Extended Kalman Filter Based Battery State of Charge (SOC) Estimation for Electric Vehicles

This paper proposed a battery state of charge (SOC) estimation methodology utilizing the Extended Kalman Filter. First, Extended Kalman Filter for Li-ion battery SOC was mathematically designed. Next, simulation models were developed in MATLAB/Simulink, which indicated that the battery SOC estimation with Extended Kalman filter is much more accurate than that from Coulomb Counting method. This is coincident with the mathematical analysis. At the end, a test bench with Lithium-Ion batteries was set up to experimentally verify the theoretical analysis and simulation. Experimental results showed that the average SOC estimation error using Extended Kalman Filter is <;1%.