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Progressive intelligence estimation of SOC based on multiple models
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AI
DOI：10.1088/1755-1315/208/1/012028.png)
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摘要
En 中文
In order to accurately estimate stage of charge(SOC) of the electric car lithium-ion battery, the paper used a variety of equivalent circuit model and built space state equation, through real-time online with forgetting factor recursive least squares identification battery model parameters, dynamic real-time update battery model state equation, the experimental condition to make use of the Matlab simulation, based on the battery circuit model of joint (FFRLS - EKF) algorithm, and joined the battery stage of health(SOH), The average error of the obtained SOC estimate is less than 1.8i% and the maximum error is less than 3%. Finally, the accuracy of FFRLS-EKF-SOC is verified, and the error accumulation problem is solved.
Keyword:
CHARGE
STATE
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