Shrivastava, Prashant and Soon, Tey Kok and Idris, Mohd Yamani Idna Bin and Mekhilef, Saad (2020) Combined SOC and SOE estimation of Lithium-ion battery for electric vehicle applications. In: 2020 IEEE Energy Conversion Congress and Exposition (ECCE), 10-15 October 2020, Detroit, MI.
Full text not available from this repository.Abstract
To optimize the energy storage management system of an electric vehicle (xEVs), the accurate monitoring of battery states are needed. In this paper, the simple combined state of charge (SOC) and state of energy (SOE) estimation method is proposed. By using this method, the battery SOC and SOE both can be estimated at a low cost of computational complexity. The relationship between battery SOC and SOE for commercial lithium nickel cobalt chemistry battery is determined and validated under different operating conditions. Experimental results show that the proposed method can effectively estimate the SOC and SOE of the battery under different dynamic operating conditions with high accuracy. The recorded RMSE of SOC and SOE is always less than 1.6 % under all considered operating conditions. The simplicity of the proposed SOC and SOE estimation method helps to reduce the computational burden to the processor used in BMS, and therefore it is suitably implemented in xEV applications.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Funders: | Office of Naval Research (N62909-18-1-2030), Office of Naval Research (IF011-2018) |
| Additional Information: | 12th Annual IEEE Energy Conversion Congress and Exposition (IEEE ECCE), Detroit, MI, OCT 10-15, 2020 |
| Uncontrolled Keywords: | State of charge; State of energy; Lithium-ion battery; Kalman filter; Battery management system |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Computer Science & Information Technology Faculty of Engineering > Department of Electrical Engineering |
| Depositing User: | Ms Zaharah Ramly |
| Date Deposited: | 14 Apr 2023 03:27 |
| Last Modified: | 14 Apr 2023 03:27 |
| URI: | http://eprints.um.edu.my/id/eprint/37180 |
Actions (login required)
 |
View Item |
