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020 _a9783658369927
024 7 _a10.1007/978-3-658-36992-7
_2doi
040 _bspa
_cES-MaUEC
_dES-MaUEC
050 4 _aTL220
_b2022 EB
100 1 _aShen, Tunan
_eautor
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_9685409
245 1 0 _aDiagnosis of the Powertrain Systems for Autonomous Electric Vehicles
_cby Tunan Shen
250 _a1st edition 2022
264 1 _aWiesbaden
_bSpringer International Publishing
_c2022
300 _a1 recurso en línea (XXXII, 120 páginas)
_b61 ilustraciones, 4 ilustraciones a color
336 _atexto
_btxt
_2rdacontent
337 _aelectrónico
_bc
_2rdamedia
338 _arecurso electrónico
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
490 0 _aWissenschaftliche Reihe Fahrzeugtechnik Universität Stuttgart
_x2567-0352
505 0 _aBackground and State of the Art -- Diagnosis of Electrical Faults in Electric Machines -- Diagnosis of Mechanical Faults in Electric Machines.
520 _aTunan Shen aims to increase the availability of powertrain systems for autonomous electric vehicles by improving the diagnostic capability for critical faults. Following the fault analysis of powertrain systems in battery electric vehicles, the focus is on the electrical and mechanical faults of the electric machine. A multi-level diagnostic approach is proposed, which consists of multiple diagnostic models, such as a physical model, a data-based anomaly detection model, and a neural network model. To improve the overall diagnostic capability, a decision making function is designed to derive a comprehensive decision from the predictions of various operating points and different models. Contents Background and State of the Art Diagnosis of Electrical Faults in Electric Machines Diagnosis of Mechanical Faults in Electric Machines Target Groups Researchers and students of mechanical engineering, especially automotive powertrains in electric vehicles Research and development engineers in this field About the Author Tunan Shen did his PhD project at the Institute of Automotive Engineering (IFS), University of Stuttgart, Germany. Currently he is Software Developer for Cross Domain Computing Solutions at a German automotive supplier.
988 _aSpringer_Engineering_2022
650 7 _2embne
_9153370
_aAutomóviles eléctricos
776 0 8 _iPrinted edition:
_z9783658369910
776 0 8 _iPrinted edition:
_z9783658369934
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-658-36992-7
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE
998 _b11/2022
_dz
_eb
_zSI