The number of mechatronic sub-systems in road vehicles is growing fast. Auxiliary systems that traditionally have been driven by the combustion engine via, for instance, gears, belts or hydraulics are being replaced with electric systems. This development is primarily driven by new and improved functionality, but it is also necessary for the transition to electric and hybrid-electric drive trains.
A mechatronic sub-system can be very complex to design and especially to optimize, mainly due to the multi domain characteristics of mechatronics. Usually, in traditional methodologies for mechatronic design, the mechanical structure is determined separate from the controller and also from the electric motor design. To improve the results from the mechatronic development process, a more holistic approach is necessary. The foreseen very large production volumes of mechatronic actuation modules for the automotive industry enable such a holistic approach, where all constituent components can be designed and optimized in one common process.
The problem that is being approached in this research is delimited to a methodology for conceptual design and optimization of mechatronic actuation modules. Such modules will be the low level corner stones to achieve advanced functionality such as vehicle stability control and collision avoidance. The goal with the methodology is to capture all relevant system design parameters and properties, from all involved engineering domains, in one single evaluation and optimization process.
Some previous work has been done in this area, and many different research groups are working on new methods for mechatronics design. Most of the work is however concentrated on design of system dynamics from a control perspective, i.e. optimization of a system’s dynamic performance. The goal with this research project is to find methods that combine the structure design (statics & dynamics) with the controller design (dynamics). Further, the goal is to derive optimization methods that can find the most optimal system configuration and parameter set with respect to both static and dynamic criteria.