Projecten per jaar
Samenvatting
As the automotive industry undergoes a major shift to electric propulsion, reliable assessment of battery health and potential safety issues is critical. This review covers advances in sensor technology, from mechanical and gas sensors to ultrasonic imaging techniques that provide insight into the complex structures and dynamics of lithium-ion batteries. In addition, we explore the integration of physics-guided machine learning methods with multi-sensor systems to improve the accuracy of battery modeling and monitoring. Challenges and opportunities in prototyping and scaling these multi-sensor systems are discussed, highlighting both current limitations and future potential. The purpose of this study is to provide a comprehensive overview of the current status, challenges, and future directions of combining sensors with physically guided methods for future vehicle battery management systems.
Originele taal-2 | English |
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Artikelnummer | 44 |
Aantal pagina's | 15 |
Tijdschrift | Communications Engineering |
Volume | 4 |
Nummer van het tijdschrift | 1 |
DOI's | |
Status | Published - dec. 2025 |
Bibliografische nota
Publisher Copyright:© The Author(s) 2025.
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EUAR141: PHOENIX: Het bouwen van betrouwbaardere en beter presterende batterijen door sensoren en zelfherstellende functionaliteiten in te bedden om degradatie te detecteren en schade te herstellen via een geavanceerd batterijbeheersysteem
Berecibar, M., Messagie, M., Dermenci, K. B., Lavigne Philippot, M., de Hoog, J. & Boursot, I.
1/05/23 → 30/04/27
Project: Toegepast
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EUAR34: H2020: RIA: Spartacus: Ruimtelijk opgeloste akoestische, mechanische en ultrasone detectie voor slimme batterijen
Van Mierlo, J., Berecibar, M., De Sutter, L. & Boursot, I.
1/09/20 → 29/02/24
Project: Toegepast