Method and device for evaluating safety entropy of lithium-ion battery system considering concurrent faults

Abstract

The present application discloses a method and device for evaluating the safety entropy of a lithium-ion battery system considering concurrent failures, belonging to the technical field of lithium battery management. The method includes: determining the accessory failure probability and concurrent failure probability of the lithium-ion battery system according to historical failure information through the accessory failure probability model and concurrent failure probability model of the lithium-ion battery system; determining the sporadic failure probability of the lithium-ion battery system according to battery parameters based on the sporadic failure probability model of the lithium-ion battery system; calculating the comprehensive failure probability and non-failure probability of the lithium-ion battery system according to the accessory failure probability, concurrent failure probability and sporadic failure probability; calculating the comprehensive safety entropy of the lithium-ion battery system according to the comprehensive failure probability and non-failure probability. This method combines the concurrent failures of system components and the sporadic failures of the lithium battery body, and can comprehensively and quantitatively analyze concurrent failures and sporadic failures, improving the accuracy of failure analysis.

Description

Technical Field

[0001] This application belongs to the technical field of lithium battery management, and particularly relates to a method and device for evaluating the safety entropy of a lithium-ion battery system considering concurrent failures. Background Art

[0002] Due to its high energy density, long cycle life, fast charging and other characteristics, lithium batteries have been widely used in fields such as automobiles, mobile phones, and computers. However, lithium-ion battery safety accidents occur continuously, causing serious losses of life and property. Therefore, there is a huge demand for research on the safety of lithium-ion batteries.

[0003] In the qualitative evaluation method, based on a decision tree, data of the battery management system (BMS) is read by a small mobile device, and the safety state of the battery is quickly evaluated based on a series of threshold judgments. Finally, three safety states of red, orange, and green are obtained, and the evaluation results are calculated and displayed on the application program.

[0004] However, the failure of the lithium-ion battery system caused by accessory failures is called concurrent failure. The above methods generally use methods such as fault trees and safety domain models based on petri nets to model the concurrent failures of lithium batteries. These methods can only achieve qualitative analysis of concurrent failures, and the accuracy of fault analysis is not high. Summary of the Invention

[0005] This application aims to solve at least one of the technical problems existing in the prior art. For this reason, this application proposes a method and device for evaluating the safety entropy of a lithium-ion battery system considering concurrent failures, which integrates the concurrent failures of system components and the accidental failures of the lithium battery body, and can comprehensively quantitatively analyze concurrent failures and accidental failures, improving the accuracy of fault analysis.

[0006] In a first aspect, this application provides a method for evaluating the safety entropy of a lithium-ion battery system considering concurrent failures. The lithium-ion battery system includes a battery body and system accessories. The method includes:

[0007] Obtain the historical fault information of the system accessories and the battery parameters of the battery body;

[0008] Determine the accessory failure probability and concurrent failure probability of the lithium-ion battery system according to the historical fault information through the accessory failure probability model and concurrent failure probability model of the lithium-ion battery system;

[0009] Determine the accidental failure probability of the lithium-ion battery system according to the battery parameters based on the accidental failure probability model of the lithium-ion battery system;

[0010] Calculate the comprehensive failure probability and the non-failure probability of the lithium-ion battery system according to the accessory failure probability, the concurrent failure probability, and the sporadic failure probability;

[0011] Calculate the comprehensive safety entropy of the lithium-ion battery system according to the comprehensive failure probability and the non-failure probability.

[0012] According to an embodiment of the present application, calculating the comprehensive failure probability and the non-failure probability of the lithium-ion battery system according to the concurrent failure probability and the sporadic failure probability includes:

[0013] Determine the different types of failure probabilities of the lithium-ion battery system based on the concurrent failure probability and the sporadic failure probability;

[0014] Determine the comprehensive failure probability and the non-failure probability according to the different types of failure probabilities.

[0015] According to an embodiment of the present application, the comprehensive failure probability is:

[0016]

[0017] Wherein, represents the comprehensive failure probability that the lithium-ion battery system fails at time, is the total number of accessories in the system accessories, , is the accessory failure probability that causes the lithium-ion battery system to fail due to the accessory at time t, is the concurrent failure probability, is the sporadic failure probability at time t, is the total number of failures, is is the non-failure probability of the lithium-ion battery system at time;

[0018] The non-failure probability of the lithium-ion battery system is:

[0019]

[0020] Wherein, is the non-failure probability of the lithium-ion battery system at time.

