Machine builders and vehicle drivetrain manufacturing companies are confronted with competitive markets which request customized machines and vehicles that exhibit ever improving characteristics, such as higher speed, higher accuracy, reduced energy consumption and lowered vibration levels to enhance comfort or reliability. Also, these machines and vehicles are operated under a wide variety of load conditions. Additionally, legislation imposes challenging emission norms and efficiency labels. 

All these requirements affect many aspects of the drivetrain design. However, the final performance and cost is to a large extend determined by the physical design and controller design during the early phase of embodiment design. Currently, the companies adopt a sequential design methodology, in which first the physical properties are selected, next these a controller is designed. However, given these challenging and often conflicting requirements, this sequential design approach yields suboptimal designs and its iterative nature inevitably increases the design time. Additionally, most manufacturers do not build a single variant of a machine. In order to cover adequately the need of their different customers, they offer different variants of the same machine. Consequently, in order to design the next generation of machines cost-effectively, component selection should not be selected for a single type of machine, but be taking into account the entire product family. 

The objective of this project is to create a model-based methodology and software tools to support optimal control design, concurrent control and physical design and product family design for electromechanical drivetrains of machines and vehicles.