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Diagnosis of the powertrain systems for autonomous electric vehicles

Record Type:	Electronic resources : Monograph/item
Title/Author:	Diagnosis of the powertrain systems for autonomous electric vehiclesby Tunan Shen.
Author:	Shen, Tunan.
Published:	Wiesbaden :Springer Fachmedien Wiesbaden :2022.
Description:	xxxii, 120 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Electric vehiclesPower trains.
Online resource:	https://doi.org/10.1007/978-3-658-36992-7
ISBN:	9783658369927$q(electronic bk.)

Diagnosis of the powertrain systems for autonomous electric vehicles
Shen, Tunan.

Diagnosis of the powertrain systems for autonomous electric vehicles[electronic resource] /by Tunan Shen. - Wiesbaden :Springer Fachmedien Wiesbaden :2022. - xxxii, 120 p. :ill., digital ;24 cm. - Wissenschaftliche Reihe Fahrzeugtechnik Universitat Stuttgart,2567-0352. - Wissenschaftliche Reihe Fahrzeugtechnik Universitat Stuttgart..

Background and State of the Art -- Diagnosis of Electrical Faults in Electric Machines -- Diagnosis of Mechanical Faults in Electric Machines.

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 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.

ISBN: 9783658369927$q(electronic bk.)

Standard No.: 10.1007/978-3-658-36992-7doiSubjects--Topical Terms:

917444
Electric vehicles
--Power trains.

LC Class. No.: TL220 / .S54 2022

Dewey Class. No.: 629.2293

Diagnosis of the powertrain systems for autonomous electric vehicles
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