Online Identification and Reconstruction of Open-Circuit Voltage for Capacity and Electrode Aging Estimation of Lithium-Ion Batteries
Zhongrui Cui, Naxin Cui, Changlong Li, Jianbo Lu, Chenghui Zhang
Abstract
Complex operating conditions of lithium-ion batteries in practical applications bring challenges to accurate diagnosis of battery aging. This article proposes a practical method to estimate both battery capacity and electrode aging through an open-circuit voltage (OCV) reconstruction process. First, the recursive least square algorithm is implemented in a real battery management system (BMS) to identify OCV in real-time. Then, an electrode OCV model is employed to reconstruct the OCV curve based on the raw identified data from BMS. Thus, the parameters of the electrode OCV model are obtained, with which the battery capacity and electrode aging can be determined. During OCV reconstruction, a two-step estimation method with weighted objective functions is utilized to address the impact of fragmented and poorly identified OCV in BMS. Meanwhile, the Peukert coefficient is employed to improve the adaptability to different temperatures. The proposed method is validated with four aged batteries at different temperatures of 5 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^\circ \rm C$</tex-math></inline-formula> , 25 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^\circ \rm C$</tex-math></inline-formula> , and 45 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^\circ \rm C$</tex-math></inline-formula> , respectively. Experimental results indicate that the proposed method can achieve accurate estimations of battery capacity and electrode aging state at various temperatures.