CN116400231B

CN116400231B - Battery multi-fault detection method and device of energy storage system and electronic equipment

Info

Publication number: CN116400231B
Application number: CN202310681299.0A
Authority: CN
Inventors: 赵珈卉; 朱勇; 张斌; 刘明义; 王建星; 刘承皓; 孙悦; 郝晓伟; 杨超然; 平小凡; 成前; 王娅宁; 周敬伦; 段召容; 孙周婷; 雷浩东; 李�昊; 杨名昊
Original assignee: Huaneng Clean Energy Research Institute; Huaneng Lancang River Hydropower Co Ltd
Current assignee: Huaneng Clean Energy Research Institute; Huaneng Lancang River Hydropower Co Ltd
Priority date: 2023-06-09
Filing date: 2023-06-09
Publication date: 2023-10-03
Anticipated expiration: 2043-06-09
Also published as: CN116400231A

Abstract

The disclosure provides a battery multi-fault detection method and device of an energy storage system and electronic equipment, wherein the method comprises the following steps: and carrying out battery overcharge fault detection and battery overtemperature fault detection on each battery cell in the battery pack according to the real-time voltage data and the real-time temperature data, carrying out operation voltage fault detection on each battery cell in the battery pack according to the voltage data to be detected and the median voltage data, carrying out operation temperature fault detection on each battery cell in the battery pack according to the temperature data to be detected and the median temperature data, and carrying out internal short circuit fault detection on each battery cell in the battery pack according to the voltage data to be detected and the resistance data information of each battery cell in the battery pack. According to the method and the device, various different calculation processes can be carried out on temperature data and voltage data, various different faults of the battery pack of the energy storage system are detected, and multi-fault detection is achieved with smaller data calculation amount.

Description

Battery multi-fault detection method and device of energy storage system and electronic equipment

Technical Field

The disclosure relates to the technical field of battery fault detection, and in particular relates to a battery multi-fault detection method and device of an energy storage system, electronic equipment and a storage medium.

Background

Currently, the structure of a battery system of a large-scale energy storage power station mainly consists of a plurality of battery monomers connected in series and in parallel.

In the related art, a conventional battery fault detection method is generally adopted, and features of measurement parameters of a battery are extracted and analyzed to directly detect whether faults occur or not, or separate fault detection modeling is performed for different faults of the battery.

In this way, when the abnormal characteristics of the battery are not obvious, the traditional fault diagnosis method is difficult to detect early faults, and as the complexity of the battery system of the large-scale energy storage system increases, a great deal of time and effort are required for performing individual fault detection modeling on different batteries and various faults possibly existing in the batteries, and it is difficult to establish an accurate fault detection mathematical model, so that a battery fault detection modeling scheme cannot be applied online, and the fault detection effect is affected.

Disclosure of Invention

The present disclosure aims to solve, at least to some extent, one of the technical problems in the related art.

To this end, the present disclosure aims to propose a battery multi-fault detection method, an apparatus, an electronic device, a storage medium and a computer program product of an energy storage system.

An embodiment of a first aspect of the present disclosure provides a method for detecting multiple faults of a battery of an energy storage system, including: respectively acquiring real-time voltage data and real-time temperature data of each battery cell in a battery pack of the energy storage system; according to the real-time voltage data and the real-time temperature data, performing battery overcharge fault detection processing and battery overtemperature fault detection processing on each battery monomer in the battery pack; sampling real-time voltage data and real-time temperature data based on a moving window with a preset window size to obtain to-be-processed voltage data and to-be-processed temperature data; performing inconsistency detection processing on the voltage data to be processed and the temperature data to be processed to remove abnormal voltage data in the voltage data to be processed to obtain voltage data to be detected, and removing abnormal temperature data in the temperature data to be processed to obtain temperature data to be detected; performing median voltage sampling treatment on the voltage data to be detected to obtain median voltage data corresponding to the battery pack, and performing median temperature sampling treatment on the temperature data to be detected to obtain median temperature data corresponding to the battery pack; according to the voltage data to be detected and the median voltage data, performing operation voltage fault detection processing on each battery cell in the battery pack; according to the temperature data to be detected and the median temperature data, performing operation temperature fault detection processing on each battery monomer in the battery pack; and carrying out internal short circuit fault detection processing on each battery cell in the battery pack according to the voltage data to be detected and the resistance data information of each battery cell in the battery pack.

An embodiment of a second aspect of the present disclosure provides a battery multi-fault detection device of an energy storage system, including: the acquisition module is used for respectively acquiring real-time voltage data and real-time temperature data of each battery cell in the battery pack of the energy storage system; the first detection module is used for carrying out battery overcharge fault detection processing and battery overtemperature fault detection processing on each battery monomer in the battery pack according to the real-time voltage data and the real-time temperature data; the first processing module is used for sampling and processing the real-time voltage data and the real-time temperature data based on a moving window with a preset window size to obtain the voltage data to be processed and the temperature data to be processed; the second processing module is used for carrying out inconsistency detection processing on the voltage data to be processed and the temperature data to be processed so as to remove abnormal voltage data in the voltage data to be processed to obtain voltage data to be detected, and removing abnormal temperature data in the temperature data to be processed to obtain temperature data to be detected; the third processing module is used for carrying out median voltage sampling processing on the voltage data to be detected to obtain median voltage data corresponding to the battery pack, and carrying out median temperature sampling processing on the temperature data to be detected to obtain median temperature data corresponding to the battery pack; the second detection module is used for carrying out operation voltage fault detection processing on each battery cell in the battery pack according to the voltage data to be detected and the median voltage data; the third detection module is used for carrying out operation temperature fault detection processing on each battery monomer in the battery pack according to the temperature data to be detected and the median temperature data; and the fourth detection module is used for carrying out internal short circuit fault detection processing on each battery cell in the battery pack according to the voltage data to be detected and the resistance data information of each battery cell in the battery pack.

An embodiment of a third aspect of the present disclosure provides an electronic device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor, where the processor executes the program to implement a method for detecting multiple faults of a battery of an energy storage system according to an embodiment of the first aspect of the present disclosure.

An embodiment of a fourth aspect of the present disclosure proposes a non-transitory computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements a battery multi-fault detection method of an energy storage system as proposed by an embodiment of the first aspect of the present disclosure.

Embodiments of a fifth aspect of the present disclosure propose a computer program product, which when executed by a processor, performs a method of battery multi-fault detection of an energy storage system as proposed by embodiments of the first aspect of the present disclosure.

The battery multi-fault detection method, device, electronic equipment, storage medium and computer program product of the energy storage system at least comprise the following beneficial effects: the method comprises the steps of respectively obtaining real-time voltage data and real-time temperature data of each battery cell in a battery pack of an energy storage system, carrying out battery overcharge fault detection processing and battery overtemperature fault detection processing on each battery cell in the battery pack according to the real-time voltage data and the real-time temperature data, sampling the real-time voltage data and the real-time temperature data based on a moving window with a preset window size to obtain voltage data to be processed and temperature data to be processed, carrying out inconsistency detection processing on the voltage data to be processed and the temperature data to be processed to remove abnormal voltage data in the voltage data to be processed to obtain voltage data to be detected, removing the abnormal temperature data in the temperature data to be processed to obtain temperature data to be detected, carrying out median voltage sampling processing on the voltage data to be detected to obtain median voltage data corresponding to the battery pack, performing median temperature sampling processing on temperature data to be detected to obtain median temperature data corresponding to the battery pack, performing operation voltage fault detection processing on each battery cell in the battery pack according to the voltage data to be detected and the median voltage data, performing operation temperature fault detection processing on each battery cell in the battery pack according to the temperature data to be detected and the median temperature data, performing internal short circuit fault detection processing on each battery cell in the battery pack according to the voltage data to be detected and resistance data information of each battery cell in the battery pack, performing multiple different calculation processing modes on the temperature data and the voltage data, realizing detection on multiple different faults of the battery pack of an energy storage system, realizing multiple fault detection with smaller data calculation amount, effectively improving fault detection efficiency and fault detection accuracy, early detection of various faults of the battery pack of the energy storage system is achieved.