[0021] According to an embodiment of the present application, the comprehensive safety entropy of the lithium-ion battery system is:

[0022]

[0023] Wherein, is the comprehensive safety entropy of the lithium-ion battery system, is the total number of faults, is at moment, the faults that occur in the lithium-ion battery system of the comprehensive fault probability, .

[0024] According to an embodiment of the present application, the accidental fault probability model is constructed based on a BP neural network;

[0025] The battery parameters include the output current, voltage, surface temperature of the battery body, and the internal gas production pressure inside the battery pack;

[0026] The accidental fault probability includes the fault probability and the non-fault probability of accidental faults. The fault types of the accidental faults include at least one of internal short circuit faults, overcharge faults, over-discharge faults, thermal runaway faults, and gas leakage faults.

[0027] According to an embodiment of the present application, through the accessory fault probability model and the concurrent fault probability model of the lithium-ion battery system, the accessory fault probability and the concurrent fault probability of the lithium-ion battery system are determined according to the historical fault information, including:

[0028] Input the historical fault information into the accessory fault probability model to obtain the fault probability of each accessory in the accessory system output by the accessory fault probability model, so as to determine the accessory fault probability of each accessory causing the lithium-ion battery system to fail. The accessory fault probability model is constructed based on a long short-term memory network;

[0029] Based on the probability of each accessory causing the lithium-ion battery system to fail and the concurrent fault probability model, determine the concurrent fault probability of each accessory in the accessory system.

[0030] According to an embodiment of the present application, after calculating the comprehensive safety entropy of the lithium-ion battery system, the method further includes:

[0031] Send the comprehensive safety entropy to the battery control unit;

[0032] Through the battery control unit, control the operating state of the lithium-ion battery system according to the comprehensive safety entropy.

[0033] In a second aspect, the present application provides a safety entropy evaluation device for a lithium-ion battery system considering concurrent faults. The lithium-ion battery system includes a battery body and system accessories. The device includes:

[0034] An acquisition module for acquiring the historical fault information of the system accessories and the battery parameters of the battery body;

[0035] A first processing module, configured to determine the accessory failure probability and the concurrent failure probability of the lithium-ion battery system according to the historical failure information through an accessory failure probability model and a concurrent failure probability model of the lithium-ion battery system;

[0036] A second processing module, configured to determine the occasional failure probability of the lithium-ion battery system according to the battery parameters based on an occasional failure probability model of the lithium-ion battery system;

[0037] A third processing module, configured to calculate the comprehensive failure probability and the non-failure probability of the lithium-ion battery system according to the accessory failure probability, the concurrent failure probability, and the occasional failure probability;

[0038] A fourth processing module, configured to calculate the comprehensive safety entropy of the lithium-ion battery system according to the comprehensive failure probability and the non-failure probability.

[0039] In a third aspect, the present application provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the method for evaluating the safety entropy of a lithium-ion battery system considering concurrent failures as described in the first aspect above is implemented.

[0040] In a fourth aspect, the present application provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method for evaluating the safety entropy of a lithium-ion battery system considering concurrent failures as described in the first aspect above is implemented.

[0041] In a fifth aspect, the present application provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor, and the processor is configured to run a program or an instruction to implement the method for evaluating the safety entropy of a lithium-ion battery system considering concurrent failures as described in the first aspect.

[0042] In a sixth aspect, the present application provides a computer program product, including a computer program. When the computer program is executed by a processor, the method for evaluating the safety entropy of a lithium-ion battery system considering concurrent failures as described in the first aspect above is implemented.

[0043] Additional aspects and advantages of the present application will be given in part in the following description, become apparent in part from the following description, or be learned through the practice of the present application.

[0044] A method and device for evaluating the safety entropy of a lithium-ion battery system considering concurrent failures provided by the present application have the following beneficial effects compared with the prior art:

[0045] (1) By splitting the faults of the lithium-ion battery system into concurrent faults caused by system accessory faults and sporadic faults of the battery body, predicting the concurrent fault probability and sporadic fault probability respectively, analyzing the correlation between the faults of the lithium-ion battery system, and calculating the comprehensive safety entropy to integrate the concurrent faults of system components and the sporadic faults of the lithium-ion battery body, it is possible to comprehensively and quantitatively analyze concurrent faults and sporadic faults, improve the accuracy of fault analysis, and achieve real-time safety assessment of the lithium-ion battery system.

