A gray-box optimization procedure based on evolutionary algorithms for the initial design of a suspension concept for four wheel independently driven and steered vehicles is developed. With thepresented optimization method, the energy consumption together with state of the art knowledge about the parametrization and design of vehicle suspension systems leads to an optimization setup closely to real world requirements while the vehicle’s topology is exploited.
To this, the modelling presented in  is considered as a geometric suspension model. Furthermore, to take advantage of the potential of such vehicles, an autonomous closed-loop setup with integrated motion control is utilized. During the optimization, the chassis parameters with the most impact on energy consumption and driving dynamics, namely camber, caster, scrub radius and the steering axis inclination (SAI) depending on a varying caster angle and SAI in relation to the steering angle, will be focused. Therefore, the geometric arrangement of linkages, further considered as optimization parameters, substitutes certain modelling assumptions, leading to a realistic parametrization regarding mechanical design.
The proposed chassis design procedure is divided into a five-stage sequence. After the model and controller initialization, roll and pitch centers are determined optimally in step two. In the following step, initial parameters of the suspension are determined in the design attitude with particle swarm optimization (PSO) and static maneuvers. Subsequently, the suspension characteristics, depending on the steering angles as well as the vehicle’s vertical dynamics, during the dynamic ISO double lane change is determined indirectly with genetic algorithms (GA) and the geometric parameters used as optimization variables. Finally, to verify the suspension also for future requirements, the resulting sets of parameters are checked with some unconventional driving maneuvers, which in particular make use of the larger steering angles.