Method, device and equipment for improving reliability of energy storage system

Abstract

A method, device and equipment for improving reliability of an energy storage system relate to the technical field of reliability of the energy storage system, and the method for improving the reliability of the energy storage system comprises the following steps: carrying out fault mode and influence analysis on the energy storage system and constructing a fault tree to obtain a failure mode of the energy storage system; the occurrence probability of each failure mode is obtained, and then the probability importance degree of each failure mode is obtained and sorted; obtaining the security importance of each failure mode, and sorting the security importance; and performing final sorting according to the sorting of the probability importance and the security importance, and outputting a to-be-promoted target failure mode. According to the method, the probability importance degree and the safety importance degree of each failure mode are combined, and the hazard factors of the failure modes are considered in reliability analysis work, so that the target failure mode of which the reliability should be preferentially improved is effectively identified, and subsequent reliability improvement strategy research is facilitated.

Description

Technical Field

[0001] The present application relates to the technical field of energy storage system reliability, and specifically to a method, device and equipment for improving the reliability of an energy storage system. Background Art

[0002] At present, electrochemical energy storage equipment, as an important energy storage and regulation facility, can not only effectively balance the load of the power grid and improve the utilization rate of renewable energy, but also play an irreplaceable role in ensuring the stability and safety of the power system. Among the various components of electrochemical energy storage equipment, the energy storage system is the main part, and its performance is directly related to the operating efficiency and power supply stability of the entire equipment. Therefore, it is very important to conduct reliability analysis and formulate corresponding reliability improvement strategies.

[0003] In the related technology, the fault tree analysis method is often used for system reliability analysis. Fault tree is a deductive analysis method from failure mode to failure cause, which is often used in reliability analysis and fault diagnosis to indicate which component failures of the system, or external events, or their combination will cause a specific failure mode of the system. Fault tree can help identify possible failure modes and causes, find weak links in reliability and safety, and then guide fault diagnosis, improve usage and maintenance plans, etc., to improve product reliability and safety. The fault tree analysis process includes qualitative analysis and quantitative analysis, and qualitative analysis is required as a prerequisite for quantitative analysis. Qualitative analysis is mainly the process of building a fault tree, and all minimum cut sets of the fault tree are obtained by the upward method or downward method. Quantitative analysis is to obtain some important indicators of the top events of the fault tree under the condition that each bottom event is independent of each other and its probability of occurrence is known.

[0004] However, to conduct quantitative analysis based on the results of fault tree analysis, it is necessary to first obtain the probability of occurrence of all basic events. This process is labor-intensive. In addition, it is difficult to obtain this data based on the actual operation data of the product, and the data accuracy is low. Summary of the invention

[0005] The present application provides a method, device and equipment for improving the reliability of an energy storage system, which can solve the technical problem in the prior art that the reliability analysis accuracy is low, thereby resulting in poor reliability improvement effect.

[0006] In a first aspect, the present application provides a method for improving the reliability of an energy storage system, the method comprising:

[0007] Performing a failure mode and effect analysis on the energy storage system and constructing a fault tree to obtain the failure mode of the energy storage system;

[0008] Obtain the occurrence probability of each failure mode, and then obtain the probability importance of each failure mode and sort them;

[0009] Obtain the safety importance of each failure mode and rank them;

[0010] According to the above ranking of probability importance and safety importance, a final ranking is performed, and the target failure mode to be improved is output.

[0011] In combination with the first aspect, in one implementation, the above-mentioned performing a fault mode and impact analysis on the energy storage system and constructing a fault tree to obtain the failure mode of the above-mentioned energy storage system specifically includes:

[0012] Decomposing the energy storage system into multiple failure modules according to functional requirements;

[0013] The failure mode and impact analysis of each failure module is performed separately, and a fault tree is constructed with the above energy storage system failure as the top event to obtain each failure mode and its corresponding failure cause, as well as the occurrence, severity and detection degree of each failure cause.

