A Lithium-Ion Battery-in-the-Loop Approach to Test and Validate Multiscale Dual H Infinity Filters for State-of-Charge and Capacity Estimation

An accurate battery capacity and state estimation method is one of the most significant and difficult techniques to ensure efficient and safe operation of the batteries for electric vehicles (EVs). Since capacity and state of charge (SoC) are strongly correlated, the SoC is hardly to be accurately estimated without knowing accurate battery capacity. Thus, a multiscale dual Hinfinity filter (HIF) has been proposed to estimate battery SoC and capacity in real time with dual timescales in response to slow-varying battery parameters and fast-varying battery state. The proposed method is first evaluated and verified using off-line experimental data and then compared with the single/multiscale dual Kalman filters (KFs). The results show that the proposed multiscale dual HIFs has better robustness and higher estimation accuracy than the single/multiscale dual KFs. To further validate the feasibility of the proposed method for EV applications, a lithium-ion battery-in- the-loop approach is applied to verify the stability and accuracy of the SoC estimation, and it is found that the SoC estimated from the proposedmethod can converge to the reference value gradually and be stabilized within 2%.