This paper presents a methodology for the optimal preliminary design of electro-mechanical actuators. The main design drivers, design parameters and degrees of freedom that can be used for preliminary design and optimization of EMA are described. The different types of models used for model based design (estimation, simulation, evaluation and meta-model), and their associations are presented. The process preferred for its effectiveness in terms of flexibility and computational time is then described and illustrated with the example of a spoiler electromechanical actuator. The proposed approach, based on meta-models obtained using the surfaces response methods and scaling laws models, is used to explore the influence of anchorage points and transmission ratio on the different design constraints and the overall mass of the actuator.
In contrast to the current overall aircraft design techniques, the design of multirotor vehicles generally consists of skill-based selection procedures or is based on pure empirical approaches. The application of a systemic approach provides better design performance and the possibility to rapidly assess the effect of changes in the requirements. This paper proposes a generic and efficient sizing methodology for electric multirotor vehicles which allows to optimize a configuration for different missions and requirements. Starting from a set of algebraic equations based on scaling laws and similarity models, the optimization problem representing the sizing can be formulated in many manners. The proposed methodology shows a significant reduction in the number of function evaluations in the optimization process due to a thorough suppression of inequality constraints when compared to initial problem formulation. The results are validated by comparison to characteristics of existing multirotors. In addition, performance predictions of these configurations are performed for different flight scenarios and payloads.
The design optimization of coupled systems requires the implementation of multidisciplinary design optimization techniques in order to obtain consistent and optimal solutions. The associated research topics include the development of optimization algorithms, computational frameworks, and multidisciplinary design optimization formulations. This paper presents a benchmarking of the combination of monolithic formulations and derivative computation techniques. The monolithic formulations include typical literature formulations as well as new normalized variable hybrid formulation. A novel test problem is proposed which consists in the sizing of a space launcher thrust vector control electro-mechanical actuator. Solving the single multidisciplinary coupling present in this problem is complex due to the possibility to face one, two, or no solutions depending on the external load and reducer gear ratio configuration. A larger scale version of this test problem is also proposed and tested by adding a high degree of freedom point-to-point trajectory. The tests are carried out in order to obtain typical performance criteria but also some proposed additional robustness criteria such as variation of the initial conditions or the external load scale. These additional criteria are particularly relevant in an industrial engineering design context where knowledge capitalization and reuse are sought. The most significant findings are the interesting performances of the new formulation in terms of computational cost and the robustness. Furthermore, the effect of the choice of derivative computation strategy on different performance criteria is assessed for the original and larger scale problem, and thus underlines the benefits of full analytic gradient-based optimization.
This article is dedicated to the generation of sizing procedures used during the preliminary optimal design of physical parts of mechatronic systems. The knowledge necessary to such design is composed of two layers: mechatronic system layer and component layer. Such knowledge can be represented by algebraic equations directly or by the use of metamodeling techniques. Constraint networks and graphs theory are used here to represent and order the constraints and the links between those algebraic models in order to obtain a well-posed optimization problem. The selected or developed algorithms are finally illustrated with typical problems of component selection.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.