A novel dynamical model for diagnosis, prognosis and health-aware control of Lithium-ion batteries
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Elsevier BV
Reference14 articles.
1. A review on lithium-ion battery ageing mechanisms and estimations for automotive applications;Barré;Journal of Power Sources,2013
2. Bole, B., Kulkarni, C.S., and Daigle, M.. (2014). Adaptation of an electrochemistry-based li-ion battery model to account for deterioration observed under randomized use. In Annual Conference of the PHM Society, volume 6.
3. Aging aware operation of lithium-ion battery energy storage systems: A review;Collath;Journal of Energy Storage,2022
4. Daigle, M. and Kulkarni, C.S. (2016). End-of-discharge and End-of-life Prediction in Lithium-ion Batteries with Electrochemistry-based Aging Models. doi: 10.2514/6.2016-2132.
5. Halimi, M., Millerioux, G., and Daafouz, J. (2013). Poly-topic Observers for LPV Discrete-Time Systems. In O. Sename, P. Gaspar, and J. Bokor (eds.), Robust Control and Linear Parameter Varying Approaches, volume 437, 97–124. Springer Berlin Heidelberg, Berlin, Heidelberg. doi:10.1007/978-3-642-36110-4.5. Series Title: Lecture Notes in Control and Information Sciences.
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