Additional aspects and advantages of the disclosure will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the disclosure.

Drawings

The foregoing and/or additional aspects and advantages of the present disclosure will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings, in which:

FIG. 1 is a flow chart of a method for detecting multiple battery faults of an energy storage system according to an embodiment of the present disclosure;

FIG. 2 is a flow diagram of a method of multi-fault detection of a battery pack in the practice of the present disclosure;

FIG. 3 is a flow chart illustrating a method for battery multi-fault detection of an energy storage system according to another embodiment of the present disclosure;

FIG. 4 is a flow chart illustrating a method for battery multi-fault detection of an energy storage system according to another embodiment of the present disclosure;

FIG. 5 is a schematic diagram of a battery circuit in an embodiment of the present disclosure;

FIG. 6 is a schematic diagram of a battery multi-fault detection device of an energy storage system according to an embodiment of the present disclosure;

FIG. 7 is a schematic diagram of a battery multi-fault detection device of an energy storage system according to another embodiment of the present disclosure;

fig. 8 illustrates a block diagram of an exemplary electronic device suitable for use in implementing embodiments of the present disclosure.

Detailed Description

Embodiments of the present disclosure are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are exemplary only for explaining the present disclosure and are not to be construed as limiting the present disclosure. On the contrary, the embodiments of the disclosure include all alternatives, modifications, and equivalents as may be included within the spirit and scope of the appended claims.

Fig. 1 is a flow chart illustrating a method for detecting multiple battery faults of an energy storage system according to an embodiment of the present disclosure.

It should be noted that, the execution body of the battery multi-fault detection method of the energy storage system in this embodiment is a battery multi-fault detection device of the energy storage system, and the device may be implemented in a software and/or hardware manner, and the device may be configured in an electronic device, which is not limited.

As shown in fig. 1, the battery multi-fault detection method of the energy storage system includes:

s101: and respectively acquiring real-time voltage data and real-time temperature data of each battery cell in the battery pack of the energy storage system.

The battery pack is composed of a plurality of battery cells which are connected in series and in parallel, and can be used for energy storage of the energy storage system.

The real-time voltage data refers to battery voltage change data of the battery pack in the charging and discharging operation process.

The real-time temperature data refers to battery temperature change data of the battery pack in the charging and discharging operation process.

The embodiment of the disclosure can be applied to a battery system of a large-scale energy storage power station, the large-scale energy storage power station is used as an energy storage system, the structure of the battery system mainly comprises a plurality of battery cells connected in series and in parallel, when real-time voltage data and real-time temperature data of each battery cell in the battery pack of the energy storage system are respectively obtained, original power data in the battery pack operation process can be obtained from a battery management system (Battery Management System, BMS), then feature extraction processing is carried out on the original power data so as to extract battery voltage change data of each battery cell in the battery pack in the charge and discharge operation process from the original power data, the voltage change data is used as real-time voltage data, battery temperature change data of each battery cell in the battery pack in the charge and discharge operation process is extracted from the original power data, and the temperature change data is used as real-time temperature data.

In other embodiments, the data acquisition device may be further installed on the battery multi-fault detection device of the energy storage system, and the real-time voltage data and the real-time temperature data of each battery cell in the battery pack may be acquired based on the data acquisition device, or any other data acquisition method may be further adopted to acquire the real-time voltage data and the real-time temperature data of each battery cell in the battery pack of the energy storage system, which is not limited.

S102: and carrying out battery overcharge fault detection processing and battery overtemperature fault detection processing on each battery cell in the battery pack according to the real-time voltage data and the real-time temperature data.

After the real-time voltage data and the real-time temperature data of each battery cell in the battery pack of the energy storage system are respectively obtained, the embodiment of the disclosure can perform battery overcharge fault detection processing and battery overtemperature fault detection processing on each battery cell in the battery pack according to the real-time voltage data and the real-time temperature data.

In the embodiment of the disclosure, when performing battery overcharge fault detection processing and battery overtemperature fault detection processing on each battery cell in the battery pack according to the real-time voltage data and the real-time temperature data, the maximum battery charging voltage and the maximum battery working temperature can be set according to the running state of the battery pack of the energy storage system, the real-time voltage of each battery is judged according to the maximum battery charging voltage and the real-time voltage data corresponding to each battery cell, if the real-time voltage exceeds the maximum battery charging voltage, the battery cell is identified to have an overcharge fault, the fault battery cell is isolated, the real-time temperature of each battery cell is judged according to the maximum battery working temperature and the real-time temperature data corresponding to each battery cell, and if the real-time temperature exceeds the maximum battery working temperature, the battery cell is identified to have an overtemperature fault, and the fault battery cell is isolated.

In other embodiments, before performing the battery overcharge fault detection process and the battery overtemperature fault detection process on each battery cell in the battery pack according to the real-time voltage data and the real-time temperature data, the data cleaning process may be further performed on the real-time voltage data and the real-time temperature data, for example, repeated data elimination is performed on the real-time voltage data and the real-time temperature data, extreme voltage data obtained by sampling errors in the real-time voltage data is eliminated, extreme temperature data obtained by sampling errors in the real-time temperature data is eliminated, data deletion process is performed on part of data with data missing in the real-time voltage data and the real-time temperature data, or data interpolation and supplement process is performed on part of data with data missing.

S103: and sampling the real-time voltage data and the real-time temperature data based on a moving window with a preset window size to obtain the voltage data to be processed and the temperature data to be processed.

The preset window size refers to a window size of a moving window for sampling real-time voltage data and real-time temperature data.

In the embodiment of the disclosure, the window size of the moving window for data sampling processing can be set according to the precision requirement of fault detection data of the battery pack, for online fault diagnosis of the battery pack, the calculation amount of all data acquired by processing is large, the moving window can be used for sampling real-time voltage data and real-time temperature data, the size of the moving window can influence the calculation amount and the sensitivity to faults, the shorter the window size of the moving window is, the higher the sensitivity to fault perception is, the higher the detection precision is, the corresponding calculation cost is high, the calculation efficiency is low, and the size of the moving window can be determined according to the actual calculation precision requirement of running fault detection of the battery pack so as to obtain the preset window size of the moving window.

In the embodiment of the disclosure, after the real-time voltage data and the real-time temperature data of each battery cell in the battery pack of the energy storage system are respectively obtained, the real-time voltage data and the real-time temperature data can be sampled and processed based on a moving window with a preset window size, so as to obtain the voltage data to be processed and the temperature data to be processed.

In the embodiment of the disclosure, when the real-time voltage data and the real-time temperature data are sampled and processed based on the moving window with the preset window size to obtain the voltage data to be processed and the temperature data to be processed, the real-time voltage data may be sampled and processed based on the preset window size, for example, the voltage data sampled and processed in the moving window is obtained as the voltage data to be processed in a mode of sampling once every 1s in the moving window, the real-time temperature data is sampled and processed based on the moving window, and the temperature data sampled and processed in the moving window is obtained as the temperature data to be processed.

S104: performing inconsistency detection processing on the voltage data to be processed and the temperature data to be processed to remove abnormal voltage data in the voltage data to be processed to obtain voltage data to be detected, and removing abnormal temperature data in the temperature data to be processed to obtain temperature data to be detected.

The abnormal voltage data refers to non-fault voltage data which influences a voltage fault detection result due to inconsistency of battery manufacturing in the voltage data to be processed.

