A New Adaptive Kalman Filter for Single-State Integrator Systems: Application to Battery State-of-Charge Estimation

Optimal energy management in HEV is primordial. A key element of energy management strategies is the battery pack State-Of-Charge (SOC). In a real-time setting, a most commonly used tool to estimate the SOC is the Kalman filter-based techniques, and more especially adaptive Kalman filtering. In this paper, we consider a particular class of Linear Time-Invariant (LTI) Single-Input Single-Output (SISO) system suited to a lot of battery types. Then, we propose a new form of adaptive Kalman filter which is more convenient to use than the original adaptive Kalman filter. Finally, we highlight the effectiveness of the proposed approach on the SOC estimation problem of a four lead-acid battery pack.