CN-122017612-A - Aluminum air battery discharge fault diagnosis method and system

CN122017612ACN 122017612 ACN122017612 ACN 122017612ACN-122017612-A

Abstract

The invention relates to the technical field of battery discharge fault diagnosis, and particularly discloses a method and a system for diagnosing discharge faults of an aluminum air battery, which realize the refinement, intelligent fault diagnosis and isolation of an aluminum air battery block. The method comprises the steps of collecting the content of dissolved oxygen in a channel of a battery pack to be tested through an optical fluorescence method dissolved oxygen sensor arranged in a battery pack cooling channel and an exhaust channel, performing discharge analysis and air circulation operation analysis, primarily judging air circulation faults, generating circulation early warning signals, obtaining battery parameters of the battery pack to be tested, determining battery parameters of battery packs of different blocks based on a preset partition strategy, performing feature extraction on the battery parameters of the battery packs of different blocks, obtaining target block features, obtaining dynamic data of different blocks in a discharging process, analyzing deviation between an actual average dynamic data range and an expected dynamic data range, evaluating according to the deviation corresponding to the target block and the target block features, and screening fault batteries.

Inventors

DUAN WEIPENG
CAO SHU
PENG GUANGPAN
DING YANAN
LIANG XIAOTONG
LI XIXI
CHEN WANG
SHI YU

Assignees

无锡职业技术大学

Dates

Publication Date: 20260512
Application Date: 20260304

Claims (10)

1. A method for diagnosing discharge faults of an aluminum-air battery, the method comprising: S1, collecting the dissolved oxygen content of a channel in a battery pack to be detected through an optical fluorescence method dissolved oxygen sensor arranged in a battery pack cooling channel and an exhaust channel, and judging whether the dissolved oxygen content is in a preset oxygen concentration interval threshold value or not: If yes, executing discharge analysis, and entering step S3; If not, carrying out air circulation operation analysis to judge whether an air circulation fault exists: If yes, generating a circulating early warning signal; If not, judging that the physical component faults exist, and entering step S2; S2, acquiring battery parameters of a battery pack to be detected, determining battery parameters of battery packs of different blocks based on a preset division strategy, and extracting characteristics of a target block; s3, acquiring dynamic data of different blocks in the discharging process, wherein the dynamic data comprises voltage and temperature; And S4, evaluating according to the deviation corresponding to the target block and the target block characteristics, and screening the fault battery.
2. The method for diagnosing a discharge failure of an aluminum-air battery as recited in claim 1, wherein the analysis of the air circulation operation in step S1 includes: starting a standby circulating pump, improving the power of a main circulating pump, checking and prompting the blockage fault of the gas circuit, and determining the fault type.
3. The method according to claim 1, wherein the predetermined division strategy is to divide blocks based on a physical structure of a battery pack, and the blocks are modules, battery clusters, or virtual units composed of a specific number of battery cells.
4. The method for diagnosing a discharge failure of an aluminum-air battery as recited in claim 3, wherein the battery parameters include static parameters and internal resistances, and the target block characteristics include at least one of a voltage range of cells in a block, a standard deviation of capacity of cells in a block, and an internal resistance uniformity coefficient of a block.
5. The method for diagnosing a discharge failure of an aluminum-air battery as recited in claim 1, wherein the step S3 is a specific process of analyzing the deviation by calculating the change rates of the voltage and the temperature with respect to the initial values of different blocks in the constant-current discharge or pulse discharge phase and comparing the change rates with an expected change rate threshold.
6. The method according to claim 5, wherein the step of calculating the rate of change of the voltage with respect to the initial value and comparing the calculated rate of change with the expected rate threshold value in the constant current discharge phase is: for any block, its voltage change rate deviation value Calculated by the following formula: ; Wherein, the The average voltage of the block at the starting moment of constant-current discharge is obtained; for the block after the constant current discharge starts Average voltage at time; is the discharge time; The expected voltage change rate reference value of the fault-free block with the same model under the same test condition; Judging when it is When the voltage deviation threshold value is larger than the preset voltage deviation threshold value, judging that the voltage dynamic data of the block is abnormal; The process of calculating the change rate of the temperature relative to the initial value of the different blocks in the constant current discharge stage and comparing the change rate with the expected change rate threshold value comprises the following steps: ; Wherein, the The average temperature of the block at the constant-current discharge starting moment is obtained; for the block after the constant current discharge starts Average temperature at time; is the discharge time; The expected temperature rise rate reference value of the fault-free block with the same model under the same test condition; Judging when it is And when the temperature deviation threshold value is larger than the preset temperature deviation threshold value, judging that the temperature dynamic data of the block is abnormal.
7. The method for diagnosing a discharge failure of an aluminum-air battery as recited in claim 6, wherein the expected dynamic data range is obtained by performing historical data statistics or simulation based on a battery electrochemical model on a same type of non-failure battery pack at the same ambient temperature and discharge rate.
8. The aluminum-air battery discharge failure diagnosis method according to claim 1, wherein the S4 step includes: Weighting and fusing the target block characteristics and the corresponding deviation to obtain a comprehensive health score; and comparing the comprehensive health score with a preset fault threshold value to determine block faults.
9. The method for diagnosing a discharge failure of an aluminum-air battery as recited in claim 8, wherein the process of obtaining the composite health score is as follows: constructing the deviation of the target block characteristic of each block from the corresponding deviation as a characteristic vector , wherein, Represents the first Target block features, representing the first Dynamic data bias; the feature vector is processed Similarity comparison is carried out on the fault detection result and a plurality of preset typical fault mode reference vectors; the typical fault mode reference vector includes an internal resistance increase mode reference vector Consistency degradation mode reference vector Partial overheat mode reference vector caused by air circulation deficiency ; Based on the weighted fusion of similarity comparison results, the comprehensive health score Calculated by the following formula: ; Wherein, the Is vector quantity And Is a function of the cosine similarity of (c) to (d), 、、 Weight coefficient corresponding to each failure mode and ; Setting a first failure threshold And a second failure threshold value And (2) and < ; Judging if it is ≥ Judging the health of the block; Judging if it is > ≥ Judging the performance degradation of the block, and generating a cyclic early warning signal; Judging if it is < Then it is determined that the block is faulty.
10. An aluminum air battery discharge fault diagnosis system for implementing the aluminum air battery discharge fault diagnosis method as defined in any one of claims 1 to 9, comprising: The data acquisition and primary diagnosis module is used for acquiring the dissolved oxygen content of the channel in the battery pack to be detected through an optical fluorescence method dissolved oxygen sensor arranged in the battery pack cooling channel and the exhaust channel and judging whether the dissolved oxygen content is within a preset oxygen concentration interval threshold value: if yes, triggering a discharge analysis module; If not, triggering an air circulation control and analysis module; the air circulation control and analysis module is used for executing air circulation operation analysis after receiving the trigger signal of the environment state monitoring and fault initial judging module and judging whether an air circulation fault exists or not: If yes, generating a circulating early warning signal; If not, judging that the physical component has faults, and triggering a feature extraction module; the feature extraction module is used for acquiring battery parameters of the battery pack to be detected, determining to perform feature extraction on the battery parameters of the battery packs of different blocks based on a preset division strategy, and acquiring target block features; The discharge analysis module is used for acquiring dynamic data of different blocks in the discharge process, wherein the dynamic data comprises voltage and temperature; and the evaluation module is used for evaluating according to the deviation corresponding to the target block and the target block characteristics and screening the fault battery.