The voltage data to be detected is voltage data obtained by removing abnormal voltage data caused by inconsistency of battery manufacturing.

The abnormal temperature data refers to non-fault temperature data which influences a temperature fault detection result due to inconsistency of battery manufacturing in the temperature data to be processed.

The temperature data to be detected is temperature data obtained by removing abnormal temperature data caused by non-uniformity of battery manufacturing.

In the implementation of the disclosure, due to unavoidable deviation in the manufacturing process of the battery cells in the battery pack of the energy storage system, differences in materials, electrode thicknesses or connection technologies may occur in different battery cells, differences in battery internal resistance, initial capacity, open circuit voltage (Open Circuit Voltage, OCV) and self-discharge rate may occur in the battery cells, inconsistency detection processing may be performed on the voltage data to be processed and the temperature data to be processed, non-fault voltage data which may affect voltage fault detection due to manufacturing process differences of different battery cells may be detected, the detected non-fault voltage data may be used as abnormal voltage data, non-fault temperature data which may affect temperature fault detection due to manufacturing process differences of different battery cells may be detected may be used as abnormal temperature data, then the abnormal voltage data may be removed from the voltage data to be processed, the voltage data to be processed after the abnormal voltage data is removed may be used as the voltage data to be processed, the abnormal temperature data to be removed from the temperature data to be processed, and the temperature data to be processed after the abnormal temperature data is removed may be used as the temperature data to be detected.

For example, taking the processing of performing inconsistency detection on the voltage data to be processed as an example, the following steps may be adopted to determine and eliminate the possible effect of inconsistency of the battery cells on fault detection of the battery, so as to reduce false alarms of subsequent fault detection possibly caused by inconsistency of the battery cells: the method comprises the steps of forming a voltage charging matrix V by voltage data to be processed, which are obtained by sampling in a current moving window, calculating a median voltage matrix of each battery cell in the voltage charging matrix V, obtaining a maximum median voltage, a minimum median voltage and a median voltage difference between the maximum median voltage and the minimum median voltage in the median voltage matrix, setting a median voltage threshold value, determining that each battery cell in the battery pack has initial inconsistency if the maximum median voltage is larger than the median voltage threshold value, fitting voltage data in the charging voltage matrix into a plurality of voltage change curves, moving a starting point of the voltage curve where the minimum median voltage is located to a starting point of the voltage curve where the median voltage difference between the maximum median voltage and the minimum median voltage is located, and then carrying out data sampling again to obtain a new charging voltage matrix V 'after resampling, wherein the new charging voltage matrix V' is the voltage data to be detected after removing abnormal voltage data, and taking the voltage data to be processed obtained by sampling in the current moving window as the voltage data to be detected.

In other embodiments, it may be determined whether the moving window corresponding to the voltage data to be processed is the first moving window in the charging state of the battery cell, if the moving window corresponding to the voltage data to be processed is not the first moving window in the charging state of the battery cell, the new charging voltage matrix V' obtained by the processing is directly used as the voltage data to be detected, and then the subsequent fault detection processing may be performed by using the voltage data to be detected, and correspondingly, the inconsistency detection processing method may be used to perform the inconsistency detection processing on the temperature data to be processed, so as to remove the abnormal temperature data in the temperature data to be processed, and obtain the temperature data to be detected.

S105: and carrying out median voltage sampling treatment on the voltage data to be detected to obtain median voltage data corresponding to the battery pack, and carrying out median temperature sampling treatment on the temperature data to be detected to obtain median temperature data corresponding to the battery pack.

The median voltage data refers to data composed of median voltages of all battery cells in the battery pack in the voltage data to be detected.

The median temperature data refers to data composed of median temperatures of all battery cells in the battery pack in temperature data to be detected.

In the embodiment of the disclosure, when median voltage sampling processing is performed on voltage data to be detected to obtain median voltage data corresponding to a battery pack, median voltages in voltage data corresponding to each battery cell in the voltage data to be detected can be obtained, and median voltages of all battery cells are used as median voltage data corresponding to the battery pack.

In the implementation of the disclosure, when median temperature sampling processing is performed on temperature data to be detected to obtain median temperature data corresponding to a battery pack, median temperature in temperature data corresponding to each battery cell in the temperature data to be detected can be obtained, and median temperature of all battery cells is used as median temperature data corresponding to the battery pack.

S106: and carrying out operation voltage fault detection processing on each battery cell in the battery pack according to the voltage data to be detected and the median voltage data.

In the embodiment of the disclosure, the inconsistency detection processing is performed on the voltage data to be processed to remove abnormal voltage data in the voltage data to be processed, obtain the voltage data to be detected, and the median voltage sampling processing is performed on the voltage data to be detected, so that after the median voltage data corresponding to the battery pack is obtained, the operation voltage fault detection processing can be performed on each battery cell in the battery pack according to the voltage data to be detected and the median voltage data.

In the embodiment of the disclosure, when performing operation voltage fault detection processing on each battery cell in a battery pack according to voltage data to be detected and median voltage data, a maximum voltage difference between all battery cells in the voltage data to be detected can be determined, a minimum battery serial number when the maximum voltage difference occurs is recorded, a terminal voltage curve corresponding to each battery cell is generated according to the voltage data to be detected, a median voltage curve corresponding to the battery pack is generated according to the median voltage data, then a cost function is introduced, an improved hausdorff distance between the terminal voltage curve of each battery cell and the median voltage curve is calculated, the terminal voltage curve of each battery cell is compared with the median voltage curve, the deviation of the improved hausdorff distance between the terminal voltage curve of an abnormal battery cell and the median voltage curve is far higher than that of a normal battery cell, and whether the battery cell serial number of the battery cell with excessive deviation is the same as the minimum battery cell serial number or not is judged, if the battery cell has the operation voltage fault, the abnormal battery cell with the operation voltage fault can be easily identified, and the influence on the average voltage can be reduced by using the comparison of the median voltage data.

S107: and carrying out operation temperature fault detection processing on each battery cell in the battery pack according to the temperature data to be detected and the median temperature data.

According to the embodiment of the disclosure, the inconsistency detection processing is performed on the temperature data to be processed so as to remove abnormal temperature data in the temperature data to be processed, obtain the temperature data to be detected, and the median temperature sampling processing is performed on the temperature data to be detected, so that after the median temperature data corresponding to the battery pack is obtained, the operation temperature fault detection processing can be performed on each battery cell in the battery pack according to the temperature data to be detected and the median temperature data.

In the embodiment of the disclosure, when performing operation temperature fault detection processing on each battery cell in a battery pack according to temperature data to be detected and median temperature data, a maximum temperature difference between all battery cells in the temperature data to be detected can be determined according to the temperature data to be detected, a minimum battery serial number when the maximum temperature difference occurs is recorded, a battery temperature curve corresponding to each battery cell is generated according to the temperature data to be detected, a median temperature curve corresponding to the battery pack is generated according to the median temperature data, then a cost function is introduced, an improved hausdorff distance between the battery temperature curve of each battery cell and the median temperature curve is calculated, the battery temperature curve of each battery is compared with the median temperature curve according to the improved hausdorff distance, the improved hausdorff distance between the battery temperature curve of an abnormal battery cell and the median temperature curve is far higher than that of a normal battery cell, and whether the battery cell serial number of the battery cell with excessive offset is the same as the minimum battery serial number is judged, if the battery cell serial number is the same, the battery cell has operation temperature fault, thus the battery cell with the median operation temperature fault can be easily identified, the abnormal operation temperature fault can be reduced, and the abnormal temperature can be influenced by comparing the average temperature of the abnormal battery cells.

S108: and carrying out internal short circuit fault detection processing on each battery cell in the battery pack according to the voltage data to be detected and the resistance data information of each battery cell in the battery pack.

