Joint state of charge and state of energy estimation of special aircraft lithium-ion batteries by optimized genetic marginalization-extended particle filtering.

Wang, Shunli; Luo, Tao; Hai, Nan; Blaabjerg, Frede; Fernandez, Carlos

Abstract

With the continuous development and widespread application of special aircraft, accurately estimating the performance and status of battery systems has become crucial. This paper focuses on the joint estimation of State of Charge (SOC) and State of Energy (SOE) under complex operating conditions using the proposed Genetic Marginalization-Extended Particle Filtering (GM-EPF) algorithm with the Dynamic Forgetting Factor Recursive Least Square (DFFRLS) algorithm. To enhance estimation accuracy, the paper first introduces DFFRLS algorithm for real-time model parameter recognition. Then, the GM-EPF algorithm is applied to combine the dynamically updated parameters from DFFRLS with particle filtering techniques, further improving the precision and robustness of the SOC and SOE estimations. The joint estimation algorithm of SOC and SOE based on DFFRLS ensures stable recognition with error control within 5.6 %. The joint estimation algorithm of SOC and SOE based on GM-EPF reduced the Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) of battery SOC estimation by 82.91 % and 87.56 %, respectively, and the MAE and RMSE of SOE estimation by 84.61 % and 85.53 %, respectively. The joint estimation method of SOC and SOE for lithium-ion batteries in special aircraft based on composite model optimization has improved the controllability and safety of lithium-ion batteries as power sources in the field of special aircraft.

Citation

WANG, S., LUO, T., HAI, N., BLAABJERG, F. and FERNANDEZ, C. [2025]. Joint state of charge and state of energy estimation of special aircraft lithium-ion batteries by optimized genetic marginalization-extended particle filtering. Journal of energy storage [online], 115, article number 116001. Available from: https://doi.org/10.1016/j.est.2025.116001

• Journal Article Type: Article
• Acceptance Date: Feb 23, 2025
• Online Publication Date: Mar 3, 2025
• Publication Date: Apr 15, 2025
• Deposit Date: Mar 3, 2025
• Publicly Available Date: Mar 4, 2026
• Journal: Journal of energy storage
• Print ISSN: 2352-152X
• Electronic ISSN: 2352-1538
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 115
• Article Number: 116001
• DOI: https://doi.org/10.1016/j.est.2025.116001
• Keywords: Lithium-ion batteries; Genetic marginalization-extended particle filtering; Dynamic forgetting factor recursive least square; State of charge; State of energy
• Public URL: https://rgu-repository.worktribe.com/output/2741646