[0046] (2) Build fault probability models for different fault categories, model the concurrent fault probability, use neural network algorithms to model the sporadic faults of the lithium-ion battery itself. In the safety entropy modeling, the concurrent faults of system components and the sporadic faults of the lithium-ion battery body are integrated, and the concurrent faults caused by accessory faults and the sporadic faults of itself are comprehensively considered, analyzing the correlation between the faults of the lithium-ion battery system. Compared with fault trees and safety domain models, through comprehensive safety entropy evaluation, this application considers the impact of fault uncertainty on the safety of lithium-ion batteries and realizes real-time safety entropy evaluation of the lithium-ion battery system. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The above and / or additional aspects and advantages of this application will become apparent and be easily understood from the description of the embodiments in conjunction with the following drawings, where:

[0048] Figure 1 is one of the schematic flowcharts of the safety entropy evaluation method for a lithium-ion battery system considering concurrent faults provided by an embodiment of this application;

[0049] Figure 2 is another schematic flowchart of the safety entropy evaluation method for a lithium-ion battery system considering concurrent faults provided by an embodiment of this application;

[0050] Figure 3 is the schematic structural diagram of the safety entropy evaluation device for a lithium-ion battery system considering concurrent faults provided by an embodiment of this application;

[0051] Figure 4 is the schematic structural diagram of the electronic device provided by an embodiment of this application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0052] Next, the technical solutions in the embodiments of this application will be clearly described in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, rather than all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art belong to the scope of protection of this application.

[0053] The terms "first", "second", etc. in the description and claims of this application are used to distinguish similar objects, rather than to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of this application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are generally of the same category, and do not limit the number of objects. For example, the first object can be one or more. In addition, "and / or" in the description and claims means at least one of the connected objects, and the character " / ", generally represents an "or" relationship between the associated objects before and after.

[0054] The following will, with reference to the accompanying drawings, through specific embodiments and their application scenarios, provide a detailed description of the method for evaluating the safety entropy of a lithium-ion battery system considering concurrent failures, the device for evaluating the safety entropy of a lithium-ion battery system considering concurrent failures, an electronic device, and a readable storage medium provided by the embodiments of this application.

[0055] Among them, the method for evaluating the safety entropy of a lithium-ion battery system considering concurrent failures can be applied to a terminal, and can be specifically executed by hardware or software in the terminal.

[0056] The terminal includes, but is not limited to, portable communication devices such as mobile phones or tablet computers having a touch-sensitive surface (for example, a touch screen display and / or a touchpad). It should also be understood that in some embodiments, the terminal may not be a portable communication device, but a desktop computer having a touch-sensitive surface (for example, a touch screen display and / or a touchpad).

[0057] In the following various embodiments, a terminal including a display and a touch-sensitive surface is described. However, it should be understood that the terminal may include one or more other physical user interface devices such as a physical keyboard, a mouse, and a joystick.

[0058] The method for evaluating the safety entropy of a lithium-ion battery system considering concurrent failures provided by the embodiments of this application, the execution subject of the method for evaluating the safety entropy of a lithium-ion battery system considering concurrent failures can be an electronic device or a functional module or functional entity in the electronic device that can implement the method for evaluating the safety entropy of a lithium-ion battery system considering concurrent failures. The electronic devices mentioned in the embodiments of this application include, but are not limited to, mobile phones, tablet computers, computers, cameras, and wearable devices, etc. The following takes an electronic device as the execution subject to illustrate the method for evaluating the safety entropy of a lithium-ion battery system considering concurrent failures provided by the embodiments of this application.

[0059] Among them, the lithium-ion battery system includes a battery body and system accessories.

[0060] It should be noted that the lithium-ion battery system consists of a battery body and various system accessories. The system accessories include key components such as a battery management system, sensors, and connection components. These components are affected by various factors during operation, such as design defects, manufacturing process deviations, working condition fluctuations, and external environment changes. Different types of system accessory failures may occur, affecting the overall performance and safety of the lithium-ion battery system.

[0061] As Figure 1 shown, the safety entropy evaluation method for the lithium-ion battery system considering concurrent failures includes:

[0062] Step 110: Obtain the historical failure information of the system accessories and the battery parameters of the battery body;

[0063] Step 120: Determine the accessory failure probability and the concurrent failure probability of the lithium-ion battery system according to the historical failure information through the accessory failure probability model and the concurrent failure probability model of the lithium-ion battery system;

[0064] Step 130: Based on the sporadic failure probability model of the lithium-ion battery system, determine the sporadic failure probability of the lithium-ion battery system according to the battery parameters;

[0065] Step 140: Calculate the comprehensive failure probability and the non-failure probability of the lithium-ion battery system according to the accessory failure probability, the concurrent failure probability, and the sporadic failure probability;

[0066] Step 150: Calculate the comprehensive safety entropy of the lithium-ion battery system according to the comprehensive failure probability and the non-failure probability.