The resistance data information refers to resistance size information of various resistors and capacitors in the battery cell circuit, and the resistance data information can comprise short-term polarization resistance data, long-term polarization resistance data, short-term polarization capacitance data, long-term polarization capacitance data, battery equivalent internal resistance data and the like in the battery cell circuit.

In the embodiment Of the disclosure, when internal short circuit fault detection is performed on each battery cell in a battery pack according to voltage data to be detected and resistance data information Of each battery cell in the battery pack, short-term polarization resistance data, long-term polarization resistance data, short-term polarization capacitance data, long-term polarization capacitance data, equivalent internal resistance data Of a battery, and the like in a battery cell circuit can be obtained as resistance data information, open-circuit voltage and battery terminal voltage Of the battery cell relative to a battery State Of Charge (SOC) are obtained from the voltage data to be detected, battery current Of a circuit in which the battery cell is located is measured, and internal short circuit resistance Of the battery cell is estimated according to the resistance data information, the open-circuit voltage, the battery terminal voltage, the battery current and other circuit parameters.

For example, as shown in fig. 2, fig. 2 is a schematic flow diagram of a multi-fault detection method of a battery pack in the implementation of the disclosure, the embodiment of the disclosure proposes a three-level multi-fault diagnosis method of a battery, a first-level fault diagnosis is performed by a threshold judgment method according to real-time voltage data and real-time temperature data of the battery cells, overcharge fault detection processing and overtemperature fault detection processing of the battery cells are performed, a second-level fault diagnosis screens abnormal battery cells having operation voltage faults and operation temperature faults based on improved hausdor distances, an improved hausdorff distance between a terminal voltage curve of each battery cell and a median voltage curve formed by median terminal voltages of all battery cells at each sampling point in the battery pack is calculated, whether the battery cells have operation voltage faults or not is judged by similarity between comparison curves, and accordingly, whether the battery cells have operation temperature faults or not is judged by calculating the improved hausdor distance between the battery temperature curves, compared with the conventional hausdor distance, the improved hausdordor distance calculation method in the embodiment of the invention has the advantages that the conventional method is added in the calculation of the prior art, the problem that the fault detection is solved in a small-scale fault detection is solved, the fault detection is carried out in a small-down window, the prior art, the fault is accurately calculated, the fault detection is solved in the prior art, the fault detection has been calculated, and the fault has been detected in the error has been accurately, and the fault detection has been solved in the error has been calculated, and the fault detection has been calculated in the fault detection process, the third-level fault diagnosis adopts an internal short circuit equivalent circuit model to accurately diagnose the internal short circuit fault, and compared with a diagnosis method based on data driving for indiscriminately all batteries, the third-level fault diagnosis method provided by the embodiment of the disclosure reduces the calculated amount, improves the real-time performance of calculation, and can identify the type of the battery fault and accurately diagnose the fault compared with the traditional fault diagnosis method only based on abnormal judgment.

In this embodiment, real-time voltage data and real-time temperature data of each battery cell in a battery pack of an energy storage system are obtained respectively, battery overcharge fault detection processing and battery overtemperature fault detection processing are performed on each battery cell in the battery pack according to the real-time voltage data and the real-time temperature data, sampling processing is performed on the real-time voltage data and the real-time temperature data based on a moving window with a preset window size to obtain to-be-processed voltage data and to-be-processed temperature data, inconsistency detection processing is performed on the to-be-processed voltage data and the to-be-processed temperature data to remove abnormal voltage data in the to-be-processed voltage data, to-be-detected voltage data is obtained, abnormal temperature data in the to-be-processed temperature data is removed, median voltage sampling processing is performed on the to-be-detected voltage data to obtain median voltage data corresponding to the battery pack, performing median temperature sampling processing on temperature data to be detected to obtain median temperature data corresponding to the battery pack, performing operation voltage fault detection processing on each battery cell in the battery pack according to the voltage data to be detected and the median voltage data, performing operation temperature fault detection processing on each battery cell in the battery pack according to the temperature data to be detected and the median temperature data, performing internal short circuit fault detection processing on each battery cell in the battery pack according to the voltage data to be detected and resistance data information of each battery cell in the battery pack, performing multiple different calculation processing modes on the temperature data and the voltage data, realizing detection on multiple different faults of the battery pack of an energy storage system, realizing multiple fault detection with smaller data calculation amount, effectively improving fault detection efficiency and fault detection accuracy, early detection of various faults of the battery pack of the energy storage system is achieved.

Fig. 3 is a flow chart illustrating a method for detecting multiple battery faults of an energy storage system according to another embodiment of the present disclosure.

As shown in fig. 3, the battery multi-fault detection method of the energy storage system includes:

s301: and respectively acquiring real-time voltage data and real-time temperature data of each battery cell in the battery pack of the energy storage system.

S302: and sampling the real-time voltage data and the real-time temperature data based on a moving window with a preset window size to obtain the voltage data to be processed and the temperature data to be processed.

S303: performing inconsistency detection processing on the voltage data to be processed and the temperature data to be processed to remove abnormal voltage data in the voltage data to be processed to obtain voltage data to be detected, and removing abnormal temperature data in the temperature data to be processed to obtain temperature data to be detected.

S304: and carrying out median voltage sampling treatment on the voltage data to be detected to obtain median voltage data corresponding to the battery pack, and carrying out median temperature sampling treatment on the temperature data to be detected to obtain median temperature data corresponding to the battery pack.

The specific description of S301 to S304 may be referred to the above embodiments, and will not be repeated here.

S305: and processing the voltage data to be detected to obtain terminal voltage curves corresponding to all the battery cells in the battery pack.

In the embodiment of the disclosure, when performing operation voltage fault detection processing on each battery cell in the battery pack according to the voltage data to be detected and the median voltage data, the data to be detected may be processed first to obtain terminal voltage data corresponding to each battery cell in the battery pack, and terminal voltage curves corresponding to each battery cell are generated by fitting according to the terminal voltage data corresponding to each battery cell.

S306: and processing the median voltage data to obtain a median voltage curve corresponding to the battery pack.

In the embodiment of the disclosure, median voltage curve fitting processing can be performed on median voltage data obtained after median sampling processing, so as to obtain a median voltage curve corresponding to the battery pack.

S307: and determining the voltage Hastedor distance between the terminal voltage curve and the median voltage curve according to the cost function information of the battery cells.

The cost function information is data constraint information which can be used for representing a norm distance in the Hastethodor distance to improve the Hastethodor distance and improve the robustness of the Hastethodor distance participating in running voltage fault detection.

The voltage hausdorff distance refers to data information that can be used to indicate the degree of similarity between the terminal voltage curve and the median voltage curve of the battery cell.

In the implementation of the present disclosure, cost function information may be introduced to improve an original calculation expression of the hausdorff distance, to obtain an improved hausdorff distance calculation expression, where an initial hausdorff distance calculation mode is: two sets of points A= { a are arranged ₁ ，…，a _p} and B={b₁ ，…，b _q Then the Hastedorff distance between point set A and point set B is defined as the double sided Hastedorff distance H (A, B), expressed asWhere H (A, B) is the one-sided Hausdorff distance from point set A to point set B, H (B, A) is the one-sided Hausdorff distance from point set B to point set A, and H (A, B) represents the maximum value of the minimum distance between point set A and all points in point set B, i.e.)>And (3) withMaximum value of (2), wherein%> and />Is the euclidean distance between the two point sets.

