Electric Vehicle Battery State-of-Charge Estimation Based On Unscented-kalman Filtering

As the energy storage of electric vehicles (EV), power battery, whose accurateestimation of State of Charge (SOC) has been a key point and a core technology in theEV research field. SOC could provide driving range for drivers, avoid overcharge andoverdischarge of battery and furthermore guarantee the safety of driver. Aiming tosolve the SOC estimation of Lithium ion batteries, the main work of this paper are asfollows:First of all, expounding the background of EV developing, clarify the meaning ofestimating battery’s SOC, comparing the advantages and disadvantages of thecommonly used power batteries, indicating that Lithium-ion battery is the idealenergy storage at the moment, analyzing the research status of SOC estimationdomestic and overseas.As to a method based on model, building an appropriate battery model issignificant to improve the accuracy, so this paper introduces several commonequivalent circuit models of battery, and adopts the second-order RC model. Toachieve a relative more accurate output, carrying out a rapid demarcation of therelationship between the battery open circuit voltage (OCV) and SOC, and identifyingthe parameters of the model with the method of forgetting factor least-squares methodin real time.Subsequently, introducing the idea of using Extended Kalman Filter (EKF) theoryto estimate system state variables, based on which promoting a method of UnscentedKalman Filter (UKF) theory to estimate SOC. Considering the state-space form of second-order RC model, according to the real parameters of Lithium ion battery,realizing the UKF SOC estimation under the environment of Matlab, then comparingthe output with EKF method. The simulation shows that UKF could provide anaccurate estimation of SOC under the term of white noise, and be better than EKF inthe same conditions.Finally, building EV model under the environment of ADVISOR, consummatingthe EV parameter and undertaking a simulation. Based on the data acquired under theactual working conditions, ultimately this paper builds the UKF SOC estimationmethod with Matlab. The experimental results show the feasibility, effectiveness andaccuracy of UKF used in SOC estimation.