Springer Nature
Model-Based Fault Diagnosis And Fault-Tolerant Control
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MarcaSpringer Nature
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Alia Salah introduces a multi-functional, model-based method for fault detection and identification in automotive electric machines. This approach integrates current vehicle diagnostics to detect faults early, before component failure. It utilizes digital twins and parameter estimation, alongside machine learning classification, to identify fault type and location. Moreover, it incorporates model reference adaptive control for fault-tolerant control, helping to maintain performance and ensure a safe driving experience.
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