Multi-field Coupling And Multi-discipline Optimization Design Of Magnetic Mechanism

The analysis and optimization design of magnetic mechanism involve several disciplines, such as mechanics, electromagnetism, material science. There also include several physical fields, such as electromagnetic field, thermal field, and dynamic field. The fields influence and affect each other, the relations among them decide the changing relations of physical parameters in subsystem, which should be considered in the analysis and optimation design of magnetic mechanism. The paper introduces the modeling and solving methods of multi-field coupling detailedly. The multi-discipline optimization design method considering multi-field coupling is introduced, which improves the design system of magnetic mechanism and provides a solution to solve the similar problems of mechanic/electrical coupling systems.Based on the research background of the project, the concepts, characterists and research current conditions of magnetic mechanology, dynamic characteristic, multi-field coupling, multi-discipline optimization are discussed, the disadvantages of current methods are pointed out, as well as the necessity of multi-discipline optimization design with multi-discipline coupling. Then the mathematic models of the fields in the coupling problem and the coupling matrix are introduced, which forms found for the research of the whole paper.Based on the classification and analysis of some local coupling problems, the global coupling design model is built. The solving method of multi-field coupling problems is researched systemically, including field partition method, coupling strategy, coupling algorithms, etc. The common features of the solving process of sub-problems are analyzed; the information which can be represented and transferred is clarified as well as their methods. A method to build a multi-field coupling system with semantics presentation, data transfer and knowledge engineering is proposed. All the above provide a method foundation for the specific analysis of multi-field coupling problems, such as dynamic characteristics analysis, thermal effect analysis.Referring to the analysis of dynamic characteristics, the mathematic models are given for the different conditions based on the common models. A sequence coupling method based on iteration strategy and a direct coupling method based on fully coupling strategy to discrete time and space dimensions are proposed to solve the electrical-magnetic-motive dynamic coupling problem, the dynamic design parameters and dynamic characteristic graphs are given. Referring to the analysis of thermal field influencing by both electromagnetic effects and mechanical moving effects, the time-changing heat sources and boundary conditions are carefully analyzed, as well as the thermal coefficients and heat transfer mechanism. The mechanic loss is pointed out, and the heat from it is added into the heat source. The coupling relation of thermal field and electromagnetic field, mechnial motion in magnetic mechanism is discussed; the electromagnetic– mechanic- thermal field is solved by time step iteration method. An example of 3D thermal analysis of the active part of frictional electromagnetic clutch is performed to illustrate the process and the feasibility of the FEM method and solving process considering coupling.The multi-discipline optimization design considering multi-field coupling is introduced in the design of magnetic mechanism, which solves the problem of the long calculation time, poor logic, and the difficulty to get the global optimal solution caused by the traditional sequential method cutting the coupling relations of disciplines. To deal with slow convergence or no convergence of CO, a devised CO and SAND integrating method is proposed in this paper, the architecture and process are given. The result shows that the optimization method proposed is useful to decrease the calculating time and increase the convergence ability of CO. Also, using the approximation models instead of complicated simulation models saves a lot of calculate time and resources. An example of optimization of frictional electromagnetic clutch is given to illustrate the analysis process of MDO, the optimization results are got and several objectives are accomplished.