Prognostics for Lithium-ion batteries for electric Vertical Take-off and Landing aircraft using data-driven machine learning

Author:

Mitici Mihaela,Hennink Birgitte,Pavel Marilena,Dong Jianning

Publisher

Elsevier BV

Subject

Artificial Intelligence,General Energy,Engineering (miscellaneous)

Reference51 articles.

1. Polaczyk N, Trombino E, Wei P, Mitici M. A review of current technology and research in urban on-demand air mobility applications. In: 8th biennial autonomous VTOL technical meeting and 6th annual electric VTOL symposium. 2019, p. 333–43.

2. Early prediction of battery lifetime via a machine learning based framework;Fei;Energy,2021

3. Battery health monitoring for commercialized electric vehicle batteries: Lithium-ion;Shah,2019

4. A review of the state of health for lithium-ion batteries: Research status and suggestions;Tian;J Clean Prod,2020

5. Performance validation of electric vehicle’s battery management system under state of charge estimation for lithium-ion battery;Khalid,2018

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