[0014] In combination with the first aspect, in one implementation, after obtaining the occurrence, severity and detection of each failure cause, the method further includes:

[0015] According to the occurrence degree of any failure cause, the occurrence probability of the failure cause is obtained.

[0016] In combination with the first aspect, in one implementation, the occurrence probability of each failure mode is obtained, and then the probability importance of each failure mode is obtained and ranked, specifically including:

[0017] According to the occurrence probability of each failure cause corresponding to each failure mode, the occurrence probability of each failure mode is obtained respectively;

[0018] The probability of occurrence of each failure mode is used to obtain the partial derivative of the probability of occurrence of each failure mode, and the probability importance of each failure mode is obtained;

[0019] Sort the probability importance of each failure mode from large to small.

[0020] In combination with the first aspect, in one implementation, the probability importance of the i-th failure mode is:

[0021]

[0022] Among them, P s is the probability of occurrence of the top event, P i is the probability of occurrence of the ith failure mode, P a is the occurrence probability of the ath failure mode, and m is the number of failure modes.

[0023] In combination with the first aspect, in one implementation, before obtaining the occurrence probability of the failure cause, the method further includes:

[0024] The highest occurrence score of the failure mode and effects analysis is taken as the highest score;

[0025] According to the preset occurrence score-occurrence probability reference range table, the occurrence probabilities corresponding to the lowest score to the highest score are obtained respectively; among which,

[0026] When the reference range of occurrence probability corresponds to a score, the probability of occurrence of the score is the maximum value of the corresponding reference range;

[0027] When the reference range of occurrence probability corresponds to multiple scores, a logarithmic equidistant search is performed on the reference range, and each searched breakpoint is used as the occurrence probability corresponding to the multiple scores.

[0028] In combination with the first aspect, in one implementation, obtaining the safety importance of each failure mode and ranking them specifically includes:

[0029] According to the severity and detection of each failure cause corresponding to any failure mode, the safety importance of the failure mode is obtained;

[0030] Sort the safety importance of each failure mode from large to small.

[0031] In combination with the first aspect, in one implementation, the above-mentioned final sorting and outputting of the target failure mode to be improved specifically include:

[0032] Obtain the sum of the probability importance ranking number and the safety importance ranking number of each failure mode;

[0033] Each ranking is sorted from large to small to obtain the final ranking, and the first N failure modes are used as the target failure modes to be improved.

[0034] In a second aspect, the present application provides a device for improving the reliability of an energy storage system, the device comprising:

[0035] An analysis module, which is used to perform a failure mode and impact analysis on the energy storage system to obtain a failure mode of the energy storage system;

[0036] A first acquisition module is used to acquire the occurrence probability of each failure mode, and then acquire the probability importance of each failure mode and sort them;

[0037] The second acquisition module is used to obtain the safety importance of each failure mode and sort them;

[0038] The output module is used to perform final sorting according to the above-mentioned probability importance and safety importance sorting, and output the target failure mode to be improved.

[0039] In a third aspect, the present application provides a device for improving the reliability of an energy storage system, wherein the device for improving the reliability of an energy storage system comprises a processor, a memory, and an energy storage system reliability improvement program stored in the memory and executable by the processor, wherein when the energy storage system reliability improvement program is executed by the processor, the steps of the energy storage system reliability improvement method are implemented.

[0040] The beneficial effects of the technical solution provided by this application include:

[0041] By performing a failure mode and impact analysis on the energy storage system and constructing a fault tree, the failure mode of the energy storage system is obtained; then, the occurrence probability of each failure mode is obtained, and then the probability importance of each failure mode is obtained and ranked, and the safety importance of each failure mode is obtained and ranked, and finally, according to the ranking of the above probability importance and safety importance, a final ranking is performed, and the target failure mode to be improved is output as a failure mode that requires special attention and preventive control; it is achieved by combining the probability importance and safety importance of each failure mode, taking the hazard factors of the failure mode into consideration in the reliability analysis work, and then effectively identifying the target failure mode whose reliability should be improved first, so as to facilitate the subsequent research on reliability improvement strategies, and solve the technical problem of low reliability analysis accuracy in related technologies, which leads to poor reliability improvement effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is a flow chart of an embodiment of a method for improving the reliability of an energy storage system of the present application;

[0043] Figure 2 A fault tree diagram of an embodiment of the present application;

[0044] Figure 3 This is a schematic diagram of the functional modules of an embodiment of a device for improving the reliability of an energy storage system of the present application. DETAILED DESCRIPTION

[0045] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0046] In a first aspect, an embodiment of the present application provides a method for improving the reliability of an energy storage system.

