Comfort Assessment and Optimization Based on FE Simulation for High-Speed Train Seats: Comparison with Different Design Parameters

• Published in: Sustainability Vol. 14; no. 22; p. 15185
• Main Authors: Huang, Shufang, Sun, Dayan, Zhang, Liang, Zhou, Jiahao, Wang, Zhihui
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.11.2022
• Subjects: CAE; Comfort; Computer aided engineering; Computer applications; Cushions; Design; Design parameters; Experiments; High speed trains; Inclination angle; Locomotives; Mathematical models; Optimization; Passengers; Pressure; Pressure distribution; Questionnaires; Railroad accidents & safety; Regression analysis; Seats; Sensors; Simulation; Software; Stiffness; China; United States > US
• ISSN: 2071-1050; 2071-1050
• DOI: 10.3390/su142215185

Nowadays, riding comfort is more significant than before for evaluating the quality of high–speed railways and sitting is the most common posture for its passengers. This study aimed to analyze and optimize the pressure distribution and sitting comfort of second–class seats with different design parameters. Firstly, 21 pressure features were calculated after the field sitting tests conducted on a CRH Train. The subjective comfort was quantified as a linear combination of 6 pressure features in 21, which were selected using stepwise regression analysis (R2 = 0.684). A seat-human finite element model was established using THUMS for a human body and MAT_57 for the seat foam. Finally, this study analyzed the effects of foam and seat angles on interface pressure distribution and comfort ratings. The set of design parameters with the highest comfort was selected from 12 free combinations. The results show that the seat foam with less stiffness may not improve sitting comfort due to the asymmetry of the seat frame. Moreover, appropriately increasing the stiffness of the cushion and backrest will not lead to a decrease in subjective feelings and the pressure distribution becomes more reasonable as the inclination angle increases within 10 degrees. The final optimization increases the computational comfort of the seat-human model by 6.5 in a −50 to 50 scale.