Fuel cell system safe operation control method and device considering concurrent faults, and medium

Abstract

The invention discloses a fuel cell system safe operation control method and device considering concurrent faults and a medium, and relates to the technical field of battery safety, and the method comprises the steps: obtaining the probability of accessory faults of each accessory based on an accessory fault probability model of each accessory, and determining the concurrent probability of different types of battery faults; based on the fuel cell fault information and a fuel cell accidental fault diagnosis model, determining accidental probabilities of occurrence of different types of cell faults and no-cell faults; based on the concurrency probability and the accidental probability of occurrence of different types of battery faults and the accidental probability of no battery fault, determining the comprehensive probability of occurrence of different types of battery faults and no battery fault; determining the safety dispersion of the fuel cell system based on the comprehensive probability of occurrence of different types of cell faults and non-cell faults; the operation of the fuel cell system is controlled using the safety dispersion of the fuel cell system. And the safe operation of the fuel cell system is ensured.

Description

Technical Field

[0001] The present application relates to the field of battery safety technology, and in particular to a method, device, and medium for controlling the safe operation of a fuel cell system taking concurrent failures into consideration. Background Art

[0002] Fuel cell systems include air supply, hydrogen supply, and cooling subsystems, and their operation requires the coordinated operation of multiple components. Any component failure directly impacts fuel cell operating conditions and can easily lead to secondary failures. Currently, modeling of secondary failures in fuel cells typically utilizes methods such as fault trees and Petri nets, which can only provide qualitative analysis of secondary failures.

[0003] In a fuel cell system safety domain modeling method, the multi-type fault constraints of the fuel cell system are comprehensively considered to construct its safe operation boundary, and then a three-dimensional safety domain model of the fuel cell system is established, which realizes the safety quantitative assessment of the fuel cell operating status. However, it is difficult to analyze the correlation characteristics between accessory failures and fuel cell body failures.

[0004] The fault tree theory was used to qualitatively analyze the failures of each subsystem of the fuel cell, analyze the correlation between subsystem failures and stack failures, and use neural networks to realize fuel cell fault diagnosis. However, it only considers concurrent failures. Even when the accessories are normal, the fuel cell may still fail.

[0005] The above methods all make it impossible to ensure the operational safety of the fuel cell system. Summary of the Invention

[0006] The purpose of this application is to provide a fuel cell system safe operation control method, device and medium taking into account concurrent failures, so as to solve the problem of relatively one-sided failure analysis of the fuel cell system.

[0007] To achieve the above objectives, this application provides the following solutions.

[0008] In a first aspect, the present application provides a method for controlling safe operation of a fuel cell system taking concurrent failures into consideration, comprising: Determine any moment during the operation of the fuel cell system to be controlled as the current moment; Inputting the current time into an accessory failure probability model of each accessory in the fuel cell system to be controlled to obtain the probability of accessory failure of each accessory at the current time; the accessory failure probability model is a bathtub curve, where the horizontal axis of the bathtub curve is time and the vertical axis is the probability of accessory failure; Determining, based on the probability of each accessory failure occurring at the current moment, concurrent probabilities of different types of battery failures occurring in the fuel cell system to be controlled; Obtaining fuel cell fault information of the fuel cell system to be controlled at the current moment; the fuel cell fault information includes: stack current, voltage, temperature, cathode inlet pressure, anode inlet pressure, cathode exhaust pressure, anode exhaust pressure, coolant inlet temperature and coolant outlet temperature; Determining the occasional probability of different types of battery failures and the occasional probability of no battery failure in the fuel cell system to be controlled at the current moment based on the fuel cell fault information of the fuel cell system to be controlled at the current moment and a fuel cell occasional fault diagnosis model obtained by training a back-propagation neural network; Determining, based on the concurrent probability and occasional probability of different types of battery failures occurring in the fuel cell system to be controlled at the current moment and the occasional probability of no battery failure, the comprehensive probability of different types of battery failures occurring in the fuel cell system to be controlled and the comprehensive probability of no battery failure at the current moment; Determining the safety discreteness of the fuel cell system to be controlled at the current moment based on the comprehensive probability of different types of battery failures occurring in the fuel cell system to be controlled at the current moment and the comprehensive probability of no battery failure; The operation of the fuel cell system to be controlled is controlled by utilizing the safety discreteness of the fuel cell system to be controlled at the current moment.

