Diagnosis of the Powertrain Systems for Autonomous Electric Vehicles (eBook)

Tunan Shen (Autor)

eBook Download: PDF

2022 | 1st ed. 2022
XXXII, 120 Seiten
Springer Fachmedien Wiesbaden (Verlag)
978-3-658-36992-7 (ISBN)

Infos

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.

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.

Produkt-Details

• Erscheint lt. Verlag: 2.3.2022
• Reihe/Serie: Wissenschaftliche Reihe Fahrzeugtechnik Universität Stuttgart
• Reihe/Serie: Wissenschaftliche Reihe Fahrzeugtechnik Universität Stuttgart
• Zusatzinfo: XXXII, 120 p. 61 illus., 4 illus. in color.
• Sprache: englisch
• Themenwelt: Technik ► Bauwesen
• Themenwelt: Technik ► Maschinenbau
• Schlagworte: Autonomous electric vehicle • Bearing faults • Data-based diagnosis • Machine faults • Multi-stage diagnosis • Powertrain System • Predictive diagnosis
• ISBN-10: 3-658-36992-2 / 3658369922
• ISBN-13: 978-3-658-36992-7 / 9783658369927