A lithium battery fault diagnosis method based on improved d-s evidence theory

Abstract

The invention relates to an improved D-S evidence theory-based lithium battery fault diagnosis method, which is used for determining the state of a lithium battery. The method comprises the following steps: primarily diagnosing the fault of the lithium battery by utilizing at least two diagnosis methods; according to the primary diagnosis results, constructing the evidence body corresponding to each diagnosis method, and calculating the elementary probability distribution function of each evidence body; based on the elementary probability distribution function of each evidence body, correcting the weight of each evidence body to obtain weighed evidence body; calculating the confidence degree of each nominalized focal element, obtaining a combination rule according to the confidence degree, and fusing the evidence body and the weighed evidence body corresponding to the diagnosis method according to the combination rule, to obtain the fused diagnosis result; and according to the fused diagnosis result, determining the state of the lithium battery by applying a decision rule. Compared with the prior art, the improved D-S evidence theory-based lithium battery fault diagnosis method has the advantages of being accurate in diagnosis results, high in evidence utilization rate, high in diagnosis precision, and the like.

Description

technical field [0001] The invention relates to the technical field of electric vehicle power lithium batteries, in particular to a lithium battery fault diagnosis method based on improved D-S evidence theory. Background technique [0002] The electric vehicle power lithium battery system is the basis for the entire electric vehicle to ensure the normal driving of the vehicle and accurately estimate the driving range. At present, the core technology that restricts the development of electric vehicles is whether the battery system can accurately and effectively provide power during driving to ensure safe travel. Since the current domestic power battery technology is not fully mature, the initial signs of battery failure are not easy to detect. Therefore, it is of great practical significance to conduct fault diagnosis research on lithium battery systems to ensure that the batteries are in normal operation. In the long-term use of single cells connected in series and parallel...

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Problems solved by technology

[0006] The battery fault diagnosis method adopted by Wu Jianrong of Jilin University in 2011 is similar, but the calculation method of the symptom membership degree is relatively simple

[0010] The battery cannot avoid bumps and collisions during work, resulting in too high or too low battery voltage, too high or too low current, etc. At the same time, the complexity of the battery system itself and uncertain factors such as being easily affected by the surrounding environment will lead to Decreased accuracy of fault diagnosis

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