[0067] It can be understood that the failures of the lithium-ion battery are divided into two types. The first type is that due to system accessory failures, the battery fails due to changes in battery working conditions; the second type is sporadic failures during battery operation. Therefore, an accessory failure probability model and a sporadic failure probability model of the battery system can be established respectively.

[0068] In some embodiments, determining the accessory failure probability and the concurrent failure probability of the lithium-ion battery system according to the historical failure information through the accessory failure probability model and the concurrent failure probability model of the lithium-ion battery system includes:

[0069] Input the historical failure information into the accessory failure probability model to obtain the failure probability of each accessory in the accessory system output by the accessory failure probability model, so as to determine the accessory failure probability of each accessory causing the lithium-ion battery system to fail. The accessory failure probability model is constructed based on a long short-term memory network;

[0070] Based on the probability of each accessory causing a failure in the lithium-ion battery system and the concurrent failure probability model, determine the concurrent failure probability of each accessory in the accessory system.

[0071] Since the failures of system accessories often have complex temporal correlations, and their failure modes and probability distributions change over time, it is crucial to accurately predict the failures of system accessories.

[0072] In terms of failure prediction, the Long Short-Term Memory (LSTM) network, with its powerful modeling ability for time series data, can capture the temporal correlation characteristics of failure occurrences and become an ideal tool for handling dynamic failure analysis. The LSTM network can effectively capture long-term dependencies in data and performs particularly well when analyzing and predicting the temporal correlation characteristics of system accessory failures. When predicting the failure probability of system accessories in a lithium-ion battery system, the occurrence probability data of system accessories at the previous N time instants can be used as inputs to form a time series data set. The LSTM network models the characteristics of these input data, learns the dynamic change rules of these data, and extracts the potential patterns of failure evolution, thereby more accurately predicting the random failure probability at the t-th time instant.

[0073] Based on the trained accessory failure probability model, the random failure probability at time t can be output:

[0074]

[0075] where represents the failure occurrence probability of each component of the lithium-ion battery system at time instant; represents the failure occurrence probability of the system accessory at time instant;

[0076] Since accessory failures have a direct and significant impact on the operating conditions of the lithium-ion battery system, it can be reasonably considered that accessory failures will necessarily trigger failures in the lithium-ion battery system. Therefore, in probability modeling, the concurrent failure probability of the lithium-ion battery system can be directly corresponded to the accessory failure probability, that is:

[0077]

[0078] where represents the accessory failure probability that causes the lithium-ion battery system to fail due to the system accessory at time t, represents the failure probability of the system accessory i at time t, and establish the failure types of the lithium-ion battery system caused by different accessory failures.

[0079] Among them, the faults of the ion battery system may include internal short - circuit faults, over - charge faults, over - discharge faults, thermal runaway faults, and gas leakage faults, etc.

[0080] An internal short - circuit fault is caused by damage to the internal structure of the battery, resulting in a short - circuit, manifested as a rapid voltage drop and heat generation; an over - charge fault is that the voltage is too high during the battery charging process, which may lead to internal thermal runaway or decomposition reaction; an over - discharge fault is that the voltage is too low during the battery discharging process, which may lead to capacity attenuation or failure; a thermal runaway fault is an uncontrollable reaction caused by a sharp increase in internal temperature, which may cause fire or explosion; a gas leakage fault is due to abnormal pressure or damaged housing, resulting in gas leakage inside the battery. The concurrent fault probabilities are shown in Table 1.

[0081] Table 1 Concurrent fault probabilities of lithium - ion battery systems

[0082]

[0083] For the concurrent fault modeling of the lithium - ion battery system, count the number of faults of system accessories such as the battery management system / sensors / connection components in historical data, and record the number of internal short - circuit faults / over - charge faults / over - discharge faults / thermal runaway faults / gas leakage faults caused respectively. Use the fault frequency equivalent to probability to obtain the concurrent fault probability model. In the concurrent fault probability model, the concurrent fault probability represents the probability of a fault in the lithium - ion battery system caused by the fault of the system accessories . .

[0084] In some embodiments, the accidental fault probability model is constructed based on a BP neural network;

[0085] The battery parameters include the output current, voltage, surface temperature of the battery body, and internal gas - generating pressure inside the battery pack;

[0086] The accidental fault probability includes the fault probability and non - fault probability of accidental faults. The fault types of accidental faults include at least one of internal short - circuit faults, over - charge faults, over - discharge faults, thermal runaway faults, and gas leakage faults.

