Electric Vehicle Battery States Estimation During Charging Process by NARX Neural Network
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Computer Science Applications,Energy Engineering and Power Technology,Control and Systems Engineering
Link
https://link.springer.com/content/pdf/10.1007/s40313-023-01038-w.pdf
Reference28 articles.
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3. Chaoui, H., Ibe-Ekeocha, C. C., & Gualous, H. (2017). Aging prediction and state of charge estimation of a lifepo4 battery using input time-delayed neural networks. Electric Power Systems Research, 146, 189–197. https://doi.org/10.1016/j.epsr.2017.01.032
4. Chen, S., & Billings, S. A. (1989). Representations of non-linear systems: The narmax model. International Journal of Control, 49(3), 1013–1032. https://doi.org/10.1080/00207178908559683
5. Chen, S., & Billings, S. A. (1992). Neural networks for nonlinear dynamic system modelling and identification. International Journal of Control, 56(2), 319–346. https://doi.org/10.1080/00207179208934317
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