In the embodiment of the disclosure, the cost function information can be utilized to improve the initial Hausdorff distance calculation expression, and the cost function is utilized when the cost function information is utilized to improve the initial Hausdorff distance calculation expressionTo be the norm distance in the Hastethodor distance, the expression of the Hastethodor distance is treated as, wherein ,N_A Representing the number of elements in set A, for one point a in set A, calculate it to all points B in set B Taking the minimum value, carrying out cost function calculation on the minimum value to obtain a minimum value cost function value, repeating the calculation processing process on all elements a in the set A, obtaining a corresponding minimum value cost function value for each point a, taking the average value of all the minimum value cost function values as a unidirectional Haoskov distance, obtaining a backward Haoskov distance in the same way, taking the maximum value of the minimum value cost function value as the Haoskov distance, and obtaining a cost functionThere is a unique minimum value +.>Define cost function->The expression of (2) is +.>，When->When it is very small, it is easy to get up>Is greater than->And is accompanied by->The effect of disturbance such as local variation can be reduced by increasing rapidly, and the effect is increased along with +.>Gradually increase and get on>Starts to grow linearly, reflecting the true distance +.>When->When it is large, the person is left in the head>Is limited by a threshold value, avoids the interference and influence of abnormal points caused by non-faults on calculation, and thus the calculation expression of the processing and obtaining cost function is +.>。

wherein ,the value range is 0-1, and the specific value is determined by experiment and is->To reduce the effect of non-faulty abnormality>The specific value of the auxiliary parameter k is determined through experiments, and the calculation expression of the cost function is substituted into the standard Haoskov distance calculation expression, so that the improved Haoskov distance calculation expression is obtained.

In the embodiment of the disclosure, when the improved hausdorff distance calculation expression is applied to voltage operation fault detection of the battery cell, the point set a can be expressed as a voltage data point set in a terminal voltage curve of the battery cell, the point set B can be expressed as a median voltage data point set of a median voltage curve of the battery pack, and the voltage data point set and the median voltage data point set are substituted into the improved hausdorff distance calculation expression to be subjected to calculation processing so as to determine the voltage hausdorff distance between the terminal voltage curve and the median voltage curve.

S308: and performing operation voltage fault detection processing on the battery cell according to the voltage Haosdorf distance.

After determining the voltage hausdorff distance between the terminal voltage curve and the median voltage curve according to the cost function information of the battery cell, the present disclosure may perform an operation voltage fault detection process on the battery cell according to the voltage hausdorff distance.

In the embodiment of the disclosure, when the operation voltage fault detection processing is performed on the battery cell according to the voltage Haydorff distance, the voltage Haydorff distance threshold H can be determined through experimental experience _th When the voltage Hastedorff distance is greater than the voltage Hastedorff distance threshold H _th When the battery cell is in a fault state, the operation voltage fault abnormality of the battery cell can be judged, and the battery cell in the fault state can be isolated.

S309: and carrying out operation temperature fault detection processing on each battery cell in the battery pack according to the temperature data to be detected and the median temperature data.

Optionally, in some embodiments, according to temperature data to be detected and median temperature data, operating temperature fault detection processing is performed on each battery cell in the battery pack, the temperature data to be detected may be processed to obtain a battery temperature curve corresponding to each battery cell in the battery pack, median temperature data is processed to obtain a median temperature curve corresponding to the battery pack, according to cost function information of the battery cells, a temperature hausdorff distance between the battery temperature curve and the median temperature curve is determined, operating temperature fault detection processing is performed on the battery cells according to the temperature hausdorff distance, and due to the adoption of an improved hausdorff distance calculation method, a technical problem that a few abnormal values in a similarity measurement method of a standard hausdorff distance may cause an erroneous result is solved, the situation that the hausdorff distance is very large to cause an erroneous similarity measurement due to the fact that a data point result of a certain time of the battery cell is far away from other points is avoided, the appearance of the similarity measurement between the fault curves is effectively improved, and the accuracy and the robustness of the detection result of the operating voltage fault detection and the operating temperature fault are ensured.

In the implementation of the disclosure, when the operation temperature fault detection processing is performed on each battery cell in the battery pack according to the temperature data to be detected and the median temperature data, the temperature data to be detected can be processed to obtain the battery temperature data corresponding to each battery cell in the temperature data to be detected, the battery temperature curve corresponding to each battery cell is generated in a fitting mode, then the median temperature data can be processed to generate the median temperature curve corresponding to the battery pack in a fitting mode, then cost function information can be introduced to improve the calculation expression of the standard Haydon distance to obtain an improved Haydon distance calculation expression, the temperature data point set in the battery temperature curve of the battery cell and the median temperature data point set of the median temperature curve of the battery pack are substituted into the improved Haydon distance calculation expression to be subjected to calculation processing, so that the temperature Haydon distance between the battery temperature curve and the median temperature Haydon distance is determined, and when the temperature Haydon distance is larger than the temperature Haydon distance threshold, the battery cell can be judged that the operation temperature fault exists, and the battery is in an isolated state.

In this embodiment, real-time voltage data and real-time temperature data of each battery cell in a battery pack of an energy storage system are obtained respectively, battery overcharge fault detection processing and battery overtemperature fault detection processing are performed on each battery cell in the battery pack according to the real-time voltage data and the real-time temperature data, sampling processing is performed on the real-time voltage data and the real-time temperature data based on a moving window with a preset window size to obtain to-be-processed voltage data and to-be-processed temperature data, inconsistency detection processing is performed on the to-be-processed voltage data and the to-be-processed temperature data to remove abnormal voltage data in the to-be-processed voltage data, to-be-detected voltage data is obtained, abnormal temperature data in the to-be-processed temperature data is removed, median voltage sampling processing is performed on the to-be-detected voltage data to obtain median voltage data corresponding to the battery pack, performing median temperature sampling processing on temperature data to be detected to obtain median temperature data corresponding to the battery pack, performing operation voltage fault detection processing on each battery cell in the battery pack according to the voltage data to be detected and the median voltage data, performing operation temperature fault detection processing on each battery cell in the battery pack according to the temperature data to be detected and the median temperature data, performing internal short circuit fault detection processing on each battery cell in the battery pack according to the voltage data to be detected and resistance data information of each battery cell in the battery pack, performing multiple different calculation processing modes on the temperature data and the voltage data, realizing detection on multiple different faults of the battery pack of an energy storage system, realizing multiple fault detection with smaller data calculation amount, effectively improving fault detection efficiency and fault detection accuracy, the early detection of various faults of the battery pack of the energy storage system is realized, the technical problem that a small amount of abnormal values in the similarity measurement method of the standard Haoskov distance can cause an error result is improved by adopting the improved Haoskov distance calculation method, the phenomenon that the Haoskov distance is large to cause the error similarity measurement due to the fact that the data point result of a single battery is far away from other points at a certain moment is avoided, the accuracy of the similarity measurement between voltage curves is effectively improved, the occurrence of fault misdiagnosis is effectively avoided, and the accuracy and the robustness of the detection results of the operation voltage fault detection and the operation temperature fault are ensured.

Fig. 4 is a flow chart illustrating a method for detecting multiple battery faults of an energy storage system according to another embodiment of the present disclosure.

As shown in fig. 4, the battery multi-fault detection method of the energy storage system includes:

s401: and respectively acquiring real-time voltage data and real-time temperature data of each battery cell in the battery pack of the energy storage system.

The specific description of S401 may be referred to the above embodiments, and will not be repeated here.

S402: and carrying out battery overcharge fault detection processing and battery overtemperature fault detection processing on each battery cell in the battery pack according to the real-time voltage data and the real-time temperature data.

Optionally, in some embodiments, according to the real-time voltage data and the real-time temperature data, performing battery overcharge fault detection processing and battery overtemperature fault detection processing on each battery cell in the battery pack, if the real-time voltage data is greater than the real-time voltage threshold, determining that the battery cell is in a battery overcharge fault state, and if the real-time temperature data is greater than the real-time temperature threshold, determining that the battery cell is in a battery overtemperature fault state, so that the possible overcharge fault and overtemperature fault of the battery cell can be detected in real time according to the real-time voltage data and the real-time temperature data, and early faults of the battery cell can be found in time to perform isolation maintenance, so as to avoid further damage to the battery cell.