[0009] Optionally, the accessory failure probability model of any accessory includes: ; ; ; ; in, is the probability of accessory failure at time t; is the probability of early failure of the accessory at time t; is the probability of failure of the accessory at the time t; is the probability of accidental failure of the accessory at time t; is the shape parameter; Dimensional parameters of the attachment; Long short-term memory network; is the probability of accessory failure at time tn; is the probability of accessory failure at time tn-1; is the probability of accessory failure at time t-1.

[0010] Optionally, based on the fuel cell fault information of the fuel cell system to be controlled at the current moment and the fuel cell occasional fault diagnosis model, determining the occasional probability of different types of battery faults occurring in the fuel cell system to be controlled at the current moment and the occasional probability of no battery fault, including: Performing Gaussian filtering on the fuel cell fault information of the fuel cell system to be controlled at the current moment to obtain the Gaussian filtered fuel cell fault information of the fuel cell system to be controlled at the current moment; The fuel cell fault information after Gaussian filtering at the current moment of the fuel cell system to be controlled is input into the fuel cell occasional fault diagnosis model to obtain the occasional probability of different types of battery faults and the occasional probability of no battery fault occurring in the fuel cell system to be controlled at the current moment.

[0011] Optionally, the process of determining the fuel cell occasional fault diagnosis model includes: Obtain fuel cell fault information of multiple sample fuel cell systems at various times, and the occasional probability of different types of cell faults occurring at corresponding times and the occasional probability of no cell faults; Performing Gaussian filtering on the fuel cell fault information of each sample fuel cell system at each moment to obtain the fuel cell fault information after Gaussian filtering of each sample fuel cell system at each moment; Initialize the back-propagation neural network; The fuel cell fault information after Gaussian filtering of each sample fuel cell system at each moment is used as input, and the occasional probability of different types of battery faults and the occasional probability of no battery fault occurring at the corresponding moment of the sample fuel cell system are used as output. The back propagation neural network is trained to obtain the fuel cell occasional fault diagnosis model.

[0012] Optionally, based on the concurrent probability and occasional probability of different types of battery failures occurring in the fuel cell system to be controlled at the current moment and the occasional probability of no battery failure, determining the comprehensive probability of different types of battery failures occurring in the fuel cell system to be controlled at the current moment and the comprehensive probability of no battery failure, includes: Calculating the comprehensive probability of different types of battery failures occurring in the fuel cell system to be controlled at the current moment using the first comprehensive fault calculation formula based on the concurrent probability and occasional probability of different types of battery failures occurring in the fuel cell system to be controlled at the current moment and the occasional probability of no battery failure; The second comprehensive fault calculation formula is used to calculate the comprehensive probability that the fuel cell system to be controlled has no battery faults at the current moment, based on the concurrent probability and occasional probability of different types of battery faults occurring in the fuel cell system to be controlled at the current moment and the occasional probability of no battery faults.

[0013] Optionally, the first comprehensive fault calculation formula includes: ; in, is the comprehensive probability of the jth type of battery failure occurring in the fuel cell system at time t; is the number of accessories in the fuel cell system; is the concurrent probability of battery failure caused by the i-th accessory at time t; is the probability that the jth type of battery failure is caused by the i-th accessory failure; is the accidental probability of the jth type of battery failure occurring in the fuel cell system at time t; The number of types of battery failure; is the accidental probability that there is no battery failure in the fuel cell system at time t.

[0014] Optionally, the second comprehensive fault calculation formula includes: ; in, is the comprehensive probability that the fuel cell system has no battery failure at time t.

[0015] Optionally, determining the safety discreteness of the fuel cell system to be controlled at the current moment based on the comprehensive probability of different types of battery failures occurring in the fuel cell system to be controlled at the current moment and the comprehensive probability of no battery failure includes: The safety dispersion calculation formula is used to calculate the safety dispersion of the fuel cell system to be controlled at the current moment based on the comprehensive probability of different types of battery failures occurring in the fuel cell system to be controlled at the current moment and the comprehensive probability of no battery failure. The safety dispersion calculation formula includes: ; ; ; in, is the safety discreteness of the fuel cell system at time t; is a natural constant; is the first-level safety evaluation value of the fuel cell system at time t; is the second-level safety evaluation value of the fuel cell system at time t.

[0016] In a second aspect, the present application provides a computer device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any of the above-described methods for controlling safe operation of a fuel cell system taking concurrent failures into consideration.

[0017] In a third aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-mentioned methods for controlling safe operation of a fuel cell system taking concurrent failures into consideration.

[0018] According to the specific embodiments provided in this application, this application discloses the following technical effects: The present application discloses a method, device and medium for controlling the safe operation of a fuel cell system taking concurrent failures into consideration. First, any moment in the operation process of the fuel cell system to be controlled is determined as the current moment; secondly, the current moment is input into the accessory failure probability model of each accessory in the fuel cell system to be controlled to obtain the probability of accessory failure of each accessory at the current moment; based on the probability of accessory failure of each accessory at the current moment, the concurrent probability of different types of battery failures occurring in the fuel cell system to be controlled at the current moment is determined; then, the fuel cell fault information of the fuel cell system to be controlled at the current moment is obtained; based on the fuel cell fault information of the fuel cell system to be controlled at the current moment and the fuel cell occasional fault diagnosis model, the concurrent probability of different types of battery failures occurring in the fuel cell system to be controlled at the current moment is determined. The control fuel cell system at the current moment has the occasional probability of different types of battery failures and the occasional probability of no battery failure; then, based on the concurrent probability and occasional probability of different types of battery failures and the occasional probability of no battery failure of the control fuel cell system at the current moment, the comprehensive probability of different types of battery failures and the comprehensive probability of no battery failure of the control fuel cell system are determined; again, based on the comprehensive probability of different types of battery failures and the comprehensive probability of no battery failure of the control fuel cell system at the current moment, the safety discreteness of the control fuel cell system at the current moment is determined; finally, the safety discreteness of the control fuel cell system at the current moment is used to control the operation of the control fuel cell system. This application comprehensively considers the concurrent failures caused by accessory failures and the occasional failures themselves, analyzes the correlation between fuel cell system failures, and proposes a safety discreteness assessment method compared to the fault tree and safety domain model, taking into account the impact of failure uncertainty on safety, realizing real-time safety assessment of the fuel cell system, and ensuring the safe operation of the fuel cell system. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0020] Figure 1 A flowchart of a method for controlling safe operation of a fuel cell system taking concurrent failures into consideration is provided in accordance with an embodiment of the present application.

[0021] Figure 2 Schematic diagram of the safe operation control architecture of the fuel cell system considering concurrent failures.

[0022] Figure 3 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0024] The purpose of this application is to provide a fuel cell system safe operation control method, device and medium taking into account concurrent failures, aiming to comprehensively consider the concurrent failures caused by accessory failures and the occasional failures themselves, and analyze the correlation between fuel cell system failures.

[0025] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0026] In an exemplary embodiment, Figure 1 and Figure 2 As shown, the fuel cell system safe operation control method considering concurrent failures in this embodiment includes steps 1 to 8.

[0027] Step 1: Determine any moment during the operation of the fuel cell system to be controlled as the current moment.

[0028] Step 2: Input the current moment into the accessory failure probability model of each accessory in the fuel cell system to be controlled, and obtain the probability of accessory failure of each accessory at the current moment.

[0029] The accessory failure probability model is a bathtub curve, where the horizontal axis of the bathtub curve is time and the vertical axis is the probability of a non-attachment failure.

