat generation items, heat dissipation items, etc.

[0040] Due to different environmental parameters, the safety status of the battery pack is different. For example, a high temperature environment will cause the chemical substances inside the battery pack to react, which will cause the battery pack to overheat or even thermal runaway. By determining multiple characteristic items for evaluating the safety status of the battery under environmental parameters, the actual operating status of the battery pack can be accurately reflected, avoiding deviations in the evaluation results of the safety status of the battery pack caused by environmental changes, which will help to analyze and determine the credibility and accuracy of the safety status index of the battery pack in the subsequent process, and thus help to accurately detect the safety status of the battery pack.

[0041] S106, determining a feature sequence according to the subjective evaluation data corresponding to the battery pack under the plurality of feature items, wherein the feature sequence includes the plurality of feature items sorted by importance index;

[0042] In step S106 provided in the present application, a feature sequence is determined.

[0043] Among them, subjective evaluation data is involved, which is obtained by subjective evaluation and is used to reflect the corresponding evaluation data of the safety status of the battery pack under multiple feature items.

[0044] Among them, a feature sequence is involved, which is a sequence of feature items obtained based on subjective evaluation data corresponding to multiple feature items respectively, and the feature sequence includes multiple feature items sorted by importance index.

[0045] Among them, an important index is involved, which is used to indicate the importance of multiple feature items for evaluating the safety status of the battery pack. The ranking results of multiple feature items obtained according to the important index can represent the priority of the feature items in the evaluation process.

[0046] When evaluating the safety status of a battery pack, multiple feature items need to be considered, and the importance of these feature items for evaluating the safety status of the battery pack varies. The higher the importance of the feature item, the higher its accuracy in characterizing the safety status of the battery pack. By introducing subjective evaluation data, the relative importance of each feature item in evaluating the safety status of the battery can be preliminarily analyzed. The feature sequence determined based on these subjective evaluation data, and the feature sequence includes feature items sorted according to importance index, helps to identify feature items with higher importance in evaluating the safety status of the battery pack, thereby clarifying which feature items have higher priority in the evaluation process, which helps to subsequently determine the accuracy of the safety status index of the battery pack, thereby ensuring that the safety status of the battery pack is accurately evaluated.

[0047] S108, determining information utility values ​​corresponding to the battery pack under the multiple feature items according to the multiple feature values ​​corresponding to the multiple target batteries under the multiple feature items, wherein the information utility value is used to indicate the importance of the feature item, wherein the multiple feature values ​​correspond to the multiple feature items one-to-one;

[0048] In step S108 provided in the present application, the information utility values ​​corresponding to the battery pack under multiple feature items are determined.

[0049] Among them, the characteristic value is involved. This characteristic value corresponds to the characteristic item one by one and is used to specifically quantify the value of the corresponding characteristic item. For example, when the characteristic item is the heat generated by the battery, the characteristic value corresponding to the heat generated by the battery is a specific temperature value, indicating the degree of heat generation of the target battery under different conditions. When the characteristic item is the heat dissipation, the corresponding characteristic value can be the heat dissipation rate, which indicates the heat dissipation capacity of the battery under unit temperature change.

[0050] Among them, the information utility value is involved. The information utility value is obtained based on the statistics and analysis of the characteristic values ​​and the association of the corresponding characteristic items, and is used to indicate the importance of the characteristic items to the safety status of the battery pack.

[0051] The information utility values ​​corresponding to the battery pack under multiple feature items are determined based on the multiple feature values ​​corresponding to the multiple target batteries under multiple feature items. This process involves how to extract useful information from a large number of multi-dimensional feature values, and then determine the information utility value of each feature item to the safety status of the battery pack. The effective integration and utilization of this multi-dimensional data of the feature values ​​corresponding to the multiple feature items can more comprehensively and accurately reflect the safety status of the battery pack, and thus help to accurately determine the safety status index of the battery pack in the future. Among them, the information utility value is used to represent the importance of the feature item. Multiple feature values ​​correspond to multiple feature items one by one, which realizes the quantification of the importance of the feature items, so that the degree of influence of the feature items on the safety status of the battery pack can be objectively and accurately reflected, which helps to determine the accuracy of the safety status index of the battery pack in the future, and thus ensure that the safety status of the battery pack is accurately evaluated.

[0052] S110, determining subjective weights corresponding to the battery pack under multiple feature items according to the feature sequence, and determining objective weights corresponding to the battery pack under multiple feature items according to the adjustment coefficient item and the information utility values ​​corresponding to the battery pack under the multiple feature items;

[0053] In step S110 provided in the present application, the subjective weights corresponding to the battery pack under multiple feature items and the objective weights corresponding to the battery pack under multiple feature items are determined.

[0054] Among them, subjective weights are involved. The subjective weights are determined based on the feature sequence and are used to reflect the weights at the subjective judgment level of the degree of influence of multiple feature items on the safety status of the battery pack.

[0055] Among them, an adjustment coefficient term is involved, which is a coefficient term used to correct the objective weight to ensure that the objective weight obtained based on the information utility value is more accurate and in line with the actual situation.

[0056] Among them, objective weights are involved. The objective weights are determined based on the adjustment coefficient and information utility value, and are used to reflect the degree of influence of multiple feature items on the safety status of the battery pack. The objective weights are more objective and based on actual data, rather than being influenced by subjective factors.

[0057] When evaluating the safety status of a battery pack, by determining the subjective weights, the subjective preferences of multiple feature items for the importance of the battery pack safety status can be reflected, ensuring that when evaluating the safety status of a battery pack, the subjective expectations and concerns when detecting the safety status of the battery pack can be taken into account. By determining the objective weights, the actual degree of influence of each feature item on the safety status of the battery pack can be objectively and accurately reflected. And by introducing the adjustment coefficient, the deviation in determining the objective weight based on the information utility value is corrected, making the evaluation results more accurate and reliable. The determination of subjective weights and objective weights together constitute a complete system for the evaluation of the safety status of a battery pack, which not only ensures that the evaluation results can meet the expectations and concerns at the subjective level, but also ensures the accuracy and reliability of the evaluation results, improves the accuracy and reliability of the subsequent determination of the safety status index of the battery pack, and thus helps to accurately detect the safety status of the battery.