In the embodiment of the disclosure, when performing battery overcharge fault detection processing and battery overtemperature fault detection processing on each battery cell in the battery pack according to the real-time voltage data and the real-time temperature data, the maximum battery charge voltage can be set as a real-time voltage threshold value according to the running state of the battery pack of the energy storage system, the maximum battery working temperature is set as a real-time temperature threshold value, then the battery overcharge fault detection is performed according to the real-time voltage data and the real-time voltage threshold value, if the real-time voltage data is greater than the real-time voltage threshold value, the battery cell is determined to be in a battery overcharge fault state, and when performing battery overcharge fault detection on the battery cell according to the real-time temperature data and the real-time temperature threshold value, if the real-time temperature data is greater than the real-time temperature threshold value, the battery cell is determined to be in a battery overtemperature fault state, and the battery cell in the battery overcharge fault state and the battery overtemperature fault state is isolated and subjected to fault maintenance processing.

S403: and sampling the real-time voltage data and the real-time temperature data based on a moving window with a preset window size to obtain the voltage data to be processed and the temperature data to be processed.

S404: performing inconsistency detection processing on the voltage data to be processed and the temperature data to be processed to remove abnormal voltage data in the voltage data to be processed to obtain voltage data to be detected, and removing abnormal temperature data in the temperature data to be processed to obtain temperature data to be detected.

The specific description of S403 and S404 may be referred to the above embodiments, and will not be repeated here.

S405: and determining the internal short circuit resistance corresponding to the battery cell according to the voltage data to be detected, the short-term polarization resistance, the long-term polarization resistance, the short-term polarization capacitance, the long-term polarization capacitance and the battery equivalent resistance.

In an embodiment of the present disclosure, the resistance data information includes: short-term polarization resistance, long-term polarization resistance, short-term polarization capacitance, long-term polarization capacitance, and battery equivalent resistance of the battery cell.

The equivalent resistance of the battery refers to equivalent internal resistance corresponding to the battery cell.

In the embodiment of the disclosure, when internal short circuit fault detection processing is performed on each battery cell in the battery pack according to voltage data to be detected and resistance data information of each battery cell in the battery pack, open circuit voltage and battery terminal voltage corresponding to the battery cell can be obtained from the voltage data to be detected, battery current is measured and obtained, and the internal short circuit resistance corresponding to the battery cell is determined by adopting a calculation method such as a recursive least square method, a genetic algorithm, a particle swarm algorithm and the like according to short-term polarization resistance, long-term polarization resistance, short-term polarization capacitance, long-term polarization capacitance, battery equivalent resistance, open circuit voltage, battery terminal voltage and battery current of the battery cell.

S406: and determining an internal short circuit resistance threshold according to the circuit state information of the battery cell.

The circuit state information refers to data information which can be used for describing the working state of the battery cell, and the circuit state information can be used for determining an internal short circuit resistance threshold according to experimental experience.

In the embodiment of the disclosure, when the internal short circuit resistance threshold is determined according to the circuit state information of the battery cell, the resistance threshold corresponding to the internal short circuit fault state which can be applied to fault detection in various different circuit states can be determined through multiple experiments, and a proper resistance threshold is selected from the multiple resistance thresholds to serve as the internal short circuit resistance threshold according to the current circuit state information of the battery cell.

S407: and carrying out internal short circuit fault detection processing on the battery cells according to the internal short circuit resistance and the internal short circuit resistance threshold value.

According to the embodiment of the disclosure, the internal short circuit resistance corresponding to the battery cell is determined according to the voltage data to be detected, the short-term polarization resistance, the long-term polarization resistance, the short-term polarization capacitance, the long-term polarization capacitance and the battery equivalent resistance, and after the internal short circuit resistance threshold value is determined according to the circuit state information of the battery cell, the internal short circuit fault detection processing can be performed on the battery cell according to the internal short circuit resistance and the internal short circuit resistance threshold value.

Optionally, in some embodiments, the internal short circuit fault detection process is performed on the battery unit according to the internal short circuit resistance and the internal short circuit resistance threshold, if the internal short circuit resistance is smaller than the internal short circuit resistance threshold, it is determined that the battery unit has an internal short circuit fault, if the internal short circuit resistance is greater than or equal to the internal short circuit resistance threshold, it is determined that the battery unit does not have an internal short circuit fault, so that the internal short circuit resistance of the battery unit can be obtained through calculation processing, so that the internal short circuit fault of the battery unit is detected, and as the used resistance, current and voltage data are obtained through real-time measurement, the real-time performance and accuracy of the internal short circuit resistance calculation can be ensured, and the accuracy of the internal short circuit fault detection is ensured.

In the embodiment of the disclosure, the internal short circuit resistance corresponding to the battery cell obtained through calculation and the internal short circuit resistance threshold value can be subjected to numerical comparison, if the internal short circuit resistance is smaller than the internal short circuit resistance threshold value, the battery cell is determined to have an internal short circuit fault, and then the battery cell with the internal short circuit fault can be subjected to isolation and maintenance treatment.

For example, as shown in fig. 5, fig. 5 is a schematic diagram of a battery circuit in an embodiment of the disclosure, wherein R _ps and R_pl Is the short-term polarization resistance and the long-term polarization resistance of the battery cell, C _ps and C_pl Is short-term polarization capacitance and long-term polarization capacitance of battery cell, R _in Is the equivalent internal resistance of the battery, voc (SOC) is the open-circuit voltage of the battery relative to the state of charge of the battery, R _short Obtaining the battery terminal voltage V of the battery cell from the voltage data to be detected by measuring the internal short-circuit resistance of the battery cell to be estimated _t Obtaining battery current of battery cell by measurementI _b Estimating the internal short circuit resistance R corresponding to the battery cell according to a parameter estimation method (such as a recursive least square method, a genetic algorithm, a particle swarm algorithm and the like) _short And the internal short circuit resistance threshold R is set through experimental experience _{short_th} If the estimated internal short-circuit resistance R _short Less than the internal short circuit resistance threshold R _{short_th} And indicating that the battery monomer has an internal short circuit fault, and isolating and overhauling the battery monomer in a fault state.

In this embodiment, real-time voltage data and real-time temperature data of each battery cell in a battery pack of an energy storage system are obtained respectively, battery overcharge fault detection processing and battery overtemperature fault detection processing are performed on each battery cell in the battery pack according to the real-time voltage data and the real-time temperature data, sampling processing is performed on the real-time voltage data and the real-time temperature data based on a moving window with a preset window size to obtain to-be-processed voltage data and to-be-processed temperature data, inconsistency detection processing is performed on the to-be-processed voltage data and the to-be-processed temperature data to remove abnormal voltage data in the to-be-processed voltage data, to-be-detected voltage data is obtained, abnormal temperature data in the to-be-processed temperature data is removed, median voltage sampling processing is performed on the to-be-detected voltage data to obtain median voltage data corresponding to the battery pack, performing median temperature sampling processing on temperature data to be detected to obtain median temperature data corresponding to the battery pack, performing operation voltage fault detection processing on each battery cell in the battery pack according to the voltage data to be detected and the median voltage data, performing operation temperature fault detection processing on each battery cell in the battery pack according to the temperature data to be detected and the median temperature data, performing internal short circuit fault detection processing on each battery cell in the battery pack according to the voltage data to be detected and resistance data information of each battery cell in the battery pack, performing multiple different calculation processing modes on the temperature data and the voltage data, realizing detection on multiple different faults of the battery pack of an energy storage system, realizing multiple fault detection with smaller data calculation amount, effectively improving fault detection efficiency and fault detection accuracy, the early detection of various faults of the battery pack of the energy storage system is realized, the internal short circuit fault detection processing is carried out on the battery unit according to the internal short circuit resistance and the internal short circuit resistance threshold value, if the internal short circuit resistance is smaller than the internal short circuit resistance threshold value, the battery unit is determined to have the internal short circuit fault, if the internal short circuit resistance is larger than or equal to the internal short circuit resistance threshold value, the battery unit is determined to have no internal short circuit fault, and therefore the internal short circuit resistance of the battery unit can be obtained through calculation processing so as to detect the internal short circuit fault of the battery unit.

