SOC and SOH State of Charge Assessment of Li-ion Batteries Based on ELM Approach
By integrating the Extreme Learning Machine(ELM)model with an integrated algorithm to improve the learning efficiency,a battery health characteristic model is designed to realize the iterative calculation of each charging state.The results show that SOC and SOH reach the maximum correlation,which can effectively prevent the battery from overcharging or overdischarging.The charging termination voltage is determined by the electric vehicle user's usage demand,and the cut-off voltage is estimated based on the constant-current and constant-voltage charging demarcation to accomplish the effect of joint estimation of SOC and SOH.This study helps to improve the efficiency of lithium batteries for electric vehicles.
lithium batterystate of chargestate of healthintegrated limit learning machine
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