Battery aging estimation algorithm with active balancing control in battery system

This article presents an open-circuit voltage differential comparison algorithm (OCV-DCA) for battery aging online estimation with active balancing control. In this method, by utilizing only a portion of battery discharging/charging data, the parameters of the equivalent circuit model are calculated and the open-circuit voltage (OCV) is estimated based on the model. Then, an accurate estimation of the battery's remaining capacity is achieved by contrasting the predicted OCV with the reference OCV. The estimated capacity is then integrated into the balancing controller to refine the state-of-charge (SOC) calculation. As a result, the battery SOC balancing shall be more accurate as it takes into account the impact of battery health, which is often overlooked in traditional balancing methods. With the presented OCV-DCA algorithm and battery balancing controller, energy is drawn at a higher rate from the less degraded (better health) cell and vice versa, such that all cells reach the end of discharging/charging operation at the same time. The results of the presented method are validated from a laboratory experimental setup. The findings highlight the importance of integrating battery aging into system optimization and control methods, which are generalized and applicable in real-world battery applications. • The OCV-DCA algorithm updates battery SOC and SOH online using only partial charge/discharge data, achieving high accuracy. • The battery pack balancing method addresses capacity changes from aging to optimize energy utilization and extend battery life. • Utilizing operational current and OCV curves to calculate internal resistance reduces computation cost for estimating remaining capacity.