[0058] S112, determining a safety status index of the battery pack according to subjective weights, objective weights and multiple characteristic values ​​corresponding to multiple characteristic items of the battery pack.

[0059] In step S112 provided in the present application, the safety status index of the battery pack is determined.

[0060] Among them, the safety status index is involved. The safety status index is obtained based on subjective weights, objective weights and multiple characteristic values ​​corresponding to multiple characteristic items, and is used to quantitatively evaluate the safety status of the battery pack.

[0061] Through the above steps S102-S112, the battery data of the battery pack is obtained, wherein the battery data includes environmental parameters, and the battery pack includes multiple target batteries. Multiple feature items for evaluating the safety status of the battery under the environmental parameters are determined. According to the subjective evaluation data corresponding to the battery pack under the multiple feature items, a feature sequence is determined, wherein the feature sequence includes multiple feature items sorted by importance index. According to the multiple feature values ​​corresponding to the multiple target batteries under the multiple feature items, the information utility values ​​corresponding to the battery pack under the multiple feature items are determined, wherein the information utility values ​​are used to indicate the importance of the feature items, wherein the multiple feature values ​​correspond to the multiple feature items one by one. According to the feature sequence, the subjective weights corresponding to the battery pack under the multiple feature items are determined, and according to the adjustment coefficient items and the information utility values ​​corresponding to the battery pack under the multiple feature items, the objective weights corresponding to the battery pack under the multiple feature items are determined. According to the subjective weights, objective weights and multiple feature values ​​corresponding to the battery pack under the multiple feature items, the safety status index of the battery pack is determined. In this embodiment, based on the battery data of the battery pack, including environmental parameters, multiple feature items for evaluating the battery safety status under environmental parameters are determined. The impact of environmental factors on battery performance and safety assessment is resolved, ensuring the accuracy of battery assessment under different environmental conditions. And according to the battery pack under multiple feature items, the corresponding subjective weights, objective weights and multiple feature values ​​are determined, and the relationship between the subjective level and the objective level is established to ensure the accuracy and comprehensiveness of the evaluation, thereby solving the technical problem in the related technology that the battery pack safety status cannot be accurately detected when the battery pack safety status is detected.

[0062] As an optional embodiment, the safety status index of the battery pack is determined according to the subjective weights, objective weights and multiple characteristic values ​​corresponding to the battery pack under multiple characteristic items, including: determining the subjective weight variable and the objective weight variable; linearly combining the subjective weights and objective weights corresponding to the battery pack under multiple characteristic items according to the subjective weight variable and the objective weight variable to obtain a linear weight function; determining the balance weights corresponding to the battery pack under multiple characteristic items according to the linear weight function; determining the safety status index of the battery pack according to the balance weights and multiple characteristic values ​​corresponding to the battery pack under multiple characteristic items.

[0063] In this embodiment, a safety status index of the battery pack is determined.

[0064] Among them, a subjective weight variable is involved. The subjective weight variable is a linear coefficient corresponding to the subjective weight in the linear weight function, and is used to adjust the relative size of the subjective weight.

[0065] Among them, an objective weight variable is involved. The objective weight variable is a linear coefficient corresponding to the objective weight in the linear weight function, and is used to adjust the relative size of the objective weight.

[0066] Among them, a linear weight function is involved, which is a mathematical function that combines subjective weight and objective weight in a linear combination to reflect the comprehensive performance of subjective weight and objective weight. By constructing a linear weight function, the combination of subjective weight and objective weight is realized, and a more comprehensive and accurate evaluation result can be obtained.

[0067] Among them, a balance weight is involved, which is obtained by combining the subjective weight and the objective weight in a linear combination manner, and is used to reflect the comprehensive weight of the subjective weight and the objective weight.

[0068] In the steps involved in this embodiment, considering that relying solely on subjective weights or objective weights cannot accurately reflect the safety status of the battery pack, the relationship between subjective weights and objective weights is established by determining subjective weight variables, objective weight variables, and constructing a linear weight function, thereby achieving an effective combination of subjective weights and objective weights, and solving the problem of how to combine the two weights to achieve accurate safety status assessment. Through the linear weight function, a balance weight is determined, which eliminates the bias that may be caused by a single weight (for example, assessing the safety status of the battery pack based solely on subjective weights, or solely on objective weights), thereby ensuring the accuracy and comprehensiveness of the safety status index of the battery pack subsequently obtained based on the balance weight and the corresponding characteristic value, thereby achieving the purpose of accurately detecting the safety status of the battery pack and responding in a timely manner.

[0069] As an optional embodiment, based on the subjective weight variable and the objective weight variable, the subjective weights and objective weights corresponding to the battery pack under multiple feature items are linearly combined to obtain a linear weight function, including: determining the product of the subjective weight variable and the first transposed vector to obtain a first sub-function, wherein the first transposed vector is a vector obtained by transposing the vectors corresponding to the subjective weights corresponding to the battery pack under multiple feature items; determining the product of the objective weight variable and the second transposed vector to obtain a second sub-function, wherein the second transposed vector is a vector obtained by transposing the vectors corresponding to the objective weights corresponding to the battery pack under multiple feature items; determining a target vector, wherein the target vector includes one of the following: a vector corresponding to the subjective weights corresponding to the battery pack under multiple feature items, and a vector corresponding to the objective weights corresponding to the battery pack under multiple feature items; obtaining a linear weight function based on the first sub-function, the second sub-function and the target vector.

[0070] In this embodiment, a linear weight function is determined.

[0071] Among them, a first transposed vector is involved, which is a vector corresponding to multiple characteristic items of the battery pack obtained by transposing the vector corresponding to the subjective weight.