[0087] To effectively diagnose the accidental faults of the lithium - ion battery system, an accidental fault probability model based on the BackPropagation (BP) neural network can be constructed, using the output current , voltage , surface temperature of the battery and internal gas - generating pressure inside the battery pack of the lithium - ion battery system as input features, and taking the probabilities of different faults and non - faults of the lithium - ion battery system as output.

[0088] The BP neural network includes an input layer, a hidden layer and an output layer. The number of nodes in the input layer is 4, corresponding to the four input features I, V, T, and P. In the hidden layer, the appropriate number of hidden layers and nodes are set through experimental optimization to ensure that the model has sufficient nonlinear expression capabilities. In the output layer, the number of nodes is 6, corresponding to the probabilities of no fault and five types of faults.

[0089]

[0090] in, express The probability of failure-free lithium-ion battery system at any moment, exist Time indicates occasional failures of different types of lithium-ion battery systems The probability that the output current ,Voltage , Battery surface temperature And the gas pressure inside the battery pack is the battery parameter.

[0091] The concurrent failure probability model and the accidental failure probability model of lithium-ion battery system are combined to redefine the comprehensive failure probability of lithium-ion battery system.

[0092] In some embodiments, calculating the comprehensive failure probability and the no-failure probability of the lithium-ion battery system according to the concurrent failure probability and the occasional failure probability includes:

[0093] Determining the probability of different types of failures of the lithium-ion battery system based on the concurrent failure probability and the accidental failure probability;

[0094] The comprehensive failure probability and no-failure probability are determined according to the failure probabilities of different types.

[0095] In some embodiments, the comprehensive failure probability is:

[0096]

[0097] in, Indicated in Moment, lithium-ion battery system fails The comprehensive failure probability, , is the total number of attachments in the system attachments, It shows that at time t, due to the system accessories The probability of accessory failure causing a lithium-ion battery system failure, is the probability of concurrent failures, is the probability of accidental failure at time t, is the total number of failures, is the probability of no failure of the lithium-ion battery system at time

[0098] The probability of no failure of the lithium-ion battery system is:

[0099]

[0100] wherein, is the probability of no failure of the lithium-ion battery system at time

[0101] After obtaining the fault types of the lithium-ion battery system and their corresponding comprehensive fault probabilities, the safety evaluation of the lithium-ion battery system can be carried out based on this information. The comprehensive safety evaluation of the lithium-ion battery system depends on the probabilities of various types of faults occurring. If the probabilities of multiple faults are more evenly distributed, it means that each type of fault needs to be prevented and controlled. If the fault probability is concentrated on a certain type of fault, it means that only the prevention and control of this type of fault need to be done well. Therefore, based on the information entropy theory, the concept of safety entropy is introduced to conduct a more accurate quantitative analysis of the safety state of the lithium-ion battery system.

[0102] In some embodiments, the comprehensive safety entropy of the lithium-ion battery system is:

[0103]

[0104] wherein, is the comprehensive safety entropy of the lithium-ion battery system, is the total number of failures, is at time the comprehensive fault probability of the lithium-ion battery system having a fault .

[0105] According to the method for evaluating the safety entropy of a lithium-ion battery system considering concurrent faults provided by the embodiments of the present application, by splitting the faults of the lithium-ion battery system into concurrent faults caused by system accessory faults and accidental faults of the battery body, predicting the concurrent fault probability and the accidental fault probability respectively, analyzing the correlation between the faults of the lithium-ion battery system, and calculating the comprehensive safety entropy, integrating the concurrent faults of system components and the accidental faults of the lithium battery body, it is possible to comprehensively conduct a quantitative analysis of concurrent faults and accidental faults, improve the accuracy of fault analysis, and realize the real-time safety evaluation of the lithium-ion battery system.

[0106] In some embodiments, after calculating the comprehensive safety entropy of the lithium-ion battery system, the method further includes:

[0107] Sending the comprehensive safety entropy to the battery control unit;

[0108] Through the battery control unit, the operating state of the lithium-ion battery system is controlled according to the comprehensive safety entropy.

[0109] In actual implementation, the comprehensive safety entropy is sent to the Electric Control Unit (ECU), and the ECU controls the operating state of the lithium-ion battery system according to the comprehensive safety entropy. For example, whether to continue operating.

[0110] This application also provides an embodiment.

[0111] As Figure 2 shown, on the one hand, through the accessory fault probability modeling method of the lithium-ion battery system, the probability model of different types of faults in the lithium-ion battery system caused by different accessory faults of the lithium-ion battery system is obtained by using the LSTM neural network, the accessory fault probability model is obtained, and the random fault probability is obtained , and the corresponding accessory fault probability is determined according to the random fault probability .

