Cargando…
Multiobjective optimization framework for designing a steering system considering structural features and full vehicle dynamics
Vehicle handling and stability performance and ride comfort is normally assessed through standard field test procedures, which are time consuming and expensive. However, the rapid development of digital technologies in the automotive industry have enabled to properly model and simulate the full-vehi...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10636188/ https://www.ncbi.nlm.nih.gov/pubmed/37945631 http://dx.doi.org/10.1038/s41598-023-45349-z |
_version_ | 1785133160446558208 |
---|---|
author | Llopis-Albert, Carlos Rubio, Francisco Devece, Carlos Zeng, Shouzhen |
author_facet | Llopis-Albert, Carlos Rubio, Francisco Devece, Carlos Zeng, Shouzhen |
author_sort | Llopis-Albert, Carlos |
collection | PubMed |
description | Vehicle handling and stability performance and ride comfort is normally assessed through standard field test procedures, which are time consuming and expensive. However, the rapid development of digital technologies in the automotive industry have enabled to properly model and simulate the full-vehicle dynamics, thus drastically reducing design and manufacturing times and costs while enhancing the performance, safety, and longevity of vehicle systems. This paper focus on a computationally efficient multi-objective optimization framework for developing an optimal design of a vehicle steering system, which is carried out by coupling certain computer-aided design tools (CAD) and computer-aided engineering (CAE) software. The 3D CAD model of the steering system is made using SolidWorks, the Finite Element Analysis (FEA) is modelled using Ansys Workbench, while the multibody kinematic and dynamic is analysed using Adams/Car. They are embedded in a multidisciplinary optimization design framework (modeFrontier) with the aim of determining the optimal hardpoint locations of the suspension and steering systems. This is achieved by minimizing the Ackermann error and toe angle deviations, together with the volume, mass, and maximum stresses of the rack-and-pinion steering mechanism. This enhances the vehicle stability, safety, manoeuvrability, and passengers’ comfort, extends the vehicle systems reliability and fatigue life, while reducing the tire wear. The method has been successfully applied to different driving scenarios and vehicle maneuvers to find the optimal Pareto front and analyse the performance and behaviour of the steering system. Results show that the design of the steering system can be significantly improved using this approach. |
format | Online Article Text |
id | pubmed-10636188 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106361882023-11-11 Multiobjective optimization framework for designing a steering system considering structural features and full vehicle dynamics Llopis-Albert, Carlos Rubio, Francisco Devece, Carlos Zeng, Shouzhen Sci Rep Article Vehicle handling and stability performance and ride comfort is normally assessed through standard field test procedures, which are time consuming and expensive. However, the rapid development of digital technologies in the automotive industry have enabled to properly model and simulate the full-vehicle dynamics, thus drastically reducing design and manufacturing times and costs while enhancing the performance, safety, and longevity of vehicle systems. This paper focus on a computationally efficient multi-objective optimization framework for developing an optimal design of a vehicle steering system, which is carried out by coupling certain computer-aided design tools (CAD) and computer-aided engineering (CAE) software. The 3D CAD model of the steering system is made using SolidWorks, the Finite Element Analysis (FEA) is modelled using Ansys Workbench, while the multibody kinematic and dynamic is analysed using Adams/Car. They are embedded in a multidisciplinary optimization design framework (modeFrontier) with the aim of determining the optimal hardpoint locations of the suspension and steering systems. This is achieved by minimizing the Ackermann error and toe angle deviations, together with the volume, mass, and maximum stresses of the rack-and-pinion steering mechanism. This enhances the vehicle stability, safety, manoeuvrability, and passengers’ comfort, extends the vehicle systems reliability and fatigue life, while reducing the tire wear. The method has been successfully applied to different driving scenarios and vehicle maneuvers to find the optimal Pareto front and analyse the performance and behaviour of the steering system. Results show that the design of the steering system can be significantly improved using this approach. Nature Publishing Group UK 2023-11-09 /pmc/articles/PMC10636188/ /pubmed/37945631 http://dx.doi.org/10.1038/s41598-023-45349-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Llopis-Albert, Carlos Rubio, Francisco Devece, Carlos Zeng, Shouzhen Multiobjective optimization framework for designing a steering system considering structural features and full vehicle dynamics |
title | Multiobjective optimization framework for designing a steering system considering structural features and full vehicle dynamics |
title_full | Multiobjective optimization framework for designing a steering system considering structural features and full vehicle dynamics |
title_fullStr | Multiobjective optimization framework for designing a steering system considering structural features and full vehicle dynamics |
title_full_unstemmed | Multiobjective optimization framework for designing a steering system considering structural features and full vehicle dynamics |
title_short | Multiobjective optimization framework for designing a steering system considering structural features and full vehicle dynamics |
title_sort | multiobjective optimization framework for designing a steering system considering structural features and full vehicle dynamics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10636188/ https://www.ncbi.nlm.nih.gov/pubmed/37945631 http://dx.doi.org/10.1038/s41598-023-45349-z |
work_keys_str_mv | AT llopisalbertcarlos multiobjectiveoptimizationframeworkfordesigningasteeringsystemconsideringstructuralfeaturesandfullvehicledynamics AT rubiofrancisco multiobjectiveoptimizationframeworkfordesigningasteeringsystemconsideringstructuralfeaturesandfullvehicledynamics AT devececarlos multiobjectiveoptimizationframeworkfordesigningasteeringsystemconsideringstructuralfeaturesandfullvehicledynamics AT zengshouzhen multiobjectiveoptimizationframeworkfordesigningasteeringsystemconsideringstructuralfeaturesandfullvehicledynamics |