[0047] In one embodiment, referring to Figure 1 , Figure 1This is a flow chart of the first embodiment of the method for improving the reliability of the energy storage system of the present application. The above-mentioned method for improving the reliability of the energy storage system includes:

[0048] S1. Perform a failure mode and effect analysis (FMEA) on the energy storage system and construct a fault tree to obtain the failure mode of the energy storage system;

[0049] S2. Obtain the occurrence probability of each failure mode, and then obtain the probability importance of each failure mode and sort them;

[0050] S3. Obtain the safety importance of each failure mode and rank them;

[0051] S4. Perform a final sorting based on the above probability importance and safety importance, and output the target failure mode to be improved.

[0052] The order of the above steps S2 and S3 is adjustable.

[0053] In this embodiment,

[0054] By performing a failure mode and impact analysis on the energy storage system and constructing a fault tree, the failure mode of the energy storage system is obtained; then, the occurrence probability of each failure mode is obtained, and then the probability importance of each failure mode is obtained and ranked, and the safety importance of each failure mode is obtained and ranked, and finally, according to the ranking of the above probability importance and safety importance, a final ranking is performed, and the target failure mode to be improved is output as a failure mode that requires special attention and preventive control; it is achieved by combining the probability importance and safety importance of each failure mode, taking the hazard factors of the failure mode into consideration in the reliability analysis work, and then effectively identifying the target failure mode whose reliability should be improved first, so as to facilitate the subsequent research on reliability improvement strategies, and solve the technical problem of low reliability analysis accuracy in related technologies, which leads to poor reliability improvement effect.

[0055] Furthermore, in one embodiment, in the above step S1, the failure mode and impact analysis of the energy storage system is performed and a fault tree is constructed to obtain the failure mode of the energy storage system, which specifically includes:

[0056] First, the above energy storage system is decomposed into multiple failure modules according to functional requirements;

[0057] Then, the failure mode and impact analysis of each failure module is performed respectively, and a fault tree is constructed with the above energy storage system failure as the top event to obtain each failure mode and its corresponding failure cause, as well as the occurrence, severity and detection degree of each failure cause.

[0058] In this embodiment, a fault tree of the energy storage system is constructed based on the FMEA results, and FMEA is combined with the fault tree to obtain each failure mode and its corresponding failure cause, and then the probability importance and safety importance index of each failure mode can be obtained.

[0059] Furthermore, in one embodiment, after obtaining the occurrence degree, severity and detection degree of each failure cause, the following steps are also included:

[0060] According to the occurrence degree of any failure cause, the occurrence probability of the failure cause is obtained.

[0061] In this embodiment, according to the occurrence degree of any failure cause, the corresponding occurrence probability can be obtained by looking up a table, and then the occurrence probability of each failure cause can be obtained.

[0062] Furthermore, in one embodiment, in the above step S2, the occurrence probability of each failure mode is obtained, and then the probability importance of each failure mode is obtained and sorted, which specifically includes:

[0063] First, according to the occurrence probability of each failure cause corresponding to each failure mode, the occurrence probability of each failure mode is obtained respectively;

[0064] Then, the probability of occurrence of each failure mode is used to obtain the partial derivative of the probability of occurrence of each failure mode, and the probability importance of each failure mode is obtained;

[0065] Finally, the probability importance of each failure mode is sorted from large to small.

[0066] In other embodiments, the above probability importance may also be sorted from small to large.

[0067] Furthermore, in this embodiment, the probability importance of the i-th failure mode is:

[0068]

[0069] Among them, P s is the probability of occurrence of the top event, P i is the probability of occurrence of the ith failure mode, P a is the occurrence probability of the ath failure mode, and m is the number of failure modes.

[0070] In this embodiment, by taking the energy storage system failure as the top event and each failure mode as the bottom event, and the bottom events are in a series relationship, the above probability importance formula can be converted to obtain the probability importance index of each failure mode.

[0071] Furthermore, in one embodiment, before obtaining the occurrence probability of the failure cause, the method further includes:

[0072] First, the highest occurrence score of the failure mode and effects analysis is taken as the highest score.

[0073] Then, according to the preset occurrence score-occurrence probability reference range table, the occurrence probabilities corresponding to the lowest score to the highest score are obtained respectively.

[0074] In this embodiment, the lowest score is an occurrence score of 1.

[0075] Preferably, obtaining the occurrence probabilities corresponding to the lowest score to the highest score specifically includes:

[0076] When the reference range of occurrence probability corresponds to a score, the probability of occurrence of the score is the maximum value of the corresponding reference range;

[0077] When the reference range of occurrence probability corresponds to multiple scores, a logarithmic equidistant search is performed on the reference range, and each searched breakpoint is used as the occurrence probability corresponding to the multiple scores.

[0078] When performing a logarithmic equidistant search for a certain reference range, the logarithmic interval is divided into the corresponding number of scores plus 1 interval.

[0079] Optionally, when a reference range corresponds to 2 scores, the logarithmic interval is divided into 3 intervals; when a reference range corresponds to 3 scores, the logarithmic interval is divided into 4 intervals, and so on.

[0080] Furthermore, in one embodiment, in the above step S3, the safety importance of each failure mode is obtained and ranked, specifically including:

[0081] First, the safety importance of any failure mode is obtained according to the severity and detection of each failure cause corresponding to the failure mode;

[0082] Then, the safety importance of each failure mode is ranked from large to small.

[0083] In this embodiment, considering the potential harm of the failure mode to the system, the harm degree needs to be used as the safety importance to characterize the degree of harm of the failure mode to the system.

[0084] In this embodiment, when a failure mode has only one failure cause, the product of the severity of the failure cause and the detection score is used as the safety importance of the failure mode. When a failure mode has multiple failure causes, the product of the severity of each failure cause and the detection score is obtained respectively, and the sum of the products is used as the safety importance of the failure mode.

[0085] In other embodiments, when the probability importance is ranked from small to large, the safety importance of each failure mode is also ranked from small to large.

[0086] Furthermore, in one embodiment, in the above step S4, a final sorting is performed and the target failure mode to be improved is output, which specifically includes:

[0087] First, the ranking sum of the probability importance ranking number and the safety importance ranking number of each failure mode is obtained.

[0088] Then, each ranking and is sorted from large to small to obtain a final ranking, and the first N failure modes are used as the target failure modes to be promoted.

[0089] In other embodiments, when the probability importance and safety importance are ranked from small to large, the rankings and are also ranked from small to large, and the last N failure modes ranked are used as target failure modes to be promoted.

[0090] Taking the electrochemical energy storage system as an example, the above energy storage system reliability improvement method specifically includes:

[0091] Step A1: Decompose the electrochemical energy storage system into six failure modules according to functional requirements, namely, power storage and output module failure, battery management module failure, high-voltage series module failure, thermal management module failure, fire safety module failure and structural support module failure. Then, perform FMEA on the six failure modules, score the severity, occurrence and detection of the failure causes of each failure mode, and take the electrochemical energy storage system failure as the top event of the fault tree. Based on the results of FMEA, perform qualitative fault tree analysis on the top event. The constructed fault tree is as follows: Figure 2 shown.

[0092] Step A2: Calculate the probability importance of each basic event, i.e., failure mode, according to its probability of occurrence, and rank them;

[0093] Since modules, functions and failure modes are all connected in series, that is, failure of any mode will cause system failure, it is impossible to point out from the qualitative analysis results which failure modes are more likely to occur and cause greater harm to the system. Therefore, quantitative analysis of the fault tree is also required.

[0094] In this embodiment, according to the scoring criteria of the fault probability level, the reference range of the occurrence probability corresponding to the occurrence degree scoring level is shown in Table 1 below.

[0095] Table 1 Reference range of occurrence probability corresponding to the occurrence score level

[0096]

[0097]

[0098] In this embodiment, the probability importance defines the degree to which the change in the probability of occurrence of the i-th bottom event causes the change in the probability of occurrence of the top event, and its mathematical formula is expressed as:

[0099]

[0100] Where, Δg i (t) is the probability importance of the ith failure mode, P s is the probability of occurrence of the top event, P i is the occurrence probability of the ith failure mode.

[0101] In order to calculate the probability importance, it is necessary to first score each occurrence and determine a fixed value within its reference range. Therefore, when the occurrence score is 1, the probability of occurrence is 10. -6 ; For other scores, logarithmic division is required within the corresponding reference range to determine the probability of occurrence corresponding to each score.

[0102] Taking scores 2 and 3 as an example, since the reference range of the probability of occurrence corresponding to scores 2 and 3 is 10 -6 <P≤10 -4 , the left and right ends of the reference range are logarithmized to -6 and -4 respectively. In addition, there are two levels in the reference range. Therefore, the logarithmized interval is divided into three equal parts, and two breakpoints are obtained in the interval, which are -5.33 and -4.67 respectively. That is, the scores 2 and 3 correspond to a probability of 10 respectively. -5.33 , 10 -4.67 , so that the probability corresponding to the occurrence score can be reasonably arranged within the reference range and avoid taking values ​​at both ends of the range.

[0103] In this embodiment, since the occurrence scores in FMEA are not higher than 5, it is only necessary to obtain the specific occurrence probability values ​​corresponding to the occurrence levels 1 to 5, as shown in Table 2 below.

[0104] Table 2. Occurrence probability corresponding to occurrence score

[0105]

[0106]

[0107] Since some failure modes have multiple failure causes, the occurrence probability of the failure mode can be calculated based on the occurrence probability corresponding to the failure cause. When a failure mode corresponds to k failure causes, the occurrence probabilities corresponding to each failure cause are P1, P1, ..., P k Since the failure causes are in series, the occurrence probability P of the failure mode can be obtained by formula (2):

[0108]

[0109] Based on FMEA and fault tree analysis, the occurrence probability of each failure mode of the electrochemical energy storage system is shown in Table 3 below.

[0110] Table 3. Occurrence probability of each failure mode of electrochemical energy storage system

[0111]

[0112] Since the bottom events, i.e., failure modes, are in series relationship, equation (1) can be further transformed into equation (3):

[0113]

[0114] The probability importance of each failure mode is calculated by formula (3) and sorted from large to small according to the probability importance, as shown in Table 4 below.

[0115] Table 4. Probability importance of each failure mode of electrochemical energy storage system

[0116]

[0117] Step A3: Obtain the safety importance score of each failure mode and sort them:

[0118] In addition to analyzing the probability of occurrence of the failure mode and calculating the probability importance, the potential harm of the failure mode to the system must also be considered. Therefore, the product of the severity and detection scores (defined as the hazard degree) can be used to characterize the degree of harm of the failure mode to the system, that is, the safety importance. For some failure modes with multiple failure causes, the product of the severity and detection scores corresponding to each failure cause is summed. The safety importance of each failure mode of the electrochemical energy storage system is arranged in order from large to small, as shown in Table 5.

[0119] Table 5. Safety importance of each failure mode of electrochemical energy storage system

[0120]

[0121]

[0122] Step A4: Combine the probability importance and safety importance of each failure mode to make a final ranking and carry out reliability improvement work:

[0123] In order to comprehensively consider the probability of occurrence of the failure mode and the potential harm to the system, the probability importance ranking of each failure mode and the sum of the safety importance ranking are finally ranked (in ascending order), as shown in Table 6. The top five failure modes in the final ranking should be paid special attention to.