[0112] Concurrent fault modeling is performed on the lithium-ion battery system to obtain a concurrent fault probability model and obtain the concurrent fault probability .

[0113] On the other hand, through the occasional fault probability modeling method of the lithium-ion battery system, an occasional fault diagnosis model of the lithium-ion battery system is established by using the BP neural network.

[0114] Obtain the accessory fault probability of the lithium-ion battery system , concurrent fault probability and occasional fault probability .

[0115] By calculating the comprehensive fault probability of different faults occurring in the lithium-ion battery system at the current operating moment and the non-fault probability , the comprehensive safety entropy of the lithium-ion battery system at the current moment is given according to the safety entropy model .

[0116] The comprehensive safety entropy of the lithium-ion battery system is transmitted to the ECU to determine whether to continue operating. If it continues to operate, then loop to execute obtaining the accessory fault probability of the lithium-ion battery system , concurrent fault probability and occasional fault probability to recalculate the comprehensive safety entropy to achieve closed-loop control.

[0117] In this embodiment, a fault probability model is constructed for different fault categories. The Markov chain is used to model the concurrent fault probability, and the neural network algorithm is used to model the sporadic faults of the lithium battery itself. In the safety entropy modeling, the concurrent faults of system components and the sporadic faults of the lithium battery body are integrated. The concurrent faults and sporadic faults caused by accessory faults are comprehensively considered, and the correlation between faults in the lithium-ion battery system is analyzed. Compared with the fault tree and safety domain model, through comprehensive safety entropy evaluation, this application considers the impact of fault uncertainty on the safety of lithium-ion batteries and realizes the real-time safety entropy evaluation of the lithium-ion battery system.

[0118] The method for evaluating the safety entropy of a lithium-ion battery system considering concurrent faults provided by the embodiment of this application may have an execution entity as a device for evaluating the safety entropy of a lithium-ion battery system considering concurrent faults. In the embodiment of this application, taking the device for evaluating the safety entropy of a lithium-ion battery system considering concurrent faults executing the method for evaluating the safety entropy of a lithium-ion battery system considering concurrent faults as an example, the device for evaluating the safety entropy of a lithium-ion battery system considering concurrent faults provided by the embodiment of this application is described.

[0119] The embodiment of this application also provides a device for evaluating the safety entropy of a lithium-ion battery system considering concurrent faults.

[0120] As Figure 3 shown, the device for evaluating the safety entropy of a lithium-ion battery system considering concurrent faults includes:

[0121] An acquisition module 310, configured to acquire historical fault information of the system accessories and battery parameters of the battery body;

[0122] A first processing module 320, configured to determine the accessory fault probability and concurrent fault probability of the lithium-ion battery system according to the historical fault information through an accessory fault probability model and a concurrent fault probability model of the lithium-ion battery system;

[0123] A second processing module 330, configured to determine the sporadic fault probability of the lithium-ion battery system according to the battery parameters based on the sporadic fault probability model of the lithium-ion battery system;

[0124] A third processing module 340, configured to calculate the comprehensive fault probability and fault-free probability of the lithium-ion battery system according to the accessory fault probability, the concurrent fault probability, and the sporadic fault probability;

[0125] A fourth processing module 350, configured to calculate the comprehensive safety entropy of the lithium-ion battery system according to the comprehensive fault probability and the fault-free probability.

[0126] According to the lithium-ion battery system safety entropy evaluation device considering concurrent faults provided by the embodiments of the present application, by splitting the faults of the lithium-ion battery system into concurrent faults caused by system accessory faults and occasional faults of the battery body, predicting the concurrent fault probability and the occasional fault probability respectively, analyzing the correlation between the faults of the lithium-ion battery system, and calculating the comprehensive safety entropy, the concurrent faults of system components and the occasional faults of the lithium battery body are integrated, enabling a comprehensive quantitative analysis of concurrent faults and occasional faults, improving the accuracy of fault analysis, and realizing the real-time safety evaluation of the lithium-ion battery system.

[0127] The lithium-ion battery system safety entropy evaluation device considering concurrent faults in the embodiments of the present application can be an electronic device or a component in an electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal or other devices other than terminals. Exemplarily, the electronic device can be a mobile phone, a tablet computer, a laptop computer, a handheld computer, an in-vehicle electronic device, a Mobile Internet Device (MID), an Augmented Reality (AR) / Virtual Reality (VR) device, a robot, a wearable device, an Ultra-Mobile Personal Computer (UMPC), a netbook, or a Personal Digital Assistant (PDA), etc. It can also be a server, a Network Attached Storage (NAS), a Personal Computer (PC), a Television (TV), a teller machine, or a self-service machine, etc. The embodiments of the present application do not make specific limitations.

