A Novel Method for Estimation of State of Charge of Lithium-ion Battery using Extended Kalman Filter

Hybrid and electric vehicles are becoming increasingly popular these days owing to concerns over exhaustion of conventional fuel sources, pollution from combustion, as well as high carbon foot print of these fuels. Lithium-ion batteries are widely preferred as the source of power for hybrid and electric vehicles because of their high monomer voltage and high energy density. Accurate estimation of the State of Charge (SoC) of battery is crucial in the electric vehicle. It provides the information on the range of operation of the vehicle. It also ensures the safety and reliability of the battery unit. Accurate State of Charge estimation also enables more optimized battery pack design for the electric vehicle. Conventional methods for State of Charge estimation such as Coulomb counting and Open Circuit Voltage (OCV) measurement suffer from inaccuracies and is affected by noise during the vehicle operation. This paper proposes a novel approach to accurately estimate State of Charge of Lithium-ion batteries based on Extended Kalman Filter. This method uses equivalent circuit of the Lithium-ion battery for the purpose of developing the state and observer equations of Extended Kalman Filter.