Cite
A novel lithium-ion battery state of charge estimation method based on the fusion of neural network and equivalent circuit models.
MLA
Tang, Aihua, et al. “A Novel Lithium-Ion Battery State of Charge Estimation Method Based on the Fusion of Neural Network and Equivalent Circuit Models.” Applied Energy, vol. 348, Oct. 2023, p. N.PAG. EBSCOhost, https://doi.org/10.1016/j.apenergy.2023.121578.
APA
Tang, A., Huang, Y., Liu, S., Yu, Q., Shen, W., & Xiong, R. (2023). A novel lithium-ion battery state of charge estimation method based on the fusion of neural network and equivalent circuit models. Applied Energy, 348, N.PAG. https://doi.org/10.1016/j.apenergy.2023.121578
Chicago
Tang, Aihua, Yukun Huang, Shangmei Liu, Quanqing Yu, Weixiang Shen, and Rui Xiong. 2023. “A Novel Lithium-Ion Battery State of Charge Estimation Method Based on the Fusion of Neural Network and Equivalent Circuit Models.” Applied Energy 348 (October): N.PAG. doi:10.1016/j.apenergy.2023.121578.