A novel design method for mechatronic systems, based on knowledge based engineering techniques, is proposed in this research study. The method is particularly suited for mechatronic vehicles which are inherently unstable and require control systems for stabilization. The method is implemented in a dedicated software tool in which physical entities of the product are defined as classes with attributes. Non-physical elements of the system and procedures for the design and analysis of the system are defined as functions with variables. The method has two key features. First, multiphysics simulation models and associated analysis functions are generated automatically within a multidisciplinary analysis and optimization framework. These models are not restricted to geometrical aspects for mechanical design, but also include the system architecture, dynamics, aerodynamics, electronic control systems and associated software codes. Second, for each representation of a design, a dedicated control system is developed completely automatically, based on the multiphysics simulation model, using model inversion control. These two features make it possible to analyse the dynamics and performance of inherently unstable mechatronic vehicles already in the early design phases when the vehicle is still subject to large configuration design changes. The method is demonstrated for the design of a multirotor unmanned aerial vehicle. Thirty thousand possible design solutions are evaluated by the system without manual interference. For each design, a dedicated control system is created and five flight test maneuvers are simulated in order to assess the aircraft performance and flying qualities. A global optimization process is applied for two conflicting requirements and the process is convergent at two optimum solutions.
Abstract. Obtaining a representative loading spectrum that corresponds well to the reality is still one of the greatest challenges for fatigue life calculations and optimal design of the trailer body. A good qualitative and quantitative knowledge of the spectrum leads to more efficient usage of material, a better design of connection points and an overall decrease of the weight of the trailer, which finally results in a significant decrease in the price of a ton of cargo per km. Despite that, the approach is nowadays mostly based on the experience and rules of thumb. It typically results in over-dimensioning of some parts while other parts remain vulnerable to failure due to unknown loading patterns. This paper describes a generic approach to solve the problems mentioned above applied in a research project named FORWARD (Fuel Optimized trailer Referring to Well Assessed Realistic Design loads). The project lasted two years and was carried out in cooperation with several different trailer manufacturers and 1st tier suppliers. The loading history of more than 1000 hours for five trailer types were captured in the shape of strains, accelerations and velocities of various elements of the trailers, enabling reconstruction of the loading in terms of forces and moments acting on the wheels and kingpin. Parallel to this extensive test-campaign, a novel generic physics-based computational approach was developed to predict selected loads encountered during common manoeuvres to all trailer types. The computational approach was validated against test-data and resulted in creating a generic multibody library applicable for all trailer types, and an automated post-processing routine for the large amount of test-data.
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