A linear recursive state of power estimation method based on fusion model of voltage and state of charge limitations.

Li, Bowen; Wang, Shunli; Fernandez, Carlos; Yu, Chunmei; Xia, Lili; Fan, Yongcun

Abstract

As the main candidate of energy storage system for electric vehicles and hybrid electric vehicles, lithium-ion battery has attracted extensive attention. The working characteristics of the battery under dynamic stress stimulation are complex and changeable. To solve the problem of high-precision state of power estimation, a fusion model based on adaptive forgetting factor recursive least squares identification and voltage and charge state constraints was proposed, and a continuous discharge state of power analysis model for lithium-ion batteries was established. The adaptive forgetting factor recursive least square method based on battery model provides accurate and reliable online parameter identification feedback. The results show that the accuracy error of online parameter identification is less than 0.02V; the combination of the linear recursive algorithm of state of power analysis and the fusion model of voltage and current limit makes the power state estimation more reliable and accurate. The results show that when the battery is t=10s, the peak discharge power error is less than 80W.

Citation

LI, B., WANG, S., FERNANDEZ, C., YU, C., XIA, L. and FAN, Y. 2021. A linear recursive state of power estimation method based on fusion model of voltage and state of charge limitations. Journal of energy storage [online], 40, article ID 102583. Available from: https://doi.org/10.1016/j.est.2021.102583

• Journal Article Type: Article
• Acceptance Date: Apr 12, 2021
• Online Publication Date: May 24, 2021
• Publication Date: Aug 31, 2021
• Deposit Date: Jun 10, 2021
• Publicly Available Date: May 25, 2022
• Journal: Journal of energy storage
• Print ISSN: 2352-152X
• Electronic ISSN: 2352-1538
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 40
• Article Number: 102583
• DOI: https://doi.org/10.1016/j.est.2021.102583
• Keywords: Lithium ion batteries; Electric vehicles; State of power; Fusion model; Adaptive forgetting factor; Recursive least square algorithm; Linear recursion algorithm
• Public URL: https://rgu-repository.worktribe.com/output/1346996