Jointly Estimation Method of the SOC and SOH of Lithium-ion Battery based on Fractional Order Multi-Innovation Dual Unscented Kalman Filter

Batteries of electronic quantities detection and state of health have always been the core of the battery management system of electric vehicles, which is capable of estimating SOC accurately and quickly and ensuring the safe operation of electric vehicles. Aiming at the problem of large estimation deviation of SOC and SOH in the whole life cycle of lithium battery, this paper proposes a multi-innovation dual Unscented Kalman Filter based on fractional-order model. Firstly, the fractional-order model of lithium battery is established and the parameters of the model are identified by a genetic algorithm. Secondly, the fractional-order multi-innovation Unscented Kalman Filter is proposed to estimate SOC, and the ohmic resistance and SOH are estimated by Unscented Kalman Filter to improve the SOC estimation accuracy in the whole life cycle. Finally, the proposed algorithm is verified by Urban Dynamometer Driving Schedule(UDDS) dynamic condition data.