Sequential Monte Carlo based technique for SOC estimation of LiFePO4 battery pack for electric vehicles

Battery energy storage management for electric vehicles and hybrid electric vehicles is the most critical enabling technology. A battery system is a complex electrochemical phenomenon whose performance degrades with ageing and the existence of varying material design. Moreover, it is very tedious and computationally very complex for monitoring and controlling the internal state of battery's electrochemical systems. This paper presents a particle filtering method for state of charge estimation of LiFePO4 battery. Using different open circuit voltages the state of charge is estimated with respect to the estimation accuracy and convergence. It was demonstrated that particle filter can be utilized to estimate the SOC for Li ion battery.