Abstract
A robust extended Kalman filter (EKF) is proposed as a method for estimation of the state of charge (SOC) of lithium-ion batteries used in hybrid electric vehicles (HEVs). An equivalent circuit model of the battery, including its electromotive force (EMF) hysteresis characteristics and polarization characteristics is used. The effect of the robust EKF gain coefficient on SOC estimation is analyzed, and an optimized gain coefficient is determined to restrain battery terminal voltage from fluctuating. Experimental and simulation results are presented. SOC estimates using the standard EKF are compared with the proposed robust EKF algorithm to demonstrate the accuracy and precision of the latter for SOC estimation.
Highlights
Lithium-ion batteries have become a promising alternative power source in electric vehicles (EVs) and power assist units used in hybrid electric vehicles (HEVs)
The self-defined hybrid pulse power characterization shown in Figure 8 was applied for validating state of charge (SOC) estimation using the Robust extended Kalman filter (EKF)
The hysteresis voltage was included in the battery model to improve the accuracy of SOC
Summary
Lithium-ion batteries have become a promising alternative power source in electric vehicles (EVs) and power assist units used in hybrid electric vehicles (HEVs). Their advantages include high nominal cell voltage, high energy density, long life and not having a memory effect. It is necessary for the battery to be effectively managed to improve its Energies 2012, 5 performance and extend its lifetime. The main components of a battery management system include state of charge (SOC) estimation, cell balancing, thermal management, and safety control. Accurate estimation of the SOC of the battery is important for accurate simulation and optimization, and real time energy management of HEVs and EVs
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