A review of battery state of health estimation methods: hybrid electric vehicle challenges

Noura, Nassim, Boulon, Loïc et Jemeï, Samir (2020). A review of battery state of health estimation methods: hybrid electric vehicle challenges. World Electric Vehicle Journal, 11 (4). p. 66. ISSN 2032-6653 DOI 10.3390/wevj11040066

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Résumé

To cope with the new transportation challenges and to ensure the safety and durability of electric vehicles and hybrid electric vehicles, high performance and reliable battery health management systems are required. The Battery State of Health (SOH) provides critical information about its performances, its lifetime and allows a better energy management in hybrid systems. Several research studies have provided different methods that estimate the battery SOH. Yet, not all these methods meet the requirement of automotive real-time applications. The real time estimation of battery SOH is important regarding battery fault diagnosis. Moreover, being able to estimate the SOH in real time ensure an accurate State of Charge and State of Power estimation for the battery, which are critical states in hybrid applications. This study provides a review of the main battery SOH estimation methods, enlightening their main advantages and pointing out their limitations in terms of real time automotive compatibility and especially hybrid electric applications. Experimental validation of an online and on-board suited SOH estimation method using model-based adaptive filtering is conducted to demonstrate its real-time feasibility and accuracy.

Type de document:	Article
Mots-clés libres:	review online parameter identification recursive least square battery internal resistance
Date de dépôt:	15 mars 2021 18:32
Dernière modification:	15 mars 2021 18:32
Version du document déposé:	Version officielle de l'éditeur
URI:	https://depot-e.uqtr.ca/id/eprint/9514

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