Lithium-ion Battery Capacity Estimation Based on a Adaptive Model Algorithm With Aging Test

Abstract

The actual capacity of the battery is an important indicator for calculating the health state and the remaining power-driven mileage. In this paper, an adaptive model algorithm based on equivalent circuit model is used to estimate the capacity of battery. First, a reasonable and effective second-order resistancecapacitance (RC) network equivalent circuit model is established. Second, the adaptive model algorithm based on an equivalent circuit model is employed. The capacity is calculated by the ratio between the accumulated ampere hour (Ah) and state of charge (SOC) difference. The SOC is obtained accurately mainly by the adaptive extended Kalman filter (AEKF). Finally, a comprehensive experimental schedule is designed to acquire the test data and verify the proposed method. The results manifest that after the estimated results tend to be stable, and the absolute error of SOC and capacity estimation are less than 1% and 0.1 Ah, respectively.