This presentation was made at the NAFEMS European Conference on Simulation-Based Optimisation held on the 15th of October in London.

Optimisation has become a key ingredient in many engineering disciplines and has experienced rapid growth in recent years due to innovations in optimisation algorithms and techniques, coupled with developments in computer hardware and software capabilities. The growing popularity of optimisation in engineering applications is driven by ever-increasing competition pressure, where optimised products and processes can offer improved performance and cost-effectiveness which would not be possible using traditional design approaches. However, there are still many hurdles to be overcome before optimisation is used routinely for engineering applications.

The NAFEMS European Conference on Simulation-Based Optimisation brings together practitioners and academics from all relevant disciplines to share their knowledge and experience, and discuss problems and challenges, in order to facilitate further improvements in optimisation techniques.

Resource Abstract

The shift towards electric propulsion of automotive vehicles brings higher demand for lightweight structures since the high prices of battery capacity put further need on energy efficiency. Lightweighting is one among several ways, e.g. reduce drivetrain losses, aerodynamic drag and rolling resistance, to improve energy efficiency and it can bring significant cost advantages in terms of price per range. Topology Optimization (TO) is a design tool often used to refine the geometrical layout relatively late and is applied to single components with predetermined boundary conditions such as joint loads and joint positions, i.e. constraints that narrow the solution space for the design. Therefore, the main idea is to broaden the solution space by introducing TO on system level together with an outer parametric loop for the joint positions.



A Finite Element (FE) model of a rear wheel suspension system is developed and validated with respect to the force signals from an existing fully modeled, dynamic, vehicle system. FE modelling techniques using SIMULIA Abaqus of structural and tuning parts such as cast components, thin sheet components, bushing joints, screw joints, dampers and springs are treated. The linkages are then optimized with respect to stiffness and weight based on current joint positions.



The proposed scheme for parametrization of joint positions is limited to a two-component system model. It is used for demonstration of a combined workflow where parametric and non-parametric optimizations are performed simultaneously. SIMULIA Tosca Structure is used for non-parametric stiffness optimization in an inner optimization loop and SIMULIA Isight is used in the outer optimization loop for parametric DoE (Design of Experiments). The studied parameters are geometric dimensions and bushing locations of the suspension components as well as the bushing characteristics. SIMULIA Abaqus/CAE is applied to automatically build the new suspension assemblies based on the input parameters from the outer loop of SIMULIA Isight. The demonstrator shows fully automated parametric and non-parametric optimization workflows with different type of trade off studies on the assembly.



Overall, the FE-model correlates well with respect to the force signals. However, there is still room for improvement, especially with respect to modeling of the dampers. There is also a need for correlation of the FE-model with respect to displacements in order to introduce proper stiffness constraints during optimization. The future potential for TO on system level is promising. In addition to a broader solution space through parametrization, the relative mass distribution between the components is achieved within one single system optimization.