Multiobjective optimization framework for designing a steering system considering structural features and full vehicle dynamics

Abstract

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.

Digital Twin-Based Approach for a Multi-objective Optimal Design of Wind Turbine Gearboxes

“…Likewise, the computational cost of data processing is still an issue in large-scale applications. As a result, DTs help to reduce the cost of wind energy and to improve the reliability of wind turbines, which has promoted their dissemination in the academic world and their applications in the engineering field [35,36,37].…”

Digital Twin-Based Approach for a Multi-Objective Optimal Design of Wind Turbine Gearboxes

“…Likewise, the computational cost of data processing is still an issue in large-scale applications. As a result, DTs help to reduce the cost of wind energy and to improve the reliability of wind turbines, which has promoted their dissemination in the academic world and their applications in the engineering field [40][41][42].…”