Fan, Y., Yang, H., Ye, C., Yang, W., Panchal, S., Fraser, R., Fowler, M., & Dong, H. (2025). State of health estimation of lithium-ion batteries based on the fusion of aging feature extraction and SSA-ELM machine learning algorithms. Ionics: International Journal of Ionics – The Science and Technology of Ionic Motion, 31(8), 7897-7915. https://doi.org/10.1007/s11581-025-06454-3

FAN, Yiwei, YANG, Haonan, YE, Congjin, YANG, Wen, PANCHAL, Satyam, FRASER, Roydon, FOWLER, Michael and DONG, Huifang, 2025. State of health estimation of lithium-ion batteries based on the fusion of aging feature extraction and SSA-ELM machine learning algorithms. Ionics: International Journal of Ionics – The Science and Technology of Ionic Motion. 1 August 2025. Vol. 31, no. 8, p. 7897-7915. DOI 10.1007/s11581-025-06454-3.

Fan, Y., H. Yang, C. Ye, W. Yang, S. Panchal, R. Fraser, M. Fowler, and H. Dong. “State of Health Estimation of Lithium-Ion Batteries Based on the Fusion of Aging Feature Extraction and SSA-ELM Machine Learning Algorithms”. Ionics: International Journal of Ionics – The Science and Technology of Ionic Motion, vol. 31, no. 8, Aug. 2025, pp. 7897-15, https://doi.org/10.1007/s11581-025-06454-3.

Fan, Yiwei/Yang, Haonan/Ye, Congjin/Yang, Wen/Panchal, Satyam/Fraser, Roydon et al.: State of health estimation of lithium-ion batteries based on the fusion of aging feature extraction and SSA-ELM machine learning algorithms, Ionics: International Journal of Ionics – The Science and Technology of Ionic Motion 2025, 7897-7915.

Fan, Y., Yang, H., Ye, C., Yang, W., Panchal, S., Fraser, R., Fowler, M. and Dong, H. (2025), “State of health estimation of lithium-ion batteries based on the fusion of aging feature extraction and SSA-ELM machine learning algorithms”, Ionics: International Journal of Ionics – The Science and Technology of Ionic Motion, Vol. 31 No. 8, pp. 7897-7915.