[0030] Specifically, the failure probability function of each battery accessory is a function of time, and the accessory failure probability model is a bathtub curve. Based on the characteristics of the bathtub curve, it can be divided into early failure period, accidental failure period, and wear-out failure period. Therefore, the accessory failure probability model can be split into the superposition of models for these three periods. Early failure and wear-out failure follow a certain pattern, and the two-parameter Weibull distribution can be used to characterize the early failure and wear-out failure probabilities. A particle swarm optimization algorithm is used to fit the fuel cell accessory bathtub curve.

[0031] Occasional failures can be regarded as random failures, and their distribution is the original data minus the probability of early failure and the probability of wear-out failure. The probability of accidental failure can be predicted using the Long Short-Term Memory (LSTM) network.

[0032] As an optional implementation, the accessory failure probability model of any accessory includes: .

[0033] .

[0034] .

[0035] .

[0036] in, is the probability of accessory failure at time t; is the probability of early failure of the accessory at time t; is the probability of failure of the accessory at the time t; is the probability of accidental failure of the accessory at time t; is the shape parameter; Dimensional parameters of the attachment; Long short-term memory network; is the probability of accessory failure at time tn; is the probability of accessory failure at time tn-1; is the probability of accessory failure at time t-1.

[0037] Step 3: Based on the probability of each accessory failure occurring at the current moment, determine the concurrent probability of different types of battery failures occurring at the current moment in the fuel cell system to be controlled.

[0038] Specifically, if an accessory fails, such as the hydrogen ejector, air compressor, or water pump, the fuel cell system's cathode and anode inlet pressures and coolant inlet temperature will inevitably become abnormal. Therefore, fuel cell failures can be divided into two categories: concurrent failures caused by fuel cell system accessory failures and occasional failures of the fuel cell itself.

[0039] Accessory failure has a significant impact on fuel cell operating conditions. It can be assumed that accessory failure will inevitably cause battery failure. In this case, the probability of concurrent failure can be considered consistent with the probability of accessory failure: .

[0040] in, is the concurrent probability of battery failure caused by the i-th accessory at time t; is the probability of accessory failure of the i-th accessory at time t.

[0041] The types of fuel cell failures caused by different accessory failures are statistically analyzed using Markov chains, and Table 1 is obtained.

[0042] .

[0043] in, is the probability that the jth type of battery failure is caused by the i-th accessory failure, , , is the number of accessories in the fuel cell system, The number of battery failure types.

[0044] Step 4: Obtain the current fuel cell fault information of the fuel cell system to be controlled.

[0045] Among them, fuel cell fault information includes: stack current ,Voltage ,temperature , cathode inlet pressure , anode inlet pressure , cathode exhaust pressure , anode exhaust pressure , coolant inlet temperature and coolant outlet temperature .

[0046] Step 5: Based on the fuel cell fault information of the fuel cell system to be controlled at the current moment and the fuel cell occasional fault diagnosis model, determine the occasional probability of different types of battery faults and the occasional probability of no battery fault in the fuel cell system to be controlled at the current moment.

[0047] Among them, the fuel cell occasional fault diagnosis model is obtained by training the back propagation neural network.

[0048] As an optional implementation, step 5 includes steps 501 and 502.

[0049] Step 501: performing Gaussian filtering on the fuel cell fault information of the fuel cell system to be controlled at the current moment to obtain the Gaussian filtered fuel cell fault information of the fuel cell system to be controlled at the current moment.

[0050] Specifically, the expression of Gaussian filtering is: .

[0051] in, is the Gaussian kernel function; is the data position, if the data window is 3, It can be (-1, 0, 1); is an adjustable parameter.

[0052] Step 502: Input the Gaussian filtered fuel cell fault information of the fuel cell system to be controlled at the current moment into the fuel cell occasional fault diagnosis model to obtain the occasional probability of different types of battery faults and the occasional probability of no battery fault occurring in the fuel cell system to be controlled at the current moment.

[0053] Specifically, the expression of the fuel cell occasional fault diagnosis model is: .

