Abstract
The accurate estimation of the battery state of charge (SOC) is crucial for providing information on the performance and remaining range of electric vehicles. Based on the analysis of battery charge and discharge data under actual vehicle driving cycles, this paper presents an online estimation method of battery SOC based on the extended Kalman filter (EKF) and neural network (NN). A battery model is established to identify and calibrate battery parameters. SOC estimation is conducted in the low-SOC area by exploring the relationship between battery parameters and SOC through many experimental results. In the fusion online estimation method, the NN is carried out to propose the estimation as the global mainstream trend providing a high precision feasible region; the EKF algorithm is used to provide the initial assessment and the local fluctuation boundary revision. Verified results show that it can improve the SOC estimation in low-battery capacity accuracy. It has achieved good adaptability to the estimation accuracy of low battery capacity SOC in different cycle conditions.
Highlights
As the ecological environment gradually deteriorates, designing the cleaning and efficient vehicle has attracted significant attention
This study investigates the online estimation of state of charge (SOC) for lithiumion batteries at the low-capacity range
Based on the analysis of battery charge and discharge data under real vehicle cycle conditions, the battery model is established to identify and calibrate battery parameters and focuses on the lowcapacity SOC estimation analysis based on the extended Kalman filter (EKF) method
Summary
As the ecological environment gradually deteriorates, designing the cleaning and efficient vehicle has attracted significant attention. Pure electric vehicles (PEVs) are popular best with their environmental friendliness. The State of Charge (SOC) is an essential state of battery parameter. It is defined as the ratio of remaining power to total power. The accurate estimation of the battery status helps to provide information about the current and remaining performance of the battery and provides a guarantee for the reliable and safe operation of the PEV (Ranjbar et al, 2011; Xiong et al, 2017; Xu et al, 2021). Over-discharging and overcharging a battery can seriously affect its condition, as doing
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