A probabilistic modeling method for the mechanical strength of a lithium battery cell based on a hybrid simulation method

Abstract

The present invention relates to a probabilistic model of the mechanical strength of a lithium battery cell based on a hybrid simulation method, including: (1) establishment of a boundary condition model for the mechanical strength of a lithium battery cell; determining the boundary condition of the mechanical strength response based on the composition of the lithium battery material; 2) Establishment of the finite element model of the lithium battery cell; according to the mechanical strength boundary condition model and the displacement-mechanical strength relationship curve, the finite element model of the lithium battery cell is established; (3) the establishment of a hybrid simulation model for the estimation of the mechanical strength of the lithium battery cell; Artificial neural network (ANN) and uncertainty estimation theory (MUET) are introduced to establish a hybrid simulation model. The beneficial effects of the present invention are: the model combines the artificial neural network and the matrix-based uncertainty evaluation method, and utilizes the finite element model of the lithium battery cell to evaluate its internal mechanical strength. The probability model and research results proposed by the present invention are as follows: Help lithium battery manufacturers improve the safety of electric vehicle applications and improve traffic road safety.

Description

technical field [0001] The invention relates to a probability model based on a simulation method, more specifically, it relates to a probability model for estimating the mechanical strength of a lithium battery cell based on an artificial neural network and uncertainty analysis. Background technique [0002] In the application process of lithium batteries, capacity and life are two major technical problems restricting its development. At present, most researches focus on the capacity and aging of lithium batteries, which involve many parameters of lithium batteries, such as temperature, depth of discharge, SEI film growth Wait. However, an important parameter-the internal mechanical strength of the lithium battery is ignored, which is an important indicator for evaluating the safety factor of the battery under the influence of factors such as external impact. At present, although there are a lot of research results on the internal heat generation and heat conduction of lith...

AI Technical Summary

Problems solved by technology

To sum up, the existing mechanical strength testing and estimation methods are still in the stage of physical and chemical experiments, with low calculation accuracy and large amount of data.

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