The design, development, and optimization of modern suspension systems is a complex process that encompasses several different engineering domains and disciplines such as vehicle dynamics simulation, tire data analysis, 1D lap-time simulation, 3D CAD design and structural analysis including full 3D collision detection. Typically, overall vehicle design and suspension development are carried out in multiple iterative design loops by several human specialists from diverse engineering departments. Fully automating this iterative design process can minimize manual effort, eliminate routine tasks and human errors, and significantly reduce design time. This desired level of automation can be achieved through digital modeling, automated model generation, and simulation using graph-based design languages and an associated language compiler for translation and execution. Graph-based design languages ensure the digital consistency of data, the digital continuity of processes, and the digital interoperability of all engineering software tools along the product life cycle (PLC). In this context, they are used to automate the design and development of a suspension system for a Formula student racing car. The automated design consists of an inner design loop for simulating suspension system properties, including a 1D lap-time simulation, and an outer loop for the 3D shape optimization of the modeled anti-roll bar geometry, including 3D collision detection. These nested loops are executed automatically, optimizing the vehicle's kinematics through a particle multi-swarm optimization algorithm. This generic design automation approach for suspension systems leads to improved design quality in significantly less time and at a lower cost.