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Energy storage battery unsupervised fault diagnosis algorithm based on similarity measurement

A fault diagnosis algorithm and similarity measurement technology, applied in the direction of measuring electricity, measuring electrical variables, measuring devices, etc., can solve the problems of difficult fault diagnosis of charging and discharging characteristics of batteries, and achieve low computational overhead, strong adaptability, and robustness Good results

Pending Publication Date: 2022-04-15
浙江零碳数字能源科技有限公司
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AI Technical Summary

Problems solved by technology

A large number of battery cells, the charging and discharging characteristics of lithium batteries, and environmental factors at the return point all bring difficulties to battery fault diagnosis

Method used

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  • Energy storage battery unsupervised fault diagnosis algorithm based on similarity measurement
  • Energy storage battery unsupervised fault diagnosis algorithm based on similarity measurement
  • Energy storage battery unsupervised fault diagnosis algorithm based on similarity measurement

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Embodiment Construction

[0026] The present invention will be further described below in conjunction with drawings and embodiments.

[0027] S1. Collect voltage signals of battery packs in several charging and discharging cycles, including data of normal batteries and faulty batteries. Assuming that the detected battery pack contains m single cells, and there are n sampling samples in several charge and discharge cycles, the monitoring matrix X of the battery pack is constructed = [X 1 , X 2 ,...,X n ]∈R n×m ,in

[0028] x i ∈R m , i=1, 2, m, x ·j ∈R n , j=1, 2, . . . , n.

[0029] S2. Connect the data matrix to the outlier processing module, which can filter and smooth the monitoring signal. For the monitoring signal at time t, the outlier processing module constructs a time window W t , the length of the time window is L, so the data contained in the window [X t-L , X t-L+2 ,...,X t-1 ]. For the monitoring signal of each single battery, due to the existence of noise, sensor mutation, e...

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Abstract

The invention provides an energy storage battery unsupervised fault diagnosis algorithm based on similarity measurement, and belongs to the field of energy storage battery fault diagnosis. The problem that high-efficiency series battery pack fault detection and positioning cannot be realized autonomously in the prior art is solved. The method comprises the following steps: monitoring, collecting and summarizing signals in the charging and discharging processes of the energy storage battery, and constructing an unsupervised fault diagnosis data set; the collected signals are cleaned, abnormal points are removed, and meanwhile, a filter is constructed to suppress noise mixed in sampling; constructing a key point sequence of each single battery according to the signal characteristics of the charging and discharging process; extracting segmentation trend term characteristics of the monitoring signal, segmenting the complete monitoring signal into time slices, and performing segmentation linearization; constructing a single battery outlier calculation module; information fusion of multiple standards is realized, the outlier degree is obtained and serves as an important measurement index of fault occurrence, and then a fault battery is judged. The method has the advantages of quickly checking faulty batteries and providing maintenance suggestions.

Description

technical field [0001] The invention relates to the field of fault diagnosis of energy storage batteries, in particular to an unsupervised fault diagnosis algorithm for energy storage batteries based on similarity measurement. Background technique [0002] Promoting the rapid development of new energy storage is an important technology and basic equipment to support the new power system. [0003] On the power supply side, energy storage can ensure the efficient consumption and utilization of new energy, provide capacity support and certain peak-shaving capabilities for the power system; on the grid side, it can improve the flexible adjustment capability and safety of the system after large-scale and high-proportion new energy and large-capacity DC access Stable level; at the end of the power grid and in remote areas, build energy storage or wind-solar storage power stations to improve the power supply capacity of the power grid; mobile or fixed energy storage can improve eme...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/382G01R31/367
Inventor 范运飞陈文胜李峰毛涛涛
Owner 浙江零碳数字能源科技有限公司
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