[0128] The lithium-ion battery system safety entropy evaluation device considering concurrent faults in the embodiments of the present application can be a device with an operating system. The operating system can be the Android operating system, the iOS operating system, or other possible operating systems. The embodiments of the present application do not make specific limitations.

[0129] The lithium-ion battery system safety entropy evaluation device considering concurrent faults provided by the embodiments of the present application can implement each process realized by the embodiments of the lithium-ion battery system safety entropy evaluation method considering concurrent faults as described in the above embodiments. To avoid repetition, it will not be elaborated here.

[0130] In some embodiments, such as Figure 4As shown in the figure, an embodiment of the present application further provides an electronic device 400, including a processor 401, a memory 402, and a computer program stored on the memory 402 and executable on the processor 401. When the program is executed by the processor 401, it implements each process of the above-mentioned embodiment of the safety entropy evaluation method for a lithium-ion battery system considering concurrent faults, and can achieve the same technical effects. To avoid repetition, it will not be elaborated here.

[0131] It should be noted that the electronic device in the embodiment of the present application includes the above-mentioned mobile electronic device and non-mobile electronic device.

[0132] An embodiment of the present application further provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements each process of the above-mentioned embodiment of the safety entropy evaluation method for a lithium-ion battery system considering concurrent faults, and can achieve the same technical effects. To avoid repetition, it will not be elaborated here.

[0133] Among them, the processor is the processor in the electronic device in the above-mentioned embodiment. The readable storage medium includes computer-readable storage media, such as computer read-only memory (Read-Only Memory, ROM), random access memory (RandomAccess Memory, RAM), magnetic disk, or optical disc, etc.

[0134] An embodiment of the present application further provides a computer program product, including a computer program. When the computer program is executed by a processor, it implements the above-mentioned safety entropy evaluation method for a lithium-ion battery system considering concurrent faults.

[0135] Among them, the processor is the processor in the electronic device in the above-mentioned embodiment. The readable storage medium includes computer-readable storage media, such as computer read-only memory ROM, random access memory RAM, magnetic disk, or optical disc, etc.

[0136] Another embodiment of the present application provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor, and the processor is used to run a program or instruction to implement each process of the above-mentioned embodiment of the safety entropy evaluation method for a lithium-ion battery system considering concurrent faults, and can achieve the same technical effects. To avoid repetition, it will not be elaborated here.

[0137] It should be understood that the chip mentioned in the embodiment of the present application may also be referred to as a system-on-chip, system chip, chip system, or system-on-chip, etc.

[0138] It should be noted that in this text, the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, article or device including a series of elements not only includes those elements but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the process, method, article or device including such element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in a reverse order according to the functions involved. For example, the described methods may be performed in an order different from that described, and various steps may be added, omitted, or combined. Additionally, the features described with reference to certain examples may be combined in other examples.

[0139] Through the description of the above embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus a necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases the former is a better implementation. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. The computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to enable a terminal (which can be a mobile phone, computer, server, or network device, etc.) to execute the method for evaluating the safety entropy of a lithium-ion battery system considering concurrent failures in each embodiment of the present application.

[0140] In the description of the present application, "the first feature", "the second feature" may include one or more of such features.

[0141] In the description of the present application, the meaning of "a plurality of" is two or more.

[0142] The embodiments of the present application have been described above in conjunction with the accompanying drawings. However, the present application is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Those of ordinary skill in the art, under the inspiration of the present application and without departing from the spirit and scope protected by the claims of the present application, can also make many forms, all of which fall within the protection scope of the present application.

[0143] In the description of this specification, the descriptions referring to terms such as "one embodiment", "some embodiments", "schematic embodiments", "examples", "specific examples", or "some examples", etc., mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0144] Although the embodiments of the present application have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and purposes of the present application, and the scope of the present application is defined by the claims and their equivalents.

Claims

1. A safety entropy assessment method for a lithium-ion battery system considering concurrent failures, characterized in that: The lithium-ion battery system includes a battery body and system accessories, and the method includes: Acquire historical fault information of the system accessories and battery parameters of the battery body; Determine the accessory failure probability and concurrent failure probability of the lithium-ion battery system according to the historical failure information by using an accessory failure probability model and a concurrent failure probability model of the lithium-ion battery system; Based on the accidental failure probability model of the lithium-ion battery system, determining the accidental failure probability of the lithium-ion battery system according to the battery parameters; Calculating the comprehensive failure probability and the no-failure probability of the lithium-ion battery system according to the accessory failure probability, the concurrent failure probability and the occasional failure probability; The comprehensive safety entropy of the lithium-ion battery system is calculated according to the comprehensive failure probability and the no-fault probability.

