Comparitive analysis between coulomb counting algorithm and adaptive kalman filter algorithm for SOC estimation

State of Charge (SOC) and State of Health (SOH) are two key parameters in battery performance management, especially for electric vehicle and energy storage applications. Accurate estimation of them is required to ensure the reliability, safety, and efficiency of a battery. This review paper presents various estimation techniques developed for SOC and SOH, including Coulomb counting filters, Adaptive Kalman filters. Each technique is discussed on the basis of strengths and limits, accuracy, computational demand, and suitability for real-time applications. This paper will facilitate selecting the best estimator based on needs and conditions for research and engineers. Discussion on the recent advancement and trend of the estimator technologies is made to reflect upon future research directions.