Big data generation platform for battery faults under real-world variances

Big data generation platform for battery faults under real-world variances

There is an increasing demand for real-time data-driven fault diagnosis of lithium-ion batteries that can predict battery faults at an early stage to avoid safety issues and improve battery reliability. However, such prediction methods require large amounts of data, generally obtained through experi...

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Bibliographic Details
Main Authors: Daniel Luder, Praise Thomas John, Paul Busch, Martin Börner, Wenjiong Cao, Philipp Dechent, Elias Barbers, Stephan Bihn, Lishuo Liu, Xuning Feng, Dirk Uwe Sauer, Weihan Li
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:Green Energy and Intelligent Transportation
Subjects:
Battery
Fault
Safety
Big data
Monte Carlo
Online Access:http://www.sciencedirect.com/science/article/pii/S2773153725000325
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