2. The method for evaluating safety entropy of a lithium-ion battery system considering concurrent failures according to claim 1 is characterized in that: Calculating the comprehensive failure probability and the no-failure probability of the lithium-ion battery system according to the concurrent failure probability and the occasional failure probability includes: Determining the probability of different types of failures of the lithium-ion battery system based on the concurrent failure probability and the accidental failure probability; The comprehensive failure probability and no-failure probability are determined according to the failure probabilities of different types.

3. The method for evaluating safety entropy of a lithium-ion battery system considering concurrent failures according to claim 2, characterized in that: The comprehensive failure probability is: ； in, Indicated in Moment, lithium-ion battery system fails The comprehensive failure probability, , is the total number of attachments in the system attachments, It is shown that at time t due to the attachment The probability of accessory failure causing a lithium-ion battery system failure, , is the probability of concurrent failures, is the probability of accidental failure at time t, is the total number of failures, yes The probability of no failure of the lithium-ion battery system at any moment; The failure-free probability of a lithium-ion battery system is: ； in, is The probability of failure-free lithium-ion battery system at all times.

4. The method for evaluating safety entropy of a lithium-ion battery system considering concurrent failures according to claim 1, characterized in that: The comprehensive safety entropy of the lithium-ion battery system is: ； in, is the comprehensive safety entropy of the lithium-ion battery system, is the total number of failures, is moment, failure of lithium-ion battery system The comprehensive failure probability, .

5. The method for evaluating safety entropy of a lithium-ion battery system considering concurrent failures according to claim 1, characterized in that: The sporadic failure probability model is constructed based on BP neural network; The battery parameters include the output current, voltage, battery surface temperature and gas production pressure inside the battery pack; The probability of occasional failure includes the probability of failure of occasional failure and the probability of no failure, and the failure type of the occasional failure includes at least one of an internal short circuit failure, an overcharge failure, an over-discharge failure, a thermal runaway failure and a gas leakage failure.

6. The method for evaluating safety entropy of a lithium-ion battery system considering concurrent failures according to claim 1, characterized in that: Determining the accessory failure probability and concurrent failure probability of the lithium-ion battery system according to the historical failure information through an accessory failure probability model and a concurrent failure probability model of the lithium-ion battery system, including: Inputting the historical fault information into an accessory fault probability model to obtain a fault probability of each accessory in the accessory system output by the accessory fault probability model, so as to determine the accessory fault probability of each accessory causing a fault in the lithium-ion battery system, wherein the accessory fault probability model is constructed based on a long short-term memory network; The concurrent failure probability of each accessory in the accessory system is determined based on the probability that each accessory causes the lithium-ion battery system to fail and the concurrent failure probability model.

7. The method for evaluating safety entropy of a lithium-ion battery system considering concurrent failures according to claim 1, characterized in that: After calculating the comprehensive safety entropy of the lithium-ion battery system, the method further includes: sending the comprehensive safety entropy to a battery control unit; The battery control unit is used to control the operating state of the lithium-ion battery system according to the comprehensive safety entropy.

8. A lithium-ion battery system safety entropy assessment device considering concurrent failures, characterized in that: The lithium-ion battery system includes a battery body and system accessories, and the device includes: An acquisition module, used for acquiring historical fault information of the system accessories and battery parameters of the battery body; A first processing module, configured to determine an accessory failure probability and a concurrent failure probability of the lithium-ion battery system according to the historical failure information by using an accessory failure probability model and a concurrent failure probability model of the lithium-ion battery system; A second processing module, configured to determine the probability of accidental failure of the lithium-ion battery system according to the battery parameters based on the accidental failure probability model of the lithium-ion battery system; A third processing module, used to calculate the comprehensive failure probability and the no-failure probability of the lithium-ion battery system according to the accessory failure probability, the concurrent failure probability and the occasional failure probability; The fourth processing module is used to calculate the comprehensive safety entropy of the lithium-ion battery system according to the comprehensive failure probability and the no-fault probability.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method for evaluating safety entropy of a lithium-ion battery system taking concurrent failures into consideration is implemented as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for evaluating safety entropy of a lithium-ion battery system taking concurrent failures into consideration as described in any one of claims 1 to 7 is implemented.

Images