Particle-Filtering-Based Prognostics for the State of Maximum Power Available in Lithium-Ion Batteries at Electromobility Applications.

MLA

Diaz, Cesar, et al. “Particle-Filtering-Based Prognostics for the State of Maximum Power Available in Lithium-Ion Batteries at Electromobility Applications.” IEEE Transactions on Vehicular Technology, vol. 69, no. 7, July 2020, pp. 7187–200. EBSCOhost, https://doi.org/10.1109/TVT.2020.2993949.

APA

Diaz, C., Quintero, V., Perez, A., Jaramillo, F., Burgos-Mellado, C., Rozas, H., Orchard, M. E., Saez, D., & Cardenas, R. (2020). Particle-Filtering-Based Prognostics for the State of Maximum Power Available in Lithium-Ion Batteries at Electromobility Applications. IEEE Transactions on Vehicular Technology, 69(7), 7187–7200. https://doi.org/10.1109/TVT.2020.2993949

Chicago

Diaz, Cesar, Vanessa Quintero, Aramis Perez, Francisco Jaramillo, Claudio Burgos-Mellado, Heraldo Rozas, Marcos E. Orchard, Doris Saez, and Roberto Cardenas. 2020. “Particle-Filtering-Based Prognostics for the State of Maximum Power Available in Lithium-Ion Batteries at Electromobility Applications.” IEEE Transactions on Vehicular Technology 69 (7): 7187–7200. doi:10.1109/TVT.2020.2993949.