State‑of‑charge estimation for lithium‑ion battery based on PNGV model and particle filter algorithm

Yuanfei Geng; Hui Pang; Xiaofei Liu

State‑of‑charge estimation for lithium‑ion battery based on PNGV model and particle filter algorithm

Yuanfei Geng

Hui Pang

Xiaofei Liu

Vol. 22, No. 7, pp. 1154-1164, Jul. 2022

10.1007/s43236-022-00422-0

Abstract

The accurate state-of-charge (SOC) estimation for lithium-ion battery (LIB) cells and packs plays an important role in fulfilling efficient battery management. However, some estimation errors of LIB states and SOC are often encountered when using the conventional battery model and filter algorithms. Thus, this paper explores a SOC estimation method of LIB based on an improved partnership for a new generation of vehicle (PNGV) model and particle filter (PF) algorithm. First, a second-order PNGV model is constructed, and the effect of different SOC interval changes on battery model parameters is considered. Then, the improved PNGV model-based PF algorithm is employed to realize the real-time estimation of battery SOC. Finally, the proposed SOC estimation method is validated under constant current and dynamic urban dynamometer driving schedule (UDDS) conditions. Results show that the improved PNGV model of LIB integration with the PF algorithm can considerably enhance the accuracy of SOC estimation. Compared to the conventional PNGV model-based PF algorithm, the mean absolute error and root mean squared error of SOC estimation errors are, respectively, reduced by approximately 32.7% and 32.5% under the 0.5C rate discharge and UDDS conditions.

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Cite this article

[IEEE Style]

Y. Geng, H. Pang, X. Liu, "State‑of‑charge estimation for lithium‑ion battery based on PNGV model and particle filter algorithm," Journal of Power Electronics, vol. 22, no. 7, pp. 1154-1164, 2022. DOI: 10.1007/s43236-022-00422-0.

[ACM Style]

Yuanfei Geng, Hui Pang, and Xiaofei Liu. 2022. State‑of‑charge estimation for lithium‑ion battery based on PNGV model and particle filter algorithm. Journal of Power Electronics, 22, 7, (2022), 1154-1164. DOI: 10.1007/s43236-022-00422-0.