An Adaptive GPR-Based Multidisciplinary Design Optimization of Structural and Control Parameters of Intelligent Bus for Rollover Stability
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| Publicado en: | Mathematics vol. 13, no. 5 (2025), p. 782 |
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| Autor principal: | |
| Otros Autores: | , , , , |
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MDPI AG
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| Acceso en línea: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 022 | |a 2227-7390 | ||
| 024 | 7 | |a 10.3390/math13050782 |2 doi | |
| 035 | |a 3176336242 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231533 |2 nlm | ||
| 100 | 1 | |a Wang, Tingting |u School of Mechanical and Power Engineering, Zhegzhou University, Zhengzhou 450001, China; <email>wangtingting@zzu.edu.cn</email> (T.W.); <email>shaoxu4869@gs.zzu.edu.cn</email> (X.S.); <email>dcqin@zzu.edu.cn</email> (D.Q.); <email>yaomingkuan@zzu.edu.cn</email> (M.Y.) | |
| 245 | 1 | |a An Adaptive GPR-Based Multidisciplinary Design Optimization of Structural and Control Parameters of Intelligent Bus for Rollover Stability | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a 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. | |
| 653 | |a Load | ||
| 653 | |a Design optimization | ||
| 653 | |a Rollover | ||
| 653 | |a Co-design | ||
| 653 | |a Public transportation | ||
| 653 | |a Multidisciplinary design optimization | ||
| 653 | |a Dynamic control | ||
| 653 | |a Collaboration | ||
| 653 | |a Lateral loads | ||
| 653 | |a Aerodynamic loads | ||
| 653 | |a Vehicle safety | ||
| 653 | |a Buses | ||
| 653 | |a Systems design | ||
| 653 | |a Aerodynamics | ||
| 653 | |a Crosswinds | ||
| 653 | |a High speed | ||
| 653 | |a Gaussian process | ||
| 653 | |a Wind effects | ||
| 653 | |a Stability | ||
| 653 | |a Attitudes | ||
| 653 | |a Optimization algorithms | ||
| 653 | |a Parameters | ||
| 653 | |a Load transfer | ||
| 653 | |a Trajectory control | ||
| 653 | |a Obstacle avoidance | ||
| 700 | 1 | |a Xu, Shao |u School of Mechanical and Power Engineering, Zhegzhou University, Zhengzhou 450001, China; <email>wangtingting@zzu.edu.cn</email> (T.W.); <email>shaoxu4869@gs.zzu.edu.cn</email> (X.S.); <email>dcqin@zzu.edu.cn</email> (D.Q.); <email>yaomingkuan@zzu.edu.cn</email> (M.Y.) | |
| 700 | 1 | |a Qin, Dongchen |u School of Mechanical and Power Engineering, Zhegzhou University, Zhengzhou 450001, China; <email>wangtingting@zzu.edu.cn</email> (T.W.); <email>shaoxu4869@gs.zzu.edu.cn</email> (X.S.); <email>dcqin@zzu.edu.cn</email> (D.Q.); <email>yaomingkuan@zzu.edu.cn</email> (M.Y.) | |
| 700 | 1 | |a Huang, Kun |u Zhengzhou Yutong Group Co., Ltd., Zhengzhou 450000, China; <email>huangkunb@yutong.com</email> | |
| 700 | 1 | |a Yao, Mingkuan |u School of Mechanical and Power Engineering, Zhegzhou University, Zhengzhou 450001, China; <email>wangtingting@zzu.edu.cn</email> (T.W.); <email>shaoxu4869@gs.zzu.edu.cn</email> (X.S.); <email>dcqin@zzu.edu.cn</email> (D.Q.); <email>yaomingkuan@zzu.edu.cn</email> (M.Y.) | |
| 700 | 1 | |a Duan, Yuechen |u School of Mechanical and Power Engineering, Zhegzhou University, Zhengzhou 450001, China; <email>wangtingting@zzu.edu.cn</email> (T.W.); <email>shaoxu4869@gs.zzu.edu.cn</email> (X.S.); <email>dcqin@zzu.edu.cn</email> (D.Q.); <email>yaomingkuan@zzu.edu.cn</email> (M.Y.) | |
| 773 | 0 | |t Mathematics |g vol. 13, no. 5 (2025), p. 782 | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3176336242/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3176336242/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3176336242/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |