State of Health Estimation for Lithium-ion Battery Based on D- UKF

This paper considers an accurate estimation method of State of Health (SOH) for lithium battery. An improved battery model is proposed which is based on equivalent circuit model and battery internal electrochemical characteristics. In our study, Double Unscented Kalman Filtering (D-UKF) algorithm is designed to calculate State of Charge (SOC) and SOH of lithium battery at the same time. The feature of our new method is SOH estimation model is derived based on battery internal resistances. The Ohmic resistance (one of internal resistances) can be identified online based on D-UKF algorithm. Two filters defined as UKF1 and UKF2 are working together to calculate the real-value of SOC and Ohmic resistance to obtain final SOH value. The experimental results indicate that our new battery model considers different value of battery internal resistances on different working condition (as different voltages, different currents). Besides, our study verifies the performance and feasibility of new estimation method based on D-UKF. This new algorithm has the practical value to further study for other types of lithium battery.

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