[0124] Table 6. Final ranking of failure modes of electrochemical energy storage modules

[0125]

[0126] It can be seen from Table 6 that the final ranking of the failure of the thermal management module to achieve the thermal management effect, the low discharge energy of the energy storage module, the weak structural strength of the energy storage module, the abnormal acquisition of the battery cell voltage and temperature, and the too weak strength of the structural support module are in the top 5, indicating that the above failure modes should be focused on and corresponding reliability improvement measures should be proposed, as listed in Table 7.

[0127] Table 7. Key failure modes of electrochemical energy storage systems and reliability improvement measures

[0128]

[0129] The reliability improvement method of this embodiment decomposes the energy storage system into several modules according to functional requirements, then performs FMEA on the system, and builds a fault tree of the system based on the FMEA results; and after the fault tree model is established, importance analysis is performed, and probability importance and safety importance are used as analysis indicators of importance. By quantifying the contribution of each bottom event to the top event, it is determined which failure modes have the greatest impact on system reliability. Based on the results of the importance analysis, the failure modes whose reliability should be improved first can be identified, and then research on reliability improvement strategies can be carried out, which solves the problem that the probability data of the bottom events of the fault tree are difficult to obtain and have low accuracy.

[0130] In a second aspect, an embodiment of the present application also provides a device for improving the reliability of an energy storage system.

[0131] In one embodiment, referring to Figure 3 , Figure 3 This is a functional module diagram of an embodiment of a device for improving the reliability of an energy storage system of the present application. The device for improving the reliability of an energy storage system comprises an analysis module, a first acquisition module, a second acquisition module and an output module.

[0132] The above analysis module is used to perform fault mode and impact analysis on the energy storage system to obtain the failure mode of the above energy storage system.

[0133] The first acquisition module is used to acquire the occurrence probability of each failure mode, and then acquire the probability importance of each failure mode and sort them.

[0134] The second acquisition module is used to acquire the safety importance of each failure mode and sort them.

[0135] The output module is used to perform final sorting according to the above-mentioned probability importance and safety importance sorting, and output the target failure mode to be improved.

[0136] Furthermore, in one embodiment, the above analysis module is also used for:

[0137] Decomposing the energy storage system into multiple failure modules according to functional requirements;

[0138] The failure mode and impact analysis of each failure module is performed separately, and a fault tree is constructed with the above energy storage system failure as the top event to obtain each failure mode and its corresponding failure cause, as well as the occurrence, severity and detection degree of each failure cause.

[0139] Furthermore, in one embodiment, the above analysis module is also used for:

[0140] After the occurrence, severity and detection of each failure cause are obtained, the occurrence probability of any failure cause is obtained according to the occurrence of the failure cause.

[0141] Furthermore, in one embodiment, the first acquisition module is used to:

[0142] According to the occurrence probability of each failure cause corresponding to each failure mode, the occurrence probability of each failure mode is obtained respectively;

[0143] The probability of occurrence of each failure mode is used to obtain the partial derivative of the probability of occurrence of each failure mode, and the probability importance of each failure mode is obtained;

[0144] Sort the probability importance of each failure mode from large to small.

[0145] Furthermore, in one embodiment, the probability importance of the i-th failure mode is:

[0146]

[0147] Among them, P s is the probability of occurrence of the top event, P i is the probability of occurrence of the ith failure mode, P a is the occurrence probability of the ath failure mode, and m is the number of failure modes.

[0148] Furthermore, in one embodiment, the energy storage system reliability improvement device further includes a division module, and the division module is used to:

[0149] The highest occurrence score of the failure mode and effects analysis is taken as the highest score;

[0150] According to the preset occurrence score level-occurrence probability reference range table, the occurrence probabilities corresponding to the lowest score to the highest score are obtained respectively.