[0072] Among them, a first sub-function is involved, which is a function obtained according to the product of the subjective weight variable and the first transposed vector, and reflects the importance of the subjective weights corresponding to multiple feature items.

[0073] Among them, a second transposed vector is involved, which is a vector corresponding to multiple characteristic items of the battery pack obtained by transposing the vector corresponding to the objective weight.

[0074] Among them, a second sub-function is involved, which is a function obtained according to the product of the objective weight variable and the second transposed vector, and reflects the importance of the objective weights corresponding to multiple feature items.

[0075] Among them, a target vector is involved, which is a vector corresponding to the battery pack under multiple feature items. It can be a vector corresponding to the subjective weights of the battery pack under multiple feature items, or it can be a vector corresponding to the objective weights of the battery pack under multiple feature items.

[0076] In the steps involved in this embodiment, when determining the safety status of the battery pack, the first sub-function is obtained by combining the subjective weight variable and the product of the first transposed vector, which can reflect the importance of the subjective level of the battery pack under multiple feature items. At the same time, the second sub-function is obtained by combining the objective weight variable and the product of the second transposed vector, which can reflect the importance of the objective level of the battery pack under multiple feature items. The vector corresponding to the subjective or objective weight is selected as the target vector, and finally a comprehensive linear weight function is obtained by linearly combining the first sub-function, the second sub-function and the target vector, which realizes the effective combination of subjective weights and objective weights, eliminates the bias that may be caused by a single weight, and ensures the accuracy and comprehensiveness of the safety status index of the battery pack obtained based on the balance weight and the corresponding eigenvalue, so as to achieve the purpose of accurately detecting the safety status of the battery pack and responding in time.

[0077] As an optional embodiment, based on multiple characteristic values ​​corresponding to multiple target batteries under multiple characteristic items, information utility values ​​corresponding to the battery pack under multiple characteristic items are determined, including: based on multiple characteristic values ​​corresponding to multiple target batteries under multiple characteristic items, multiple trend indicators corresponding to the multiple target batteries under multiple characteristic items are determined, wherein the trend indicators are determined based on current indicator values ​​of the corresponding target batteries under the corresponding characteristic items, and maximum indicator values ​​and minimum indicator values ​​of the multiple target batteries under the corresponding characteristic items; based on multiple trend indicators corresponding to multiple target batteries under multiple characteristic items, information utility values ​​corresponding to the battery pack under multiple characteristic items are determined.

[0078] In this embodiment, the information utility values ​​corresponding to the battery pack under multiple feature items are determined.

[0079] Among them, a trend indicator is involved, which is determined by the current indicator value of the target battery under the corresponding feature item, and the maximum indicator value and the minimum indicator value of multiple target batteries under the corresponding feature item. It is an indicator used to eliminate the differences between the characteristic values ​​corresponding to multiple feature items, and their respective impact on the battery safety status.

[0080] Among them, the current indicator value is involved, and the current indicator value is the specific value of a target battery under the corresponding feature item when evaluating the safety status of the battery pack.

[0081] Among them, the maximum indicator value is involved, and the maximum indicator value is used to represent the maximum current indicator value among the current indicator values ​​corresponding to a certain characteristic item of multiple target batteries when evaluating the safety status of the battery pack.

[0082] Among them, the minimum indicator value is involved, which is used to represent the smallest current indicator value among the current indicator values ​​corresponding to a certain characteristic item of multiple target batteries when evaluating the safety status of the battery pack.

[0083] In the steps involved in this embodiment, the trend indicator is determined based on the current indicator value of the corresponding target battery under the corresponding feature item, and the maximum indicator value and the minimum indicator value of multiple target batteries under the corresponding feature item, and the information utility value of the battery pack under each feature item is determined according to the multiple trend indicators corresponding to the multiple target batteries under the multiple feature items, thereby eliminating the influence of the differences between the characteristic values ​​corresponding to the multiple feature items of the target battery on the battery safety status, effectively solving the evaluation difficulties caused by data heterogeneity, and ensuring the objectivity and accuracy of subsequent evaluations.

[0084] As an optional embodiment, based on multiple trend indicators corresponding to multiple target batteries under multiple feature items, information utility values ​​corresponding to the battery pack under multiple feature items are determined, including: based on multiple trend indicators corresponding to multiple target batteries under multiple feature items, information entropy values ​​corresponding to the battery pack under multiple feature items are determined, wherein the information entropy value is used to represent the degree of discreteness of the feature value under the corresponding feature item; based on the information entropy values ​​corresponding to the battery pack under multiple feature items, information utility values ​​corresponding to the battery pack under multiple feature items are determined.

[0085] In this embodiment, specific steps are described for determining information utility values ​​corresponding to a battery pack under multiple feature items based on multiple trend indicators corresponding to multiple target batteries under multiple feature items.

[0086] Among them, the information entropy value is involved. The information entropy value is used to indicate the discreteness of the eigenvalue under the corresponding feature item. The lower the information entropy value, the more concentrated the eigenvalue distribution is and the smaller the uncertainty is. On the contrary, the higher the information entropy value, the more dispersed the eigenvalue distribution is and the greater the uncertainty or amount of information.

[0087] In the steps involved in this embodiment, by determining the information entropy values ​​corresponding to the multiple characteristic items of the battery pack according to the multiple trend indicators corresponding to the multiple target batteries under the multiple characteristic items, the uniformity of the characteristic value distribution of the multiple target batteries under a certain characteristic item can be reflected. Furthermore, by determining the information utility values ​​corresponding to the multiple characteristic items of the battery pack according to the information entropy values ​​corresponding to the multiple characteristic items of the battery pack, the importance of the multiple characteristic items to the safety status of the battery pack is quantified, so that the influence of the characteristic items on the safety status of the battery pack can be objectively and accurately reflected, which is helpful for the subsequent determination of the accuracy of the safety status index of the battery pack, so as to achieve the purpose of accurately detecting the safety status of the battery pack and responding in time.