[0054] in, is the accidental probability of no battery failure in the fuel cell system at time t; is the accidental probability of a type 1 battery failure occurring in the fuel cell system at time t; is the accidental probability of a type 2 battery failure occurring in the fuel cell system at time t; is the accidental probability of the Nth type of battery failure occurring in the fuel cell system at time t; It is a back propagation (BP) neural network.

[0055] As an optional implementation, the process of determining the fuel cell occasional fault diagnosis model includes steps 511 to 514.

[0056] Step 511: Obtain fuel cell fault information of multiple sample fuel cell systems at various times, and the occasional probability of different types of cell faults occurring at corresponding times and the occasional probability of no cell faults.

[0057] Step 512: Perform Gaussian filtering on the fuel cell fault information of each sample fuel cell system at each moment to obtain the fuel cell fault information after Gaussian filtering of each sample fuel cell system at each moment.

[0058] Step 513: Initialize the back propagation neural network.

[0059] Step 514: Using the fuel cell fault information after Gaussian filtering of each sample fuel cell system at each moment as input, and the occasional probability of different types of battery failures and the occasional probability of no battery failure at the corresponding moment of the sample fuel cell system as output, a back propagation neural network is trained to obtain a fuel cell occasional fault diagnosis model.

[0060] Step 6: Based on the concurrent probability and occasional probability of different types of battery failures occurring in the fuel cell system to be controlled at the current moment and the occasional probability of no battery failure, determine the comprehensive probability of different types of battery failures occurring in the fuel cell system to be controlled at the current moment and the comprehensive probability of no battery failure.

[0061] As an optional implementation, step 6 includes steps 61 and 62.

[0062] Step 61: Using the first comprehensive fault calculation formula, calculate the comprehensive probability of different types of battery failures occurring in the fuel cell system to be controlled at the current moment based on the concurrent probability and occasional probability of different types of battery failures occurring in the fuel cell system to be controlled at the current moment and the occasional probability of no battery failure.

[0063] As an optional implementation, the first comprehensive fault calculation formula includes: .

[0064] in, is the comprehensive probability of the jth type of battery failure occurring in the fuel cell system at time t; is the number of accessories in the fuel cell system; is the concurrent probability of battery failure caused by the i-th accessory at time t; is the probability that the jth type of battery failure is caused by the i-th accessory failure; is the accidental probability of the jth type of battery failure occurring in the fuel cell system at time t; The number of types of battery failure; is the accidental probability that there is no battery failure in the fuel cell system at time t.

[0065] Step 62: Using the second comprehensive fault calculation formula, based on the concurrent probability and occasional probability of different types of battery faults occurring in the fuel cell system to be controlled at the current moment and the occasional probability of no battery fault, calculate the comprehensive probability that the fuel cell system to be controlled has no battery fault at the current moment.

[0066] As an optional implementation, the second comprehensive fault calculation formula includes: .

[0067] in, is the comprehensive probability that the fuel cell system has no battery failure at time t.

[0068] Step 7: Based on the comprehensive probability of different types of battery failures and the comprehensive probability of no battery failure in the fuel cell system to be controlled at the current moment, determine the safety discreteness of the fuel cell system to be controlled at the current moment.

[0069] As an optional implementation, step 7 includes: The safety discreteness calculation formula is used to calculate the safety discreteness of the fuel cell system to be controlled at the current moment based on the comprehensive probability of different types of battery failures occurring in the fuel cell system to be controlled and the comprehensive probability of no battery failure. The safety discreteness calculation formula includes: .

[0070] .

[0071] .

[0072] in, is the safety discreteness of the fuel cell system at time t; is a natural constant; is the first-level safety evaluation value of the fuel cell system at time t; is the second-level safety evaluation value of the fuel cell system at time t.

[0073] Specifically, the safety evaluation is divided into two levels: the first-level safety evaluation value is used to evaluate the safety and failure probability of fuel cells, and the comprehensive probability of no battery failure can be directly used as an evaluation indicator; the second-level safety evaluation value depends on the comprehensive probability of various types of battery failures. If the comprehensive probability of multiple battery failures is more average, it means that each type of battery failure needs to be prevented and controlled. If the comprehensive probability of battery failure is concentrated on a certain type of battery failure, it means that only this type of battery failure needs to be prevented and controlled.