[0151] Furthermore, in one embodiment, the above-mentioned division module is also used for:

[0152] When the reference range of occurrence probability corresponds to a score, the probability of occurrence of the score is the maximum value of the corresponding reference range;

[0153] When the reference range of occurrence probability corresponds to multiple scores, a logarithmic equidistant search is performed on the reference range, and each searched breakpoint is used as the occurrence probability corresponding to the multiple scores.

[0154] Furthermore, in one embodiment, the second acquisition module is used to:

[0155] According to the severity and detection of each failure cause corresponding to any failure mode, the safety importance of the failure mode is obtained;

[0156] Sort the safety importance of each failure mode from large to small.

[0157] Furthermore, in one embodiment, the output module is used to:

[0158] Obtain the sum of the probability importance ranking number and the safety importance ranking number of each failure mode;

[0159] Each ranking is sorted from large to small to obtain the final ranking, and the first N failure modes are used as the target failure modes to be improved.

[0160] The device of this embodiment obtains the probability of occurrence by combining the scores of the occurrence of each failure mode in FEMA, and further obtains the probability importance index; the safety importance is obtained by combining the scores of the criticality of each failure mode in FEMA, and the critical factors of the failure mode are taken into account in the reliability analysis work, so that the safety of the system can be guaranteed.

[0161] Among them, the functional implementation of each module in the above-mentioned energy storage system reliability improvement device corresponds to the various steps in the above-mentioned energy storage system reliability improvement method embodiment, and its functions and implementation processes are no longer repeated here one by one.

[0162] In a third aspect, an embodiment of the present application provides a device for improving the reliability of an energy storage system. The device for improving the reliability of an energy storage system may be a personal computer (PC), a laptop computer, a server, or other device having a data processing function.

[0163] In an embodiment of the present application, a device for improving the reliability of an energy storage system may include a processor, a memory, a communication interface, and a communication bus.

[0164] The communication bus may be of any type and is used to interconnect the processor, the memory, and the communication interface.

[0165] The communication interface includes input / output (I / O) interface, physical interface and logical interface, etc., which are used to realize the interconnection of devices inside the energy storage system reliability improvement device, and the interface used to realize the interconnection between the energy storage system reliability improvement device and other devices (such as other computing devices or user devices). The physical interface can be an Ethernet interface, a fiber optic interface, an ATM interface, etc.; the user device can be a display, a keyboard, etc.

[0166] The memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical storage, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.

[0167] The processor may be a general-purpose processor, which may call the energy storage system reliability improvement program stored in the memory and execute the energy storage system reliability improvement method provided in the embodiment of the present application. For example, the general-purpose processor may be a central processing unit (CPU). The method executed when the energy storage system reliability improvement program is called may refer to the various embodiments of the energy storage system reliability improvement method of the present application, which will not be described in detail here.

[0168] It should be noted that the serial numbers of the above-mentioned embodiments of the present application are only for description and do not represent the advantages or disadvantages of the embodiments.

[0169] The terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices. The terms "first", "second" and "third" are used to distinguish different objects, etc., and do not represent a sequence, nor do they limit "first", "second" and "third" to different types.

[0170] In the description of the embodiments of the present application, "exemplary", "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary", "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary", "for example" or "for example" is intended to present related concepts in a specific way.

[0171] In the description of the embodiments of the present application, unless otherwise specified, “ / ” means or, for example, A / B can mean A or B; the “and / or” in the text is merely a description of the association relationship of associated objects, indicating that three relationships may exist, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of the present application, “multiple” refers to two or more than two.

[0172] In some processes described in the embodiments of the present application, multiple operations or steps that appear in a specific order are included, but it should be understood that these operations or steps may not be executed in the order in which they appear in the embodiments of the present application or in parallel, and the sequence number of the operation is only used to distinguish the different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed in sequence or in parallel, and these operations or steps may be combined.

[0173] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, disk, CD) as described above, and includes a number of instructions for a terminal device to execute the methods described in each embodiment of the present application.

