A fast capacity estimation method based on open circuit voltage estimation for LiNixCoyMn1-x-y battery assessing in electric vehicles. (December 2020)

• Record Type: Journal Article
• Authors: Zhou, Zheng; Cui, Yifan; Kong, Xiangdong; Li, Jiaqi; Zheng, Yuejiu
• Is Part Of: Journal of energy storage. Volume 32(2020)
• Publication Date: 2020-12
• Subjects: Capacity estimation -- Open circuit voltage prediction -- Voltage relaxation -- Rapid battery life evaluation; Energy storage -- Periodicals; Energy storage -- Research -- Periodicals; 621.3126
• DOI: 10.1016/j.est.2020.101830
• Languages: English
• ISSNs: 2352-152X

Abstract

Hightlights: A fast off-line capacity estimation method based on fast OCV estimation is proposed for EV assessment. A test procedure which takes less than 30 minutes in total is designed for the fast estimation. A novel voltage relaxation model containing two parallel resistor–capacitor components with different weights is proposed. The Beetle antenna search algorithm is used for the parameter identification with higher efficiency. Abstract: With the widespread popularity of electric vehicles (EV), effective assessment for retired EVs has become increasingly critical. Unlike traditional internal combustion vehicles, for EV, batteries account for a large proportion of the entire vehicle cost. Therefore, a fast battery capacity estimation method based on open-circuit voltage (OCV) estimation is forthwith proposed. The method calculates capacity using the ratio of the change in electric quantity to the corresponding change in state-of-charge (SOC), and the SOC is estimated via a fast OCV estimation method proposed in this paper. The fast test procedure includes a charging/discharging test and a short rest, which take less than 30 minutes in total and provide the data for the battery capacity estimation. For estimation, a weighted voltage relaxation model, containing two parallel resistor–capacitor (RC) components, is established. Its parameters are then optimized using the beetle antenna search algorithm with the approximate OCV range obtained in the test and an early voltage relaxation curve. The results of the experiments show that the proposed model and algorithm can accurately estimate the OCV, and the capacity estimation can be quickly realized in half an hour while limiting inaccuracy to less than 3%.