[0088] As an optional embodiment, the subjective weights corresponding to the battery pack under multiple feature items are determined based on the feature sequence, including: determining the importance ratio between two adjacent feature items in the feature sequence; determining the subjective weights corresponding to the battery pack under multiple feature items based on the importance ratio between two adjacent feature items in the feature sequence.

[0089] In this embodiment, the subjective weights corresponding to the battery pack under multiple feature items are determined.

[0090] Among them, the importance ratio is involved. The importance ratio is the ratio between two adjacent feature items, which is used to reflect the relative importance of the two feature items in affecting the safety status of the battery pack. The value of the importance ratio reflects the relative weight of the two adjacent feature items in evaluating the safety status of the battery pack. For example, if the two adjacent feature items are F and E, the importance ratio is F / E. If the result of F / E is equal to 1, it can be considered that F and E have the same importance in affecting the safety status of the battery pack.

[0091] In the steps involved in this embodiment, by determining the importance ratio between two adjacent feature items in the feature sequence, the relative weight of the two adjacent feature items in the evaluation of the safety status of the battery pack is quantified. And through the corresponding importance ratio, the subjective weights corresponding to the battery pack under multiple feature items are determined. The determination of the subjective weight takes into account the importance ranking of the feature items and the proportional relationship between them, effectively avoiding the arbitrariness and imbalance of the subjective weight allocation, so that the subsequent evaluation can accurately reflect the actual impact of different feature items on the battery safety status, which is helpful for the subsequent determination of the accuracy of the safety status index of the battery pack and realizes the accurate evaluation of the safety status of the battery pack.

[0092] As an optional embodiment, after determining the safety status index of the battery pack according to the subjective weights, objective weights and multiple characteristic values ​​corresponding to the battery pack under multiple characteristic items, it also includes: when the safety status index is lower than a predetermined threshold, determining an alarm indicator item from the multiple characteristic items; sending an alarm message to a predetermined terminal, wherein the alarm message includes the safety status index, the alarm indicator item, and the indicator value corresponding to the alarm indicator item.

[0093] In this embodiment, specific steps after determining the safety status index of the battery pack are described.

[0094] Among them, a predetermined threshold is involved, which is a predetermined critical value used to reflect the safety status of the battery pack. The predetermined threshold can be determined based on the corresponding working characteristics, safety standards or historical data of the battery pack.

[0095] Among them, the alarm indicator item is involved. When the safety status index of the battery pack is lower than the predetermined threshold, the corresponding characteristic value in the multiple characteristic items of the battery pack is abnormal or changes, which causes the battery pack safety status index to decrease. Determining the alarm indicator item helps to quickly locate and diagnose the safety problem of the battery pack.

[0096] Among them, the alarm information is involved. When the safety status index of the battery pack is lower than the predetermined threshold, the alarm information is used to warn the current battery pack of the safety status problem and is sent to the predetermined terminal. The alarm information may include key information such as the specific value of the safety status index, the alarm index items that cause the safety status index to drop, and the index values ​​corresponding to these alarm index items.

[0097] Among them, a predetermined terminal is involved, which is a predetermined terminal for receiving alarm information. The predetermined terminal can be a mobile device, a computer in a monitoring center, or a control unit of a battery management system. After receiving the alarm information, the predetermined terminal can display it to relevant personnel for viewing, or automatically trigger further safety operations, such as stopping charging, starting the cooling system, etc.

[0098] In the steps involved in this embodiment, when the safety status index is lower than a predetermined threshold, determining the alarm indicator item helps to quickly locate and diagnose the safety problem of the battery pack, effectively reducing the blindness of the battery pack safety status detection and improving the efficiency of fault diagnosis and processing. By sending an alarm message to a predetermined terminal, wherein the alarm message includes the safety status index, the alarm indicator item, and the indicator value corresponding to the alarm indicator item, the current safety status of the battery pack and possible problems can be notified, ensuring the timely communication and clarity of the battery pack safety status, improving the response speed of the battery pack safety status detection, significantly shortening the time from problem discovery to action, thereby achieving accuracy and timeliness of battery pack safety detection and avoiding unnecessary losses.

[0099] Based on the above embodiments and optional embodiments, an optional implementation is provided, which is described in detail below.

[0100] In related technologies, with the widespread application of energy storage batteries and power batteries in the field of new energy, battery safety issues have received increasing attention. Battery packs generate a lot of heat during operation. If the temperature inside the battery pack is too high or the heat dissipation is poor, thermal runaway may occur, leading to battery pack failure or even explosion. How to accurately detect the safety status of the battery pack has become a challenge. Although traditional methods can monitor basic operating parameters, there is a technical problem that the safety status of the battery pack cannot be accurately detected during the safety status detection of the battery pack.

[0101] To address the above-mentioned problems, no effective solution has been proposed yet.

[0102] In view of this, a method for determining a safety status index of a battery pack is provided in an optional embodiment of the present invention, which can also be called a battery safety status assessment method based on temperature and heat, which can effectively solve the technical problem in related technologies that the safety status of the battery pack cannot be accurately detected during the safety status detection.

[0103] Figure 2 is an overall flow chart of a battery safety status assessment system in an optional embodiment of the present invention, Figure 3 is a structural diagram of a battery safety status evaluation indicator set in an optional implementation manner of the present invention, such as Figure 2 as well as Figure 3 As shown, the optional implementation methods of the present application are described in detail below.

[0104] S1. Acquire battery data of a battery pack, wherein the battery data includes environmental parameters, and the battery pack includes a plurality of target batteries;

[0105] S2. determining a plurality of characteristic items for evaluating the safety status of the battery under environmental parameters;

[0106] For example, according to the influence of different factors on the battery safety status under the thermal physical field, eight safety characteristic quantities (same as the above multiple characteristic items) are selected, including battery internal temperature, ambient temperature, battery surface temperature, battery module temperature non-uniformity, battery heat generation, heat generation rate, heat dissipation, and temperature change rate. Based on multiple safety characteristic quantities under the thermal physical field, a battery safety status assessment system is established.

