Cite
Fast capacity prediction of lithium-ion batteries using aging mechanism-informed bidirectional long short-term memory network.
MLA
Xu, Xiaodong, et al. “Fast Capacity Prediction of Lithium-Ion Batteries Using Aging Mechanism-Informed Bidirectional Long Short-Term Memory Network.” Reliability Engineering & System Safety, vol. 234, June 2023, p. N.PAG. EBSCOhost, https://doi.org/10.1016/j.ress.2023.109185.
APA
Xu, X., Tang, S., Han, X., Lu, L., Wu, Y., Yu, C., Sun, X., Xie, J., Feng, X., & Ouyang, M. (2023). Fast capacity prediction of lithium-ion batteries using aging mechanism-informed bidirectional long short-term memory network. Reliability Engineering & System Safety, 234, N.PAG. https://doi.org/10.1016/j.ress.2023.109185
Chicago
Xu, Xiaodong, Shengjin Tang, Xuebing Han, Languang Lu, Yu Wu, Chuanqiang Yu, Xiaoyan Sun, Jian Xie, Xuning Feng, and Minggao Ouyang. 2023. “Fast Capacity Prediction of Lithium-Ion Batteries Using Aging Mechanism-Informed Bidirectional Long Short-Term Memory Network.” Reliability Engineering & System Safety 234 (June): N.PAG. doi:10.1016/j.ress.2023.109185.