MULTI-INNOVATION RECURSIVE BAYESIAN ALGORITHM-BASED BATTERY MODEL PARAMETER IDENTIFICATION METHOD
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机译：基于多新息递归贝叶斯算法的电池模型参数辨识方法
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摘要
A multi-innovation recursive Bayesian algorithm-based battery model parameter identification method, comprising the following steps: step 1) measuring terminal voltage and load current data of a lithium ion battery within a certain period of time by means of an intermittent constant current discharge method, and determining an OCV-SOC functional relationship thereof by means of a polynomial fitting method; step 2) determining a dual-polarized equivalent circuit model of the lithium ion battery, and establishing a system equation that represents the relationship between a battery parameter identification vector and system output; and step 3), establishing an identification process of a multi-innovation recursive Bayesian algorithm. According to the method, an ARX model for parameter identification of the lithium ion battery is established, the innovation correction technology is used to correct results at a previous moment, and innovation length parameters are introduced on the basis of the multi-innovation identification method, which overcomes the influence of bad data on parameter estimation and improves the parameter estimation accuracy. It may be seen from the parameter identification results that the present method has high identification accuracy and has engineering value.
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