Prediction Methods and Evaluation of the Fatigue Life for Automotive Structural Components
Language: English
Published by Elsevier Science Jun 2025, 2025
- Softcover
- New
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Neuware - Automotive structural components are an important component that affects the performance of the entire vehicle. The light weight of automotive structural components is one of the sustainable solutions to energy and environmental issues, and the development technology of its core components and vehicle performance evaluation technology are its key development directions. To gradually replace traditional cars on a large scale, electric vehicles need to address the durability and reliability issues of the entire vehicle and key components. Prediction Methods and Evaluation of the Fatigue Life for Automotive Structural Components helps readers understand how they can do this.
Seller Inventory # 9780443302350
- Title
- Prediction Methods and Evaluation of the Fatigue Life for Automotive Structural Components
- Author
- Xiaolan Wang
- Publisher
- Elsevier Science Jun 2025
- Publication year
- 2025
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 0443302359
- ISBN 13
- 9780443302350
- Item weight
- 816 grams
- Dimensions
- 234x191x20 mm
- Fatigue life prediction and evaluation for automotive structural components are provided, based on product forward design
- Covers prediction methods of fatigue life for different structural components
- Readers gain an understanding of both the theoretical and practical aspects of structural components fatigue life
"Synopsis" may belong to another edition of this title.
About the Author
Professor Yu Fang is currently a Professor at the School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, China. He received his PhD from Harbin Institute of Technology, China, in 2008
Dr Xu Wang received her PhD degree in pattern recognition and intelligent system in 2013 from Donghua University, China. She is currently a lecturer at the school of mechanical and automotive engineering, Shanghai University of Engineering Science, China. Her research interests include prediction methods, evolutionary computation, optimization methods, deep learning and their applications
Dr Xiaolan Wang received her M.S. and Ph.D. degrees in vehicle application engineering from Jilin University, Changchun, China, in 2009 and 2012, respectively. She is currently a lecturer with the School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai, China. Her active research interests include intelligent vehicles, driving assistance systems, and driver behaviour
"About the title" may belong to another edition of this title.
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