North China Electric Power University Distributed Botility and Micro-Network Hebei Province Key Laboratory, China Automotive Technology Research Center Co., Ltd. The article No. 18 “Journal of Electrician Technology” pointed out that “the paper title is” based on adaptive elsewheld Kalman filtering power battery health condition detection and ladder utilization “) Electricity (SOC) and Health State (SOH) is essential to extend the life of the prolonged lithium-ion battery pack and the ladder utilization.
This article is based on battery thevenin second-order equivalent circuit model, and uses adaptive elsewheld Kalman filter (AUKF) algorithm to real-time estimation of battery SOC and ohm internal resistance, and according to ohm internal resistance and battery SOH correspondence, Estimate battery SOH in real time. The battery is charged with the battery under two different conditions, and the feasibility and accuracy of the method are verified.
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