[0107] S3. Determine a feature sequence according to the subjective evaluation data corresponding to the battery pack under multiple feature items, wherein the feature sequence includes multiple feature items sorted by importance index;

[0108] S4, determining information utility values ​​corresponding to the battery pack under the multiple feature items according to the multiple feature values ​​corresponding to the multiple target batteries under the multiple feature items, wherein the information utility value is used to indicate the importance of the feature item, wherein the multiple feature values ​​correspond to the multiple feature items one by one;

[0109] Specifically, S4 also includes:

[0110] S41, determining multiple trend indicators corresponding to the multiple target batteries under the multiple feature items according to the multiple feature values ​​corresponding to the multiple target batteries under the multiple feature items, wherein the trend indicators are determined according to the current indicator values ​​of the corresponding batteries under the corresponding feature items, and the maximum indicator values ​​and the minimum indicator values ​​of the multiple batteries under the corresponding feature items;

[0111] S42. Determine the information utility values ​​corresponding to the battery pack under the multiple feature items according to the multiple trend indicators corresponding to the multiple target batteries under the multiple feature items.

[0112] Specifically, S42 also includes:

[0113] S421, determining information entropy values ​​corresponding to the battery pack under the multiple feature items according to the multiple trend indicators corresponding to the multiple target batteries under the multiple feature items, wherein the information entropy value is used to represent the discrete degree of the feature value under the corresponding feature item;

[0114] S422. Determine the information utility values ​​corresponding to the battery pack under the multiple feature items according to the information entropy values ​​corresponding to the battery pack under the multiple feature items.

[0115] S5. Determine the subjective weights corresponding to the battery pack under multiple feature items according to the feature sequence, and determine the objective weights corresponding to the battery pack under multiple feature items according to the adjustment coefficient item and the information utility values ​​corresponding to the battery pack under multiple feature items;

[0116] Specifically, S5 also includes:

[0117] S51, determining the importance ratio between two adjacent feature items in the feature sequence;

[0118] S52. Determine the subjective weights corresponding to the battery pack under multiple feature items according to the importance ratio between two adjacent feature items in the feature sequence.

[0119] For example, the subjective weight X (same as the subjective weight) of each indicator (same as the above-mentioned multiple feature items) is determined according to the order relationship analysis method (G1 method), X = [X1, X2, X3...X8]. The G1 method is a method improved from the hierarchical analysis method. Compared with the hierarchical analysis method, the amount of calculation is reduced and no consistency test is required. The G1 analysis method is mainly divided into three stages: determining the order of indicators, ranking according to the importance of indicators, and calculating weights.

[0120] According to the entropy method, the objective weight Y of each indicator is obtained (same as the above objective weight), Y = [Y1, Y2, Y3...Y8]. The entropy method assigns weights according to the differences in the degree of order of the indicator data. The more discrete the data, the greater its weight. The improved entropy method mainly includes five steps: data standardization, calculation of indicator weights, determination of indicator information entropy, calculation of indicator information utility value, and calculation of evaluation indicator weights. The improved entropy method can solve the problem that when the credit entropy value gradually approaches 1 in the traditional entropy method, a small change in the credit entropy value will lead to a change in its multiple. Adding the adjustment term ε on the basis of the entropy method can solve this drawback. The improved indicator objective weight value is expressed as:

[0121]

[0122] Among them, Y j represents the objective weight value of the jth indicator, e j is the credit entropy value (same as the information entropy value mentioned above), n=8.

[0123] The subjective weight of the indicator is determined according to the ordinal relationship analysis method. The main steps of the ordinal relationship analysis method can be divided into three stages.

[0124] (1) Determine the order of indicators. Suppose the object to be evaluated is A, and the corresponding evaluation indicators are: x1, x2, ..., x m , if the evaluation index x1 is more important than x2 under a certain evaluation criterion or evaluation object, then it is recorded as: x1>x2. Therefore, if it is extended to m indicators and the importance ranking between indicators is determined, we can get: x * 1>x * 2>x * 3>...>x * m-1 >x * m .

[0125] (2) According to the order of importance of the indicators judged above, the importance is further quantified below. Suppose the decision maker judges x * k-1 / x * k The importance ratio is X k-1 / X k (Weight ratio). According to the decision maker’s judgment, the ratio between the two is: X k-1 / X k =r k (k=m,m-1,m-2...m) Where r k It is called the tone operator. At present, there are 9 levels of operator methods commonly used in China. Table 1 is a description table of the 9 levels of operator methods commonly used in China.

[0126] Table 1

[0127]

[0128] Calculate the weight X of each indicator m The formula is shown below.

[0129]

[0130] Then we can get X m-1 The weight is: X m-1 =r k * X m , and the weights of all indicators can be obtained in sequence.

[0131] The objective weight of the indicator is determined according to the improved entropy method. The main steps of the entropy method are as follows:

[0132] (1) Data standardization. In order to eliminate the impact of data differences on the battery safety status, the original data needs to be standardized. Different standardization processes are performed according to the different positive and negative indicators of the safety characteristic value (the same as the above trend indicators). The following is the formula for standardization:

[0133] Positive indicators:

[0134] Negative indicators:

[0135] Among them, x ij is the positive or negative indicator of the j-th safety characteristic value corresponding to the i-th target battery, x j is the jth security characteristic value, x min is the minimum value of the j-th security characteristic value, x max is the maximum value of the jth security characteristic value. At the same time, in order to ensure the integrity of the data and the scientific nature of the evaluation, the values ​​equal to 0 after standardization are reassigned, and 0.001 is selected as the translation amount and included in the calculation.

[0136] (2) Calculate the weight of the safety characteristic value of target battery i under the j-th safety characteristic value. The calculation formula is as follows.

