Electric Vehicles Lithium-Polymer Ion Battery Dynamic Behaviour Charging Identification and Modelling Scheme
Journal article
Makeen, P., Ghali, H.A., Memon, S., Duan, F. and Besada, P. (2023). Electric Vehicles Lithium-Polymer Ion Battery Dynamic Behaviour Charging Identification and Modelling Scheme. Journal of Dynamics, Monitoring and Diagnostics. https://doi.org/10.37965/jdmd.2023.398
| Authors | Makeen, P., Ghali, H.A., Memon, S., Duan, F. and Besada, P. |
|---|---|
| Abstract | Lithium-ion batteries are considered the substantial electrical storage element for electric vehicles (EVs). The battery model is the basis of battery monitoring, efficient charging, and safety management. Non-linear modelling is the key to representing the battery and its dynamic internal parameters and performance. This paper proposes a smart scheme to model the lithium-polymer ion battery while monitoring its present charging current and terminal voltage at various ambient conditions (temperature and relative humidity). Firstly, the suggested framework investigated the impact of temperature and relative humidity on the charging process using the constant current-constant voltage (CC-CV) charging protocol. This will be followed by monitoring the battery at the surrounding operating temperature and relative humidity. Hence, efficient non-linear modelling of the EV battery dynamic behaviour using the Hammerstein-Wiener (H-W) model is implemented. The H-W model is considered a black box model that can represent the battery without any mathematical equivalent circuit model which reduces the computation complexity. Finally, the model beholds the boundaries of the charging process that not affecting on the lifetime of the battery. Several dynamic models are applied and tested experimentally to ensure the effectiveness of the proposed scheme under various ambient conditions where the temperature is fixed at 40°C and the relative humidity (RH) at 35%, 52%, and 70%. The best fit using the H-W model reached 91.83% to describe the dynamic behaviour of the battery with a maximum percentage of error 0.1V which is in good agreement with the literature survey. Besides, the model has been scaled up to represent a real EV and expressed the significance of the proposed H-W model. |
| Year | 2023 |
| Journal | Journal of Dynamics, Monitoring and Diagnostics |
| Publisher | Intelligence Science and Technology Press |
| ISSN | 2831-5308 |
| Digital Object Identifier (DOI) | https://doi.org/10.37965/jdmd.2023.398 |
| Web address (URL) | https://doi.org/10.37965/jdmd.2023.398 |
| Publication dates | |
| Online | 03 Aug 2023 |
| Publication process dates | |
| Deposited | 04 Aug 2023 |
| Publisher's version | License File Access Level Open |
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| ID398-EV+Lithium-Polymer+Ion+Battery+Dynamic+Behaviour+Charging+Identification+and+Modelling+Scheme【final】 (1).pdf | ||
| License: CC BY 4.0 | ||
| File access level: Open | ||
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