[0074] Step 8: Using the safety discreteness of the fuel cell system to be controlled at the current moment, the operation of the fuel cell system to be controlled is controlled.

[0075] Specifically, if the safety discreteness of the fuel cell system to be controlled at the current moment exceeds the preset safety entropy range, the operation of the fuel cell system to be controlled is stopped; if the safety discreteness of the fuel cell system to be controlled at the current moment is within the preset safety entropy range, the safety discreteness at the next moment is calculated to achieve control at the next moment.

[0076] In an exemplary embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the computer program to implement a fuel cell system safe operation control method considering concurrent faults.

[0077] In an exemplary embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, a method for controlling safe operation of a fuel cell system considering concurrent failures is implemented.

[0078] In an exemplary embodiment, a computer program product is provided, including a computer program, which, when executed by a processor, implements a method for controlling safe operation of a fuel cell system taking concurrent failures into consideration.

[0079] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 3 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface. The processor, memory and input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a fuel cell system safe operation control method considering concurrent failures is implemented.

[0080] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0081] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0082] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0083] The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.

[0084] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0085] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A fuel cell system safe operation control method considering concurrent failures, characterized in that: The fuel cell system safe operation control method considering concurrent failures includes: Determine any moment during the operation of the fuel cell system to be controlled as the current moment; Inputting the current time into an accessory failure probability model of each accessory in the fuel cell system to be controlled to obtain the probability of accessory failure of each accessory at the current time; the accessory failure probability model is a bathtub curve, where the horizontal axis of the bathtub curve is time and the vertical axis is the probability of accessory failure; Determining, based on the probability of each accessory failure occurring at the current moment, concurrent probabilities of different types of battery failures occurring in the fuel cell system to be controlled; Obtaining fuel cell fault information of the fuel cell system to be controlled at the current moment; the fuel cell fault information includes: stack current, voltage, temperature, cathode inlet pressure, anode inlet pressure, cathode exhaust pressure, anode exhaust pressure, coolant inlet temperature and coolant outlet temperature; Determining the occasional probability of different types of battery failures and the occasional probability of no battery failure in the fuel cell system to be controlled at the current moment based on the fuel cell fault information of the fuel cell system to be controlled at the current moment and a fuel cell occasional fault diagnosis model obtained by training a back-propagation neural network; Determining, based on the concurrent probability and occasional probability of different types of battery failures occurring in the fuel cell system to be controlled at the current moment and the occasional probability of no battery failure, the comprehensive probability of different types of battery failures occurring in the fuel cell system to be controlled and the comprehensive probability of no battery failure at the current moment; Determining the safety discreteness of the fuel cell system to be controlled at the current moment based on the comprehensive probability of different types of battery failures occurring in the fuel cell system to be controlled at the current moment and the comprehensive probability of no battery failure; The operation of the fuel cell system to be controlled is controlled by utilizing the safety discreteness of the fuel cell system to be controlled at the current moment.

2. The fuel cell system safe operation control method considering concurrent failures according to claim 1, characterized in that: Accessory failure probability model for any accessory, including: ； ； ； ； in, is the probability of accessory failure occurring at time t; is the probability of early failure of the accessory at time t; is the probability of failure of the accessory at the time t; is the probability of accidental failure of the accessory at time t; and are all shape parameters; is the size parameter of the attachment; Long short-term memory network; is the probability of accessory failure at time tn; is the probability of accessory failure at time tn-1; is the probability of accessory failure at time t-1.

3. The fuel cell system safe operation control method considering concurrent failures according to claim 1, characterized in that: Based on the fuel cell fault information of the fuel cell system to be controlled at the current moment and the fuel cell occasional fault diagnosis model, determining the occasional probability of different types of battery faults occurring in the fuel cell system to be controlled at the current moment and the occasional probability of no battery fault, including: Performing Gaussian filtering on the fuel cell fault information of the fuel cell system to be controlled at the current moment to obtain the Gaussian filtered fuel cell fault information of the fuel cell system to be controlled at the current moment; The fuel cell fault information after Gaussian filtering at the current moment of the fuel cell system to be controlled is input into the fuel cell occasional fault diagnosis model to obtain the occasional probability of different types of battery faults and the occasional probability of no battery fault in the fuel cell system to be controlled at the current moment.

