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Prediction Methods and Evaluation of the Fatigue Life for Automotive Structural Components
- 1st Edition - June 1, 2025
- Authors: Xintian Liu, Yu Fang, Xu Wang, Xiaolan Wang
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 3 0 2 3 5 - 0
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 3 0 2 3 6 - 7
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… Read more
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Request a sales quoteAutomotive 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
- 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
Researchers and professional technicians engaged in fields such as vehicle engineering, data analysis and processing, materials science and engineering
1. Classification and characteristics of automotive structural components
2. The characteristics of metals and non-metallic materials
3. The strength properties of structural components
4. The principles and characteristic of load
5. Fatigue life prediction methods
6. Theoretical and experimental standardization of fatigue life
7. Fatigue reliability analysis and evaluation
8. The correlation between quality characteristics and fatigue life
9. Conclusions and future outlook
2. The characteristics of metals and non-metallic materials
3. The strength properties of structural components
4. The principles and characteristic of load
5. Fatigue life prediction methods
6. Theoretical and experimental standardization of fatigue life
7. Fatigue reliability analysis and evaluation
8. The correlation between quality characteristics and fatigue life
9. Conclusions and future outlook
- No. of pages: 400
- Language: English
- Edition: 1
- Published: June 1, 2025
- Imprint: Elsevier
- Paperback ISBN: 9780443302350
- eBook ISBN: 9780443302367
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Xintian Liu
Dr Xintian Liu is the Vice Dean of the School of Mechanical and Automotive Engineering at Shanghai University of Engineering Science, China, and also serves as a member of the Modern Management Branch of the China Society of Automotive Engineering and the Automotive Reliability Professional Committee of Shanghai Society of Automotive Engineering. Currently, he is mainly engaged in research in automotive reliability engineering, fatigue life prediction and evaluation, structural system uncertainty, and functional safety of intelligent vehicle systems. He has published more than 100 papers as the first or corresponding author
Affiliations and expertise
Shanghai University of Engineering Science, Beijing, ChinaYF
Yu Fang
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
Affiliations and expertise
Shanghai University of Engineering Science, Beijing, ChinaXW
Xu Wang
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
Affiliations and expertise
Shanghai University of Engineering Science, Beijing, ChinaXW
Xiaolan Wang
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
Affiliations and expertise
Shanghai University of Engineering Science, Beijing, China