Battery state-of-charge estimation based on H<inf>∞</inf> filter for hybrid electric vehicle

Abstract

State-of-charge (SOC) estimation is the most difficult problem in battery management system, which is one of the key component of electric vehicle and hybrid electric vehicle. Suffered from the non-zero mean noise and uncertain model parameters in practice, the conventional current integral and Kalman filter estimation methods can not achieve the required accuracy, even causing nonconvergent results. The essential difficulties to apply current integral and Kalman filter to solve SOC estimation problem in colored noise and time-variant battery system are analyzed. H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> filter, an estimator designed to handle the estimation problem in noised and uncertain situation, is then applied to calculate SOC online. The simulation experiment based on a typical battery model verifies the availability and efficiency of the proposed method.