Abstract
The electric vehicle has become an important development direction of the automobile industry, and the lithium-ion power battery is the main energy source of electric vehicles. The accuracy of state of charge (SOC) estimation directly affects the performance of the vehicle. In this paper, the first order fractional equivalent circuit model of a lithium iron phosphate battery was established. Battery capacity tests with different charging and discharging rates and open circuit voltage tests were carried out under different ambient temperatures. The conversion coefficient of charging and discharging capacity and the simplified open circuit voltage model considering the hysteresis characteristics of the battery were proposed. The parameters of the first order fractional equivalent circuit model were identified by using a particle swarm optimization algorithm with dynamic inertia weight. Finally, the recursive formula of a fractional extended Kalman filter was derived, and the battery SOC was estimated under continuous Dynamic Stress Test (DST) conditions. The results show that the estimation method has high accuracy and strong robustness.
Highlights
With the decrease in non-renewable energy and the turbulence of the global energy situation, the development of green energy has become an important theme of the global automobile industry [1,2].In the past decade, electric vehicles have shown a rapid development trend, and ownership has increased year by year
The battery state of charge (SOC) is an important parameter in the battery management system, which can provide a basis for the battery management and maintenance system to prevent the battery from over charging or discharging, which will lead to the decrease in battery life and potential safety hazards
The most widely used observer is the extended Kalman filter (EKF) which has nonlinear estimation ability to estimate the SOC of a battery [25], but, for integer order models, the accuracy is poor
Summary
With the decrease in non-renewable energy and the turbulence of the global energy situation, the development of green energy has become an important theme of the global automobile industry [1,2]. When the battery state changes frequently, if not considering the hysteresis characteristics of the open circuit voltage, the error of the model output voltage will be extended, and the accuracy of the model will decrease. The most widely used observer is the extended Kalman filter (EKF) which has nonlinear estimation ability to estimate the SOC of a battery [25], but, for integer order models, the accuracy is poor. The influence of temperature and hysteresis characteristics of open circuit voltage on the fractional order model was considered, and the SOC estimation of a battery was studied by using the extended Kalman filter. SOC was estimated by using a the parameters of a fractional equivalent circuit model at different temperatures.
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