An Adaptive GPR-Based Multidisciplinary Design Optimization of Structural and Control Parameters of Intelligent Bus for Rollover Stability

Tingting Wang, Xu Shao, Dongchen Qin, Kun Huang, Mingkuan Yao and Yuechen Duan ()
Additional contact information
Tingting Wang: School of Mechanical and Power Engineering, Zhegzhou University, Zhengzhou 450001, China
Xu Shao: School of Mechanical and Power Engineering, Zhegzhou University, Zhengzhou 450001, China
Dongchen Qin: School of Mechanical and Power Engineering, Zhegzhou University, Zhengzhou 450001, China
Kun Huang: Zhengzhou Yutong Group Co., Ltd., Zhengzhou 450000, China
Mingkuan Yao: School of Mechanical and Power Engineering, Zhegzhou University, Zhengzhou 450001, China
Yuechen Duan: School of Mechanical and Power Engineering, Zhegzhou University, Zhengzhou 450001, China

Mathematics, 2025, vol. 13, issue 5, 1-35

Abstract: Considering the influence of high-speed obstacle avoidance trajectory in the optimization design stage of intelligent bus aerodynamic shape. A collaborative optimization method aiming at aerodynamic structure and trajectory control system for intelligent bus rollover stability is proposed to reduce the interference of lateral aerodynamic load caused by large bus side area on driving stability and improve the rollover safety of intelligent bus in high-speed obstacle avoidance process. At the conceptual design stage, a multidisciplinary co-design optimization frame of aerodynamics/dynamics/control is built, and an adaptive Gaussian Process Regression approximate modeling method is proposed to establish an approximate model of high-precision and high-efficiency rollover evaluation index with rollover stability as the optimization objective and obstacle avoidance safety and resistance to crosswind interference as constraints. Taking rollover stability and obstacle avoidance safety as the optimization objectives, the integrated design of static structural parameters and dynamic control parameters of intelligent buses is carried out. The results show that the proposed MDO method can obtain the aerodynamic shape of the vehicle body with low crosswind sensitivity and a safe and stable obstacle avoidance trajectory. Compared with the initial trajectory, the peak lateral load transfer rate during the obstacle avoidance process decreases by 33.91%, which significantly reduces the risk of rollover. Compared with the traditional serial optimization method, the proposed co-design optimization method has obvious advantages and can further improve the driving safety performance of intelligent buses.

Keywords: intelligent bus; multidisciplinary design optimization; adaptive Gaussian process regression; rollover stability; trajectory planning; aerodynamic/vehicle dynamic/control coupling (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/13/5/782/pdf (application/pdf)
https://www.mdpi.com/2227-7390/13/5/782/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:13:y:2025:i:5:p:782-:d:1600728

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().