Development of a Tool for Elasto-Kinematic Suspension Optimization: Application to Double Wishbone and Multilink Archetypes

The following thesis is written in cooperation with the company Danisi Engineering S.r.l, a leading supplier of engineering and prototype solutions in the automotive sector. The aim of the thesis is the development of an optimization tool, based on the interaction between Adams Car and Matlab, for Elasto-kinematic (Kinematics & Compliance) suspension analysis. In particular, thanks to a global optimization algorithm, it is able to provide the optimal hardpoint coordinates for a given suspension archetype that meet certain targets. In the first analysis, a state-of-the-art study is conducted to identify the most suitable algorithm type for the specific case. Subsequently, a detailed study of the language underlying the Adams Car software, owned by the company Hexagon, is carried out to optimize the exchange of information with MATLAB software. Finally, considering that the optimization problem is multi-objective, two global optimization tools are implemented. The first based on NSGA II , Non-dominated Sorting Genetic Algorithm II, and the second based on MOPSO, Multi-Objective Particle Swarm Optimization. For the calibration of the input parameters, a double wishbone frontal archetype is used. Finally, multiple optimizations are conducted on additional archetypes, including one company archetype, and considering different loadcases. Additionally, a user-friendly Graphical User Interface (GUI) has been developed to make the tool accessible for engineers tackling complex suspension designs.