[0137]

[0138] Determine the information entropy value e of the jth indicator j :

[0139]

[0140] (3) Calculate the information utility value d of the jth indicator j (Same as the above information utility value). The value of d is equal to 1 and the information entropy value of the indicator is e j The larger the d value, the more important it is to the evaluation object. The calculation formula is:

[0141] d j =1-e j

[0142] (4) Calculate the weight of the evaluation index. Use the value coefficient of information entropy to determine the index weight. The higher the value coefficient, the greater the index weight. Finally, the weight of the j-item index c is obtained. j The calculation formula is:

[0143]

[0144] (5) However, the traditional entropy method has certain drawbacks. jWhen it gradually approaches 1, a small change in the entropy value of the indicator will lead to a change in its multiple. Therefore, the traditional entropy method can be adjusted. Adding the adjustment term ε on the basis of the entropy method can solve this problem. The improved formula for calculating the objective weight value of the indicator is:

[0145]

[0146] S6. Determine the safety status index of the battery pack according to the subjective weights, objective weights and multiple characteristic values ​​corresponding to the battery pack under multiple characteristic items.

[0147] Specifically, S6 also includes:

[0148] S61. Determine a subjective weight variable and an objective weight variable;

[0149] S62, based on the subjective weight variable and the objective weight variable, linearly combine the subjective weights and the objective weights corresponding to the battery pack under multiple feature items to obtain a linear weight function;

[0150] Specifically, S62 also includes:

[0151] S621, determining the product of the subjective weight variable and the first transposed vector to obtain a first sub-function, wherein the first transposed vector is a vector obtained by transposing vectors corresponding to the subjective weights corresponding to the battery pack under multiple feature items;

[0152] S622, determining the product of the objective weight variable and the second transposed vector to obtain a second sub-function, wherein the second transposed vector is a vector obtained by transposing vectors corresponding to the objective weights corresponding to the battery pack under multiple feature items;

[0153] S623, determining a target vector, wherein the target vector includes one of the following: vectors corresponding to subjective weights corresponding to the battery pack under multiple feature items, and vectors corresponding to objective weights corresponding to the battery pack under multiple feature items;

[0154] S624. Obtain a linear weight function according to the first sub-function, the second sub-function and the target vector.

[0155] S63, determining the corresponding balancing weights of the battery pack under multiple feature items according to the linear weight function;

[0156] S64. Determine a safety status index of the battery pack according to the balance weights and multiple characteristic values ​​corresponding to the battery pack under multiple characteristic items.

[0157] For example, a safety score is obtained based on subjective and objective weights and safety feature parameters. Specifically, the ordinal relationship analysis method is a subjective weighting method, which can set weights according to the subjective wishes of decision makers, but at the same time ignores the connection between objective data itself and lacks objectivity. The improved entropy method is an objective weighting method. Although it can dig deep into the data and find the variation of each indicator data, it is less consistent with the actual situation and lacks accuracy. Therefore, it is necessary to use game theory to combine weights to determine the weights and find the Nash equilibrium point of the subjective and objective weighting methods, so as to make the evaluation indicators more scientific and effective. According to the subjective weight X and the objective weight Y, the subjective and objective weight Z is obtained, Z = [Z1, Z2, Z3...Z8]. The specific steps are as follows:

[0158] (1) A new weight vector Z is constructed by linearly combining the weight X obtained by the order relationship analysis method and the weight Y obtained by the improved entropy method. The relationship (same as the above linear weight function) is as follows:

[0159] Z=β1X T +β2Y T

[0160] Among them, β1 and β2 are the linear coefficients of subjective and objective weights respectively (same as the subjective weight variable and objective weight variable mentioned above).

[0161] (2) According to the idea of ​​game theory, find the Nash equilibrium point of weights that minimizes the deviation between subjective and objective weights and combined weights. The formula is as follows:

[0162] min||β1X T +β2Y T -P T ||2, P = X, Y

[0163] Among them, X T is the first transposed vector, Y T is the second transposed vector, P is the target vector, P T is the transposed vector of P, β1X T is the first subfunction, β2Y T is the second sub-function.

[0164] (3) Derivative the formula in step (2). The optimal solution obtained by derivation is the subjective and objective optimal weight combination obtained under game theory. The first-order derivative of the optimal solution should meet the following conditions:

[0165] β1PX T +β2PY T =PP T

[0166] (4) Normalize the weight coefficients β1 and β2 obtained by the formula in step (3):

[0167]

[0168] in, is the normalized weight coefficient, a=1,2.

[0169] (5) Obtain the final combination weight Z (same as the above balance weight), the formula is as follows:

[0170]

[0171] Finally, the battery safety status score S (same as the above safety status index) is obtained by combining the weight Z, and the formula is as follows:

[0172]

[0173] Specifically, after S6, it also includes:

[0174] S7. When the security status index is lower than a predetermined threshold, determining an alarm indicator item from a plurality of characteristic items;

[0175] S8. Sending alarm information to a predetermined terminal, wherein the alarm information includes a security status index, alarm indicator items, and indicator values ​​corresponding to the alarm indicator items.

[0176] Through the above optional implementation, at least the following beneficial effects can be achieved:

[0177] (1) Compared with the prior art, the present invention determines multiple feature items for evaluating the safety status of the battery under environmental parameters based on the battery data of the battery pack, including environmental parameters. The impact of environmental factors on battery performance and safety assessment is resolved, ensuring the accuracy of battery assessment under different environmental conditions. Based on the multiple feature items of the battery pack, the corresponding subjective weights, objective weights and multiple feature values ​​are determined, and the relationship between the subjective level and the objective level is established to ensure the accuracy and comprehensiveness of the evaluation, thereby solving the technical problem in the related art that the safety status of the battery pack cannot be accurately detected during the safety status detection of the battery pack.

