Diagnosis of the Powertrain Systems for Autonomous Electric Vehicles / Wissenschaftliche Reihe Fahrzeugtechnik Universität Stuttgart (PDF)
(Sprache: Englisch)
Tunan 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...
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Produktinformationen zu „Diagnosis of the Powertrain Systems for Autonomous Electric Vehicles / Wissenschaftliche Reihe Fahrzeugtechnik Universität Stuttgart (PDF)“
Tunan 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
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.
Autoren-Porträt von Tunan Shen
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.
Bibliographische Angaben
- Autor: Tunan Shen
- 2022, 1st ed. 2022, 120 Seiten, Englisch
- Verlag: Springer Fachmedien Wiesbaden
- ISBN-10: 3658369922
- ISBN-13: 9783658369927
- Erscheinungsdatum: 02.03.2022
Abhängig von Bildschirmgrösse und eingestellter Schriftgrösse kann die Seitenzahl auf Ihrem Lesegerät variieren.
eBook Informationen
- Dateiformat: PDF
- Grösse: 3.65 MB
- Ohne Kopierschutz
- Vorlesefunktion
Sprache:
Englisch
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