Up until recently a sequential approach has been pursued for model-based design of dynamic mechatronic systems, where first the system is optimized for static performance measures after which its functionality is enhanced by optimizing its control trajectory. However, this impedes finding systems with concurrent optimal design and trajectory. To address this, multi-disciplinary integrated design methods – co-design – have appeared that treat design and trajectory optimization simultaneously. However, as yet, co-design has only been applied to low-fidelity models, that are cheap to evaluate but typically lack the ability to correctly represent reality. In this proposal I wish to push model-based system design further by including high-fidelity models, that more accurately capture the system’s actual behavior but come at an increased computational cost. To do this, I introduce surrogate-assisted methodologies that possess the ability to include high-fidelity models in co-design. I intend to validate the new methodology by performing a model-based design of an unmanned aerial vehicle with the objective of enabling medical transportation beyond its current capabilities, that are presently limited by range. Furthermore, the methodological development will also enable the innovative design of e.g. airborne wind energy and break through the current barrier of several fields to accelerate the transition towards renewable energy.