Description

Aluminum air battery discharge fault diagnosis method and system Technical Field The invention relates to the technical field of battery discharge fault diagnosis, in particular to a method and a system for diagnosing discharge faults of an aluminum-air battery. Background The aluminum-air battery has wide application prospect in the fields of electric automobiles, unmanned aerial vehicles, standby power supplies, special equipment and the like. The working principle is that the electrochemical reaction between the metal aluminum anode and oxygen in the air takes place in the electrolyte to directly convert chemical energy into electric energy. In the actual discharging operation process of the aluminum-air battery, the performance and the reliability of the aluminum-air battery are limited by various complex factors, various discharging faults are easy to occur, and the service life and the system safety of the aluminum-air battery are seriously influenced. In order to identify a specific fault of battery discharge, the existing method mostly only monitors a single external electrical parameter such as terminal voltage or discharge current of the battery to judge the fault of the battery. However, different types of faults may show similar electrical property attenuation characteristics in the early stage, and are difficult to accurately distinguish and position only by voltage or current changes, so that erroneous judgment or missed judgment is very easy to cause. In particular, in the actual detection process of the discharge faults of the aluminum air battery, the fault type is not positioned, particularly the problem that the fault source is difficult to distinguish accurately between the fault of a battery channel and the fault of a battery block is solved, and the states of all the battery blocks are judged by only using a fixed and unified threshold value, so that the performance difference and the inconsistency of different battery individuals are ignored, and the false alarm is easily caused. Disclosure of Invention The invention aims to provide a method and a system for diagnosing discharge faults of an aluminum-air battery, which solve the following technical problems: how to provide a fault diagnosis method capable of carrying out multi-dimensional, layered and accurate positioning and early warning on an aluminum-air battery pack so as to overcome the problem that the fault source is difficult to distinguish in the prior art; how to realize timely treatment of the defect problem of high false alarm rate caused by the lack of monitoring the state of the aluminum-air battery pack, the masking of local faults and the poor adaptability of a diagnosis model. The aim of the invention can be achieved by the following technical scheme: a method for diagnosing discharge faults of an aluminum-air battery comprises the following steps: S1, collecting the dissolved oxygen content of a channel in a battery pack to be detected through an optical fluorescence method dissolved oxygen sensor arranged in a battery pack cooling channel and an exhaust channel, and judging whether the dissolved oxygen content is in a preset oxygen concentration interval threshold value or not: If yes, executing discharge analysis, and entering step S3; If not, carrying out air circulation operation analysis to judge whether an air circulation fault exists: If yes, generating a circulating early warning signal; If not, judging that the physical component faults exist, and entering step S2; S2, acquiring battery parameters of a battery pack to be detected, determining battery parameters of battery packs of different blocks based on a preset division strategy, and extracting characteristics of a target block; S3, acquiring dynamic data of different blocks in the discharging process, wherein the dynamic data comprises voltage and temperature; And S4, evaluating according to the deviation corresponding to the target block and the target block characteristics, and screening the fault battery. Preferably, the analysis of the air circulation operation in step S1 includes: starting a standby circulating pump, improving the power of a main circulating pump, checking and prompting the blockage fault of the gas circuit, and determining the fault type. Preferably, the preset dividing strategy is to divide blocks based on the physical structure of the battery pack, and the blocks are modules, battery clusters or virtual units composed of a specific number of battery cells. Preferably, the battery parameters comprise static parameters and internal resistances, and the target block characteristics comprise at least one of voltage range of the battery cells in the block, standard deviation of capacity of the battery cells in the block and internal resistance consistency coefficient of the block. Preferably, the specific process of analyzing the deviation in the step S3 is to calculate the change rate of the voltage and the temperature relative to