Abstract
Prognosis is a relatively new concept that aims detecting system’s defect before it occurs or at a very small scale. The concept began in the field of medicine; then, several engineering domains took advantage of it. Prognosis and health assessment in critical applications like hybrid electrical vehicles are very important to assure their reliability, availability, safety, and proper operation. Some researches addressed prognostic techniques; while others applied prognosis on mechanical components in hybrid electrical vehicles like bearing. In this paper the prognostic technique, hidden Markov model (HMM), will be presented; then, this model will be applied on a 12 poles permanent magnet synchronous machine (PMSM) of a hybrid electric vehicle (HEV). The aim of the prognostic model is to identify the presence of a machine’s fault in its early stage.
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This work is co-funded by European Union and Normandy Region. Europe is involved in Normandy through the European Funds for Regional Development.
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Ginzarly, R., Hoblos, G., Moubayed, N. (2022). Hidden Markov Model-Based Failure Prognosis for Permanent Magnet Synchronous Machine. In: Zattoni, E., Simani, S., Conte, G. (eds) 15th European Workshop on Advanced Control and Diagnosis (ACD 2019). ACD 2019 2018. Lecture Notes in Control and Information Sciences - Proceedings. Springer, Cham. https://doi.org/10.1007/978-3-030-85318-1_35
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DOI: https://doi.org/10.1007/978-3-030-85318-1_35
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