Data-Driven Modelling for Health Estimation of High-Voltage Battery Systems
Published in Chalmers Open Digital Repository, 2020
Short abstract - An accurate determination of battery health and life prediction is essential to ensure reliable, efficient and durable battery performance along the full lifetime of a vehicle. This thesis builds on achievements with data-driven modelling to determine the behaviour of complex dynamical systems through machine learning techniques. The conducted survey over a range of model techniques, from standard baseline up to state-of-the-art approaches, indicates the power and flexibility of data-driven models in the directions of per vehicle and fleet use cases.
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