[0174] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A method for improving the reliability of an energy storage system, characterized in that: The method comprises: Performing a failure mode and effect analysis on the energy storage system and constructing a fault tree to obtain a failure mode of the energy storage system; Obtain the occurrence probability of each failure mode, and then obtain the probability importance of each failure mode and sort them; Obtain the safety importance of each failure mode and rank them; According to the ranking of the probability importance and the safety importance, a final ranking is performed, and the target failure mode to be improved is output.

2. The method for improving the reliability of an energy storage system according to claim 1, characterized in that: The performing of a failure mode and impact analysis on the energy storage system and constructing a fault tree to obtain the failure mode of the energy storage system specifically includes: Decomposing the energy storage system into multiple failure modules according to functional requirements; The failure mode and impact analysis is performed on each failure module respectively, and a fault tree is constructed with the energy storage system failure as the top event to obtain each failure mode and its corresponding failure cause, as well as the occurrence, severity and detection degree of each failure cause.

3. The method for improving the reliability of an energy storage system according to claim 2, characterized in that: After obtaining the occurrence, severity and detection of each failure cause, it also includes: According to the occurrence degree of any failure cause, the occurrence probability of the failure cause is obtained.

4. The method for improving the reliability of an energy storage system according to claim 3, characterized in that: Obtain the occurrence probability of each failure mode, and then obtain the probability importance of each failure mode and sort them, including: According to the occurrence probability of each failure cause corresponding to each failure mode, the occurrence probability of each failure mode is obtained respectively; The probability of occurrence of each failure mode is used to obtain the partial derivative of the probability of occurrence of each failure mode, and the probability importance of each failure mode is obtained; Sort the probability importance of each failure mode from large to small.

5. The method for improving the reliability of an energy storage system according to claim 4, characterized in that: The probability importance of the i-th failure mode is: Among them, P s is the probability of occurrence of the top event, P i is the probability of occurrence of the ith failure mode, P a is the occurrence probability of the ath failure mode, and m is the number of failure modes.

6. The method for improving the reliability of an energy storage system according to claim 3, characterized in that: Before obtaining the probability of occurrence of the failure cause, the following steps are also included: The highest occurrence score of the failure mode and effects analysis is taken as the highest score; According to the preset occurrence score-occurrence probability reference range table, the occurrence probabilities corresponding to the lowest score to the highest score are obtained respectively; among which, When the reference range of occurrence probability corresponds to a score, the probability of occurrence of the score is the maximum value of the corresponding reference range; When the reference range of occurrence probability corresponds to multiple scores, a logarithmic equidistant search is performed on the reference range, and each searched breakpoint is used as the occurrence probability corresponding to the multiple scores.

7. The method for improving the reliability of an energy storage system according to claim 2, characterized in that: Obtain the safety importance of each failure mode and rank them, including: According to the severity and detection of each failure cause corresponding to any failure mode, the safety importance of the failure mode is obtained; Sort the safety importance of each failure mode from large to small.

8. The method for improving the reliability of an energy storage system according to claim 1, characterized in that: The final sorting and output of the target failure mode to be improved specifically include: Obtain the sum of the probability importance ranking number and the safety importance ranking number of each failure mode; Each ranking is sorted from large to small to obtain the final ranking, and the first N failure modes are used as the target failure modes to be improved.

9. A device for improving the reliability of an energy storage system, characterized in that: The device comprises: An analysis module, which is used to perform a failure mode and impact analysis on the energy storage system to obtain a failure mode of the energy storage system; A first acquisition module is used to acquire the occurrence probability of each failure mode, and then acquire the probability importance of each failure mode and sort them; The second acquisition module is used to obtain the safety importance of each failure mode and sort them; The output module is used to perform a final sorting according to the sorting of the probability importance and the safety importance, and output the target failure mode to be improved.

10. A device for improving the reliability of an energy storage system, characterized in that: The energy storage system reliability improvement device includes a processor, a memory, and an energy storage system reliability improvement program stored in the memory and executable by the processor, wherein when the energy storage system reliability improvement program is executed by the processor, the steps of the energy storage system reliability improvement method as described in any one of claims 1 to 8 are implemented.

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