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pro vyhledávání: '"Karam D. Kallu"'
Autor:
Muhammad U. Ali, Hafiz F. Khan, Haris Masood, Karam D. Kallu, Malik M. Ibrahim, Amad Zafar, Semin Oh, Sangil Kim
Publikováno v:
Energy Science & Engineering, Vol 10, Iss 7, Pp 2333-2347 (2022)
Abstract This study presents a data‐driven approach in conjunction with an adaptive extended Kalman filter (AEKF) to estimate lithium‐ion batteries' state of charge (SOC) online. The Thevenin battery model is used to evaluate the effects using ba
Externí odkaz:
https://doaj.org/article/1177d1fadd2e47d89075809e23394bf9
