Diagnosis of the Powertrain Systems for Autonomous Electric Vehicles

Tunan Shen

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English

Springer Vieweg
03 March 2022

Engines & power transmission; Electrical engineering; Automotive technology & trades

Series: Wissenschaftliche Reihe Fahrzeugtechnik Universität Stuttgart

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.

By: Tunan Shen
Imprint: Springer Vieweg
Country of Publication: Germany
Edition: 1st ed. 2022
Dimensions: Height: 210mm, Width: 148mm,
Weight: 208g
ISBN: 9783658369910
ISBN 10: 3658369914
Series: Wissenschaftliche Reihe Fahrzeugtechnik Universität Stuttgart
Pages: 120
Publication Date: 03 March 2022
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

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.