4. The fuel cell system safe operation control method considering concurrent failures according to claim 3, characterized in that: The process of determining the fuel cell occasional fault diagnosis model includes: Obtaining fuel cell fault information of multiple sample fuel cell systems at various times, and the occasional probability of different types of cell faults occurring at corresponding times and the occasional probability of no cell faults; Performing Gaussian filtering on the fuel cell fault information of each sample fuel cell system at each moment to obtain the fuel cell fault information after Gaussian filtering of each sample fuel cell system at each moment; Initialize the back-propagation neural network; The fuel cell occasional fault diagnosis model is obtained by training the back propagation neural network using the fuel cell fault information of each sample fuel cell system at each moment after Gaussian filtering as input and the occasional probability of different types of battery faults and the occasional probability of no battery fault occurring at the corresponding moment of the sample fuel cell system as output.

5. The fuel cell system safe operation control method considering concurrent failures according to claim 1, characterized in that: Based on the concurrent probability and occasional probability of different types of battery failures occurring in the fuel cell system to be controlled at the current moment and the occasional probability of no battery failure, determining the comprehensive probability of different types of battery failures occurring in the fuel cell system to be controlled at the current moment and the comprehensive probability of no battery failure, including: Calculating the comprehensive probability of different types of battery failures occurring in the fuel cell system to be controlled at the current moment using the first comprehensive fault calculation formula based on the concurrent probability and occasional probability of different types of battery failures occurring in the fuel cell system to be controlled at the current moment and the occasional probability of no battery failure; The second comprehensive fault calculation formula is used to calculate the comprehensive probability that the fuel cell system to be controlled has no battery faults at the current moment, based on the concurrent probability and occasional probability of different types of battery faults occurring in the fuel cell system to be controlled at the current moment and the occasional probability of no battery faults.

6. The fuel cell system safe operation control method considering concurrent failures according to claim 5, characterized in that: The first comprehensive fault calculation formula includes: ； in, is the comprehensive probability of the jth type of battery failure occurring in the fuel cell system at time t; is the number of accessories in the fuel cell system; is the concurrent probability of battery failure caused by the i-th accessory at time t; is the probability that the jth type of battery failure is caused by the i-th accessory failure; is the accidental probability of the jth type of battery failure occurring in the fuel cell system at time t; The number of types of battery failure; is the accidental probability that there is no battery failure in the fuel cell system at time t.

7. The fuel cell system safe operation control method considering concurrent failures according to claim 6, characterized in that: The second comprehensive fault calculation formula includes: ； in, is the comprehensive probability that the fuel cell system has no battery failure at time t.

8. The fuel cell system safe operation control method considering concurrent failures according to claim 7, characterized in that: Based on the comprehensive probability of different types of battery failures occurring in the fuel cell system to be controlled at the current moment and the comprehensive probability of no battery failure, the safety discreteness of the fuel cell system to be controlled at the current moment is determined, including: The safety dispersion calculation formula is used to calculate the safety dispersion of the fuel cell system to be controlled at the current moment based on the comprehensive probability of different types of battery failures occurring in the fuel cell system to be controlled at the current moment and the comprehensive probability of no battery failure. The safety dispersion calculation formula includes: ； ； ； in, is the safety discreteness of the fuel cell system at time t; is a natural constant; is the first-level safety evaluation value of the fuel cell system at time t; is the second-level safety evaluation value of the fuel cell system at time t.

9. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for controlling safe operation of a fuel cell system taking concurrent failures into consideration as described in any one of claims 1 to 8.

10. A 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 controlling safe operation of a fuel cell system taking concurrent failures into consideration as described in any one of claims 1 to 8 is implemented.

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