[0178] (2) Compared with the prior art, the present invention can reflect the subjective preferences of multiple feature items for the importance of the battery pack safety status by determining subjective weights when evaluating the battery pack safety status, ensuring that the subjective expectations and concerns when detecting the battery pack safety status can be taken into account when evaluating the battery pack safety status. By determining objective weights, the actual impact of each feature item on the battery pack safety status can be objectively and accurately reflected. And by introducing an adjustment coefficient, the deviation in determining the objective weight based on the information utility value is corrected, making the evaluation result more accurate and reliable. The determination of subjective weights and objective weights together constitute a complete system for battery pack safety status evaluation, which not only ensures that the evaluation results can meet the expectations and concerns at the subjective level, but also ensures the accuracy and reliability of the evaluation results, improves the accuracy and reliability of the subsequent determination of the battery pack safety status index, and thus helps to accurately detect the battery safety status.

[0179] (3) Compared with the prior art, the present invention takes into account that relying solely on subjective weights or objective weights cannot accurately reflect the safety status of the battery pack. Therefore, by determining the subjective weight variables, objective weight variables, and constructing a linear weight function, the relationship between the subjective weights and the objective weights is established, and an effective combination of the subjective weights and the objective weights is achieved, solving the problem of how to combine the two weights to achieve accurate safety status assessment. Through the linear weight function, the balance weight is determined, which eliminates the bias that may be caused by a single weight, thereby ensuring the accuracy and comprehensiveness of the safety status index of the battery pack obtained subsequently based on the balance weight and the corresponding characteristic value, thereby achieving the purpose of accurately detecting the safety status of the battery pack and responding in a timely manner.

[0180] (4) Compared with the prior art, when determining the performance of the battery pack, the present invention combines the subjective weight variable and the product of the first transposed vector to obtain a first sub-function, which can reflect the importance of the battery pack under multiple feature items at the subjective level. At the same time, the objective weight variable and the product of the second transposed vector are combined to obtain a second sub-function, which can reflect the importance of the battery pack under multiple feature items at the objective level. The vector corresponding to the subjective or objective weight is selected as the target vector, and finally a comprehensive linear weight function is obtained by linearly combining the first sub-function, the second sub-function and the target vector, thereby achieving an effective combination of subjective weights and objective weights, eliminating the bias that may be caused by a single weight, and ensuring the accuracy and comprehensiveness of the safety status index of the battery pack obtained subsequently based on the balance weight and the corresponding eigenvalue, thereby achieving the purpose of accurately detecting the safety status of the battery pack and responding in a timely manner.

[0181] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should know that the present invention is not limited by the described action sequence, because according to the present invention, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

[0182] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods of various embodiments of the present invention.

[0183] Example 2

[0184] According to an embodiment of the present invention, a device for implementing the above-mentioned method for determining the safety status index of a battery pack is also provided. Figure 4 is a structural block diagram of a device for determining a safety status index of a battery pack according to an embodiment of the present invention. Figure 4 As shown, the device includes: an acquisition module 402, a first determination module 404, a second determination module 406, a third determination module 408, a fourth determination module 410 and a fifth determination module 412. The device is described in detail below.

[0185] The acquisition module 402 is used to acquire battery data of the battery pack, wherein the battery data includes environmental parameters, and the battery pack includes multiple target batteries; the first determination module 404 is connected to the acquisition module 402, and is used to determine multiple feature items for evaluating the safety status of the battery under the environmental parameters; the second determination module 406 is connected to the first determination module 404, and is used to determine a feature sequence according to the subjective evaluation data corresponding to the multiple feature items of the battery pack, wherein the feature sequence includes multiple feature items sorted by importance index; the third determination module 408 is connected to the second determination module 406, and is used to determine the battery pack under multiple feature items according to the multiple feature values ​​corresponding to the multiple target batteries under the multiple feature items. The information utility values ​​corresponding to the feature items are respectively used, wherein the information utility values ​​are used to indicate the importance of the feature items, wherein multiple feature values ​​correspond one-to-one to multiple feature items; a fourth determination module 410, connected to the third determination module 408, is used to determine the subjective weights corresponding to the battery pack under the multiple feature items according to the feature sequence, and to determine the objective weights corresponding to the battery pack under the multiple feature items according to the adjustment coefficient items and the information utility values ​​corresponding to the battery pack under the multiple feature items; a fifth determination module 412, connected to the fourth determination module 410, is used to determine the safety status index of the battery pack according to the subjective weights, objective weights and multiple feature values ​​corresponding to the battery pack under the multiple feature items.

[0186] It should be noted here that the above-mentioned acquisition module 402, first determination module 404, second determination module 406, third determination module 408, fourth determination module 410 and fifth determination module 412 correspond to steps S102 to S112 in the method for determining the safety status index of the battery pack, and the instances and application scenarios implemented by the multiple modules are the same as the corresponding steps, but are not limited to the contents disclosed in the above-mentioned embodiment 1.

[0187] Example 3

[0188] According to another aspect of an embodiment of the present invention, there is also provided an electronic device, comprising: a processor; and a memory for storing instructions executable by the processor, wherein the processor is configured to execute instructions to implement any of the above methods for determining a safety status index of a battery pack.

[0189] Example 4

[0190] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is also provided. When the instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device can execute any of the above-mentioned methods for determining the safety status index of a battery pack.

[0191] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0192] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0193] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0194] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0195] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0196] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present 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, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0197] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for determining a safety status index of a battery pack, characterized in that: include: Acquire battery data of a battery pack, wherein the battery data includes environmental parameters, and the battery pack includes a plurality of target batteries; Determining a plurality of characteristic items for evaluating a battery safety state under the environmental parameters; Determine a feature sequence according to the subjective evaluation data corresponding to the battery pack under the multiple feature items, wherein the feature sequence includes the multiple feature items sorted by importance index; Determine, according to the plurality of characteristic values ​​respectively corresponding to the plurality of target batteries under the plurality of characteristic items, the information utility values ​​respectively corresponding to the plurality of characteristic items of the battery pack under the plurality of characteristic items, wherein the information utility values ​​are used to indicate the importance of the characteristic items, wherein the plurality of characteristic values ​​correspond one-to-one to the plurality of characteristic items; Determine, according to the feature sequence, the subjective weights of the battery pack corresponding to the multiple feature items, respectively, and determine, according to the adjustment coefficient item and the information utility values ​​of the battery pack corresponding to the multiple feature items, respectively, the objective weights of the battery pack corresponding to the multiple feature items, respectively; The safety status index of the battery pack is determined according to the subjective weights, objective weights and multiple characteristic values ​​corresponding to the multiple characteristic items of the battery pack.