Fig. 6 is a schematic structural diagram of a battery multi-fault detection device of an energy storage system according to another embodiment of the present disclosure.

As shown in fig. 6, the battery multi-fault detection device 60 of the energy storage system includes:

an acquisition module 601, configured to acquire real-time voltage data and real-time temperature data of each battery cell in a battery pack of the energy storage system respectively;

the first detection module 602 is configured to perform a battery overcharge fault detection process and a battery overtemperature fault detection process on each battery cell in the battery pack according to the real-time voltage data and the real-time temperature data;

the first processing module 603 is configured to sample the real-time voltage data and the real-time temperature data based on a moving window with a preset window size, so as to obtain to-be-processed voltage data and to-be-processed temperature data;

the second processing module 604 is configured to perform inconsistency detection processing on the voltage data to be processed and the temperature data to be processed, so as to remove abnormal voltage data in the voltage data to be processed, obtain voltage data to be detected, and remove abnormal temperature data in the temperature data to be processed, so as to obtain temperature data to be detected;

the third processing module 605 is configured to perform median voltage sampling processing on the voltage data to be detected to obtain median voltage data corresponding to the battery pack, and perform median temperature sampling processing on the temperature data to be detected to obtain median temperature data corresponding to the battery pack;

The second detection module 606 is configured to perform an operation voltage fault detection process on each battery cell in the battery pack according to the voltage data to be detected and the median voltage data;

the third detection module 607 is configured to perform an operation temperature fault detection process on each battery cell in the battery pack according to the temperature data to be detected and the median temperature data;

and the fourth detection module 608 is configured to perform internal short circuit fault detection processing on each battery cell in the battery pack according to the voltage data to be detected and the resistance data information of each battery cell in the battery pack.

In some embodiments of the present disclosure, the second detection module 606 is specifically configured to:

processing the voltage data to be detected to obtain terminal voltage curves corresponding to all battery monomers in the battery pack;

processing the median voltage data to obtain a median voltage curve corresponding to the battery pack;

determining the voltage Haosdorf distance between the terminal voltage curve and the median voltage curve according to the cost function information of the battery cell;

and performing operation voltage fault detection processing on the battery cell according to the voltage Haosdorf distance.

In some embodiments of the present disclosure, the third detection module 607 is specifically configured to:

Processing temperature data to be detected to obtain a battery temperature curve corresponding to each battery cell in the battery pack;

processing the median temperature data to obtain a median temperature curve corresponding to the battery pack;

determining the temperature Hausdorff distance between the battery temperature curve and the median temperature curve according to the cost function information of the battery monomers;

and performing operation temperature fault detection processing on the battery monomer according to the Haoskov distance.

In some embodiments of the present disclosure, as shown in fig. 7, fig. 7 is a schematic structural diagram of a battery multi-fault detection device of an energy storage system according to another embodiment of the present disclosure, wherein the resistance data information includes: short-term polarization resistance, long-term polarization resistance, short-term polarization capacitance, long-term polarization capacitance, and battery equivalent resistance of the battery cell;

wherein the fourth detection module 608 includes:

the first determining submodule 6081 is used for determining an internal short circuit resistance corresponding to the battery cell according to the voltage data to be detected, the short-term polarization resistance, the long-term polarization resistance, the short-term polarization capacitance, the long-term polarization capacitance and the battery equivalent resistance;

a second determining submodule 6082, configured to determine an internal short-circuit resistance threshold according to the circuit state information of the battery cell;

And the detection submodule 6083 is used for performing internal short circuit fault detection processing on the battery cell according to the internal short circuit resistance and the internal short circuit resistance threshold value.

In some embodiments of the present disclosure, the detection submodule 6083 is specifically configured to:

if the internal short circuit resistance is smaller than the internal short circuit resistance threshold value, determining that the battery cell has an internal short circuit fault;

and if the internal short circuit resistance is greater than or equal to the internal short circuit resistance threshold value, determining that the battery cell has no internal short circuit fault.

In some embodiments of the present disclosure, the first detection module 602 is specifically configured to:

if the real-time voltage data is larger than the real-time voltage threshold value, determining that the battery cell is in a battery overcharge fault state;

and if the real-time temperature data is larger than the real-time temperature threshold value, determining that the battery cell is in the battery overtemperature fault state.

Corresponding to the method for detecting multiple battery faults of the energy storage system provided by the embodiments of fig. 1 to 5, the present disclosure further provides a device for detecting multiple battery faults of the energy storage system, and since the device for detecting multiple battery faults of the energy storage system provided by the embodiments of the present disclosure corresponds to the method for detecting multiple battery faults of the energy storage system provided by the embodiments of fig. 1 to 5, implementation of the method for detecting multiple battery faults of the energy storage system is also applicable to the device for detecting multiple battery faults of the energy storage system provided by the embodiments of the present disclosure, which will not be described in detail in the embodiments of the present disclosure.

To achieve the above-described embodiments, the present disclosure also proposes a non-transitory computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements a battery multi-fault detection method of an energy storage system as proposed in the foregoing embodiments of the present disclosure.

To achieve the above embodiments, the present disclosure also proposes a computer program product which, when executed by an instruction processor in the computer program product, performs a battery multi-fault detection method of an energy storage system as proposed by the foregoing embodiments of the present disclosure.

The electronic device 8 shown in fig. 8 is merely an example and should not be construed to limit the functionality and scope of use of the disclosed embodiments.

As shown in fig. 8, the electronic device 8 is in the form of a general purpose computing device. Components of the electronic device 8 may include, but are not limited to: one or more processors or processing units 16, a memory 28, and a bus 18 that connects the various system components, including the memory 28 and the processing unit 16.

Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, and a local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include industry Standard architecture (Industry Standard Architecture; hereinafter ISA) bus, micro channel architecture (Micro Channel Architecture; hereinafter MAC) bus, enhanced ISA bus, video electronics standards Association (Video Electronics Standards Association; hereinafter VESA) local bus, and peripheral component interconnect (Peripheral Component Interconnection; hereinafter PCI) bus.

Electronic device 8 typically includes a variety of computer system readable media. Such media can be any available media that is accessible by electronic device 8 and includes both volatile and non-volatile media, removable and non-removable media.

Memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (Random Access Memory; hereinafter: RAM) 30 and/or cache memory 32. The electronic device 8 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from or write to non-removable, nonvolatile magnetic media (not shown in FIG. 8, commonly referred to as a "hard disk drive").

Although not shown in fig. 8, a magnetic disk drive for reading from and writing to a removable non-volatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive for reading from or writing to a removable non-volatile optical disk (e.g., a compact disk read only memory (Compact Disc Read Only Memory; hereinafter CD-ROM), digital versatile read only optical disk (Digital Video Disc Read Only Memory; hereinafter DVD-ROM), or other optical media) may be provided. In such cases, each drive may be coupled to bus 18 through one or more data medium interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to carry out the functions of the various embodiments of the disclosure.

A program/utility 40 having a set (at least one) of program modules 42 may be stored in, for example, memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment. Program modules 42 generally perform the functions and/or methods in the embodiments described in this disclosure.

