Lithium-ion battery capacity estimation based on battery surface temperature change under constant-current charge scenario. (15th February 2022)

• Record Type: Journal Article
• Authors: Yang, Jufeng; Cai, Yingfeng; Mi, Chris
• Is Part Of: Energy. Volume 241(2022)
• Publication Date: 2022-02-15
• Subjects: Electric vehicles (EVs) -- Lithium-ion batteries -- Capacity estimation -- Differential thermal voltammetry (DTV) -- Battery surface temperature change -- Temperature curve transformation; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2021.122879
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Accurate estimation of battery actual capacity in real time is crucial for a reliable battery management system and the safety of electrical vehicles. In this paper, the battery capacity is estimated based on the battery surface temperature change under constant-current charge scenario. Firstly, the evolution of the smoothed differential thermal voltammetry (DTV) curves throughout the aging process is analyzed. Then, the change of the battery surface temperature, which is equivalent to the area under the DTV curve, over a specific voltage range is introduced as a direct feature of interest to reflect the battery actual capacity. In addition, the temperature variation transformation is utilized to reduce the influence of the initial battery inconsistency. Lastly, two battery degradation datasets are utilized to validate the proposed method. The maximum root mean-square errors of the estimation results by the reference correlation are less than 20 mAh and 60 mAh for the two employed batteries (respective nominal capacities are 740 mAh and 4800 mAh). Specifically, the mean estimation errors for the respective two batteries are reduced by approximately 24.74% and 39.60% after the temperature variation transformation. The proposed method is further compared with the existing DTV analysis method and demonstrates the superior performance. Highlights: Introduced battery surface temperature change over certain voltage range as FoI. Determined voltage range based on differential thermal voltammetry analysis. Utilized temperature variation transformation to reduce initial inconsistency. Developed a capacity estimation method under constant-current charge scenario. Validated the feasibility based on aging data from two different batteries.