2. The method according to claim 1, characterized in that Determining the safety status index of the battery pack according to the subjective weights, objective weights and multiple characteristic values ​​corresponding to the battery pack under the multiple characteristic items, including: Determine subjective weight variables and objective weight variables; According to the subjective weight variable and the objective weight variable, a linear combination of the subjective weights and the objective weights corresponding to the battery pack under the plurality of feature items is performed to obtain a linear weight function; Determining, according to the linear weight function, the corresponding balancing weights of the battery pack under the plurality of characteristic items; The safety status index of the battery pack is determined according to the balance weights and multiple characteristic values ​​corresponding to the battery pack under the multiple characteristic items.

3. The method according to claim 2, characterized in that According to the subjective weight variable and the objective weight variable, the subjective weight and the objective weight corresponding to the battery pack under the multiple feature items are linearly combined to obtain a linear weight function, including: Determine the product of the subjective weight variable and a first transposed vector to obtain a first sub-function, wherein the first transposed vector is a vector obtained by transposing vectors corresponding to the subjective weights of the battery pack under the multiple feature items respectively; Determine the product of the objective weight variable and a second transposed vector to obtain a second sub-function, wherein the second transposed vector is a vector obtained by transposing vectors corresponding to the objective weights corresponding to the battery pack under the plurality of feature items; Determine a target vector, wherein the target vector includes one of the following: vectors corresponding to the subjective weights of the battery pack under the multiple feature items, and vectors corresponding to the objective weights of the battery pack under the multiple feature items; The linear weight function is obtained according to the first sub-function, the second sub-function and the target vector.

4. The method according to claim 1, characterized in that: Determining the information utility values ​​corresponding to the plurality of characteristic items of the battery pack according to the plurality of characteristic values ​​corresponding to the plurality of target batteries under the plurality of characteristic items, including: Determine, according to the plurality of characteristic values ​​respectively corresponding to the plurality of target batteries under the plurality of characteristic items, a plurality of trend indicators respectively corresponding to the plurality of target batteries under the plurality of characteristic items, wherein the trend indicator is determined according to the current indicator value of the corresponding target battery under the corresponding characteristic item, and the maximum indicator value and the minimum indicator value of the plurality of target batteries under the corresponding characteristic item; According to the plurality of trend indicators respectively corresponding to the plurality of target batteries under the plurality of characteristic items, the information utility values ​​respectively corresponding to the plurality of characteristic items of the battery pack are determined.

5. The method according to claim 4, characterized in that Determining the information utility values ​​corresponding to the plurality of characteristic items of the battery pack according to the plurality of trend indicators corresponding to the plurality of target batteries under the plurality of characteristic items, including: Determine, according to the plurality of trend indicators respectively corresponding to the plurality of target batteries under the plurality of feature items, information entropy values ​​respectively corresponding to the plurality of feature items of the battery pack under the plurality of feature items, wherein the information entropy values ​​are used to indicate the degree of discreteness of the feature values ​​under the corresponding feature items; According to the information entropy values ​​corresponding to the battery pack under the multiple feature items, the information utility values ​​corresponding to the battery pack under the multiple feature items are determined.

6. The method according to claim 1, characterized in that Determining, according to the feature sequence, the subjective weights corresponding to the battery pack under the multiple feature items, respectively, including: Determining the importance ratio between two adjacent feature items in the feature sequence; According to the importance ratio between two adjacent feature items in the feature sequence, the subjective weights corresponding to the battery pack under the multiple feature items are determined.

7. The method according to any one of claims 1 to 6, characterized in that After determining the safety status index of the battery pack according to the subjective weights, objective weights and multiple characteristic values ​​corresponding to the multiple characteristic items of the battery pack, the method further includes: When the safety status index is lower than a predetermined threshold, determining an alarm indicator item from the multiple feature items; Sending alarm information to a predetermined terminal, wherein the alarm information includes the security status index, the alarm indicator item, and the indicator value corresponding to the alarm indicator item.

8. A device for determining a safety status index of a battery pack, characterized in that: include: An acquisition module, used for acquiring battery data of a battery pack, wherein the battery data includes environmental parameters, and the battery pack includes a plurality of target batteries; A first determination module, used to determine a plurality of characteristic items for evaluating a battery safety state under the environmental parameters; A second determination module is used to determine a feature sequence according to the subjective evaluation data corresponding to the battery pack under the multiple feature items, wherein the feature sequence includes the multiple feature items sorted by importance index; A third determination module, configured to determine information utility values ​​corresponding to the battery pack under the multiple feature items according to the multiple feature values ​​corresponding to the multiple target batteries under the multiple feature items, wherein the information utility value is used to indicate the importance of the feature item, wherein the multiple feature values ​​correspond to the multiple feature items one-to-one; a fourth determination module, configured to determine, according to the feature sequence, the subjective weights corresponding to the battery pack under the plurality of feature items, respectively, and to determine, according to the adjustment coefficient item and the information utility values ​​corresponding to the battery pack under the plurality of feature items, respectively, the objective weights corresponding to the battery pack under the plurality of feature items, respectively; The fifth determination module is used to determine the safety status index of the battery pack according to the subjective weights, objective weights and multiple characteristic values ​​corresponding to the battery pack under the multiple characteristic items.

9. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the method for determining the safety status index of the battery pack according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: When the instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the method for determining a safety status index of a battery pack as described in any one of claims 1 to 7.

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