The electronic device 8 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), one or more devices that enable a person to interact with the electronic device 8, and/or any devices (e.g., network card, modem, etc.) that enable the electronic device 8 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 22. Also, the electronic device 8 may communicate with one or more networks, such as a local area network (Local Area Network; hereinafter: LAN), a wide area network (Wide Area Network; hereinafter: WAN) and/or a public network, such as the Internet, via the network adapter 20. As shown, the network adapter 20 communicates with other modules of the electronic device 8 over the bus 18. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with electronic device 8, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.

The processing unit 16 executes various functional applications and parameter information determination by running a program stored in the memory 28, for example, implementing the battery multi-fault detection method of the energy storage system mentioned in the foregoing embodiment.

It should be noted that in the description of the present disclosure, the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. Furthermore, in the description of the present disclosure, unless otherwise indicated, the meaning of "a plurality" is two or more.

Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and further implementations are included within the scope of the preferred embodiment of the present disclosure in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present disclosure.

It should be understood that portions of the present disclosure may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.

Those of ordinary skill in the art will appreciate that all or a portion of the steps carried out in the method of the above-described embodiments may be implemented by a program to instruct related hardware, where the program may be stored in a computer readable storage medium, and where the program, when executed, includes one or a combination of the steps of the method embodiments.

Furthermore, each functional unit in the embodiments of the present disclosure may be integrated in one processing module, or each unit may exist alone physically, or two or more units may be integrated in one module. The integrated modules may be implemented in hardware or in software functional modules. The integrated modules may also be stored in a computer readable storage medium if implemented in the form of software functional modules and sold or used as a stand-alone product.

The above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, or the like.

In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present disclosure. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

Although embodiments of the present disclosure have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the present disclosure, and that variations, modifications, alternatives, and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the present disclosure.

Claims

1. A battery multi-fault detection method for an energy storage system, comprising:

respectively acquiring real-time voltage data and real-time temperature data of each battery cell in a battery pack of the energy storage system;

performing battery overcharge fault detection processing and battery overtemperature fault detection processing on each battery monomer in the battery pack according to the real-time voltage data and the real-time temperature data;

sampling the real-time voltage data and the real-time temperature data based on a moving window with a preset window size to obtain voltage data to be processed and temperature data to be processed;

performing inconsistency detection processing on the voltage data to be processed and the temperature data to be processed to remove abnormal voltage data in the voltage data to be processed to obtain voltage data to be detected, and removing abnormal temperature data in the temperature data to be processed to obtain temperature data to be detected;

Performing median voltage sampling processing on the voltage data to be detected to obtain median voltage data corresponding to the battery pack, and performing median temperature sampling processing on the temperature data to be detected to obtain median temperature data corresponding to the battery pack;

performing operation voltage fault detection processing on each battery cell in the battery pack according to the voltage data to be detected and the median voltage data;

performing operation temperature fault detection processing on each battery monomer in the battery pack according to the temperature data to be detected and the median temperature data;

performing internal short circuit fault detection processing on each battery cell in the battery pack according to the voltage data to be detected and the resistance data information of each battery cell in the battery pack;

and performing operation voltage fault detection processing on each battery cell in the battery pack according to the voltage data to be detected and the median voltage data, wherein the operation voltage fault detection processing comprises the following steps:

processing the voltage data to be detected to obtain terminal voltage curves corresponding to all battery cells in the battery pack;

And determining the voltage Haoskov distance between the terminal voltage curve and the median voltage curve according to the cost function information of the battery cell, wherein the calculation expression of the cost function is as follows:

wherein ,for the sole minimum of the cost function at zero, < +.>To reduce the influence of non-fault abnormalityAn excessive threshold value, k is an auxiliary parameter, set A is a voltage data point set in a terminal voltage curve of a battery cell, set B is a median voltage data point set of a median voltage curve of a battery pack, a is an element in set A, B is an element in set B,

the expression of the voltage Haoskov distance is as follows:

wherein ,N_A Representing the number of elements in set A, B being the elements in set B;

and carrying out operation voltage fault detection processing on the single battery according to the voltage Haoskov distance.

2. The method of claim 1, wherein said performing an operating temperature fault detection process on each cell in said battery pack based on said temperature data to be detected and said median temperature data comprises:

processing the temperature data to be detected to obtain a battery temperature curve corresponding to each battery monomer in the battery pack;

determining a temperature Hausdorff distance between the battery temperature curve and the median temperature curve according to the cost function information of the battery monomers;

and carrying out operation temperature fault detection processing on the battery monomer according to the temperature Haoskov distance.

3. The method of claim 1, wherein the resistance data information comprises: short-term polarization resistance, long-term polarization resistance, short-term polarization capacitance, long-term polarization capacitance, and battery equivalent resistance of the battery cell;

and performing internal short circuit fault detection processing on each battery cell in the battery pack according to the voltage data to be detected and the resistance data information of each battery cell in the battery pack, wherein the internal short circuit fault detection processing comprises the following steps:

determining an internal short circuit resistance corresponding to the battery cell according to the voltage data to be detected, the short-term polarization resistance, the long-term polarization resistance, the short-term polarization capacitance, the long-term polarization capacitance and the battery equivalent resistance;

determining an internal short circuit resistance threshold according to the circuit state information of the battery cell;

And carrying out internal short circuit fault detection processing on the battery cell according to the internal short circuit resistance and the internal short circuit resistance threshold value.

4. The method of claim 3, wherein said performing an internal short circuit fault detection process on said battery cell based on said internal short circuit resistance and said internal short circuit resistance threshold comprises:

5. The method of claim 1, wherein said performing a battery overcharge fault detection process and a battery overtemperature fault detection process on each cell in said battery pack based on said real-time voltage data and said real-time temperature data comprises:

and if the real-time temperature data is larger than the real-time temperature threshold value, determining that the battery cell is in a battery overtemperature fault state.

6. A battery multi-fault detection device of an energy storage system, comprising:

the acquisition module is used for respectively acquiring real-time voltage data and real-time temperature data of each battery cell in the battery pack of the energy storage system;

the first detection module is used for carrying out battery overcharge fault detection processing and battery overtemperature fault detection processing on each battery monomer in the battery pack according to the real-time voltage data and the real-time temperature data;

the first processing module is used for sampling the real-time voltage data and the real-time temperature data based on a moving window with a preset window size to obtain voltage data to be processed and temperature data to be processed;

the second processing module is used for carrying out inconsistency detection processing on the voltage data to be processed and the temperature data to be processed so as to remove abnormal voltage data in the voltage data to be processed to obtain voltage data to be detected, and removing abnormal temperature data in the temperature data to be processed to obtain temperature data to be detected;

the third processing module is used for carrying out median voltage sampling processing on the voltage data to be detected to obtain median voltage data corresponding to the battery pack, and carrying out median temperature sampling processing on the temperature data to be detected to obtain median temperature data corresponding to the battery pack;

The second detection module is used for carrying out operation voltage fault detection processing on each battery cell in the battery pack according to the voltage data to be detected and the median voltage data;

the third detection module is used for carrying out operation temperature fault detection processing on each battery cell in the battery pack according to the temperature data to be detected and the median temperature data;

the fourth detection module is used for carrying out internal short circuit fault detection processing on each battery cell in the battery pack according to the voltage data to be detected and the resistance data information of each battery cell in the battery pack;

wherein ,as the only minimum of the cost function at zero point，/>To reduce the influence of non-fault abnormalityAn excessive threshold value, k is an auxiliary parameter, set A is a voltage data point set in a terminal voltage curve of a battery cell, set B is a median voltage data point set of a median voltage curve of a battery pack, a is an element in set A, B is an element in set B,

the expression of the voltage Haoskov distance is as follows:

7. An electronic device, comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.

8. A non-transitory computer readable storage medium storing computer instructions, wherein the computer instructions are for causing the computer to perform the method of any one of claims 1-5.