A novel streamlined particle-unscented Kalman filtering method for the available energy prediction of lithium-ion batteries considering the time-varying temperature-current influence

Autor: Yongcun Fan, Shunli Wang, Chuan-Yun Zou, Liang Zhang, Siyu Jin, Carlos Fernandez

Publikováno v: Zhang, L, Wang, S, Zou, C, Fan, Y, Jin, S & Fernandez, C 2021, ' A novel streamlined particle-unscented Kalman filtering method for the available energy prediction of lithium-ion batteries considering the time-varying temperature-current influence ', International Journal of Energy Research, vol. 45, no. 12, pp. 17858-17877 . https://doi.org/10.1002/er.6930

Effective energy prediction is of great importance for the operational status monitoring of high-power lithium-ion battery packs. It should be embedded in the battery system performance evaluation, energy management, and safety protection. A new Stre

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bf44906fd315f708108b8e2282ec0b01
https://vbn.aau.dk/ws/files/510053933/ZHANG_2021_A_novel_streamlined_particle_AAM_.pdf