A design method of motor optimization based on Game Theory

An optimization design and game theory technology, applied in the field of motor optimization design and manufacturing, can solve the problem of a large number of non-inferior solutions, and achieve the effect of accelerating the development cycle, lowering the technical threshold, and improving the optimization speed

Inactive Publication Date: 2009-09-02
TIANJIN UNIV
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Problems solved by technology

However, in order to ensure the dispersion of solutions, this multi-objective optimization algorithm obtains a large number of non-inferior solutions, and selecting the optimal solution requires strong professional knowledge and a long time

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  • A design method of motor optimization based on Game Theory
  • A design method of motor optimization based on Game Theory
  • A design method of motor optimization based on Game Theory

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Embodiment Construction

[0024] The important indicators in the motor design - cost and efficiency are in conflict to a certain extent. Among the non-inferior solutions obtained by the multi-objective optimization algorithm, the efficiency with low cost is also low, and the cost with high efficiency is also high. To solve this problem, the present invention adopts a strategic concession game to search for a comprehensive optimization scheme.

[0025] The present invention expresses the multi-objective optimization problem of the motor as a game problem G, the optimization target is regarded as the game party, and m sub-objective functions are used as the utility of each game party, represented by ui, and the design variables are decomposed into The strategy of each player and the Pareto solution set of the design plan obtained by the multi-objective optimization algorithm constitute the game strategy set (strategy space) S, and the strategies in S satisfy all the equality and inequality constraints in ...

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Abstract

The invention relates to a design method of motor optimization based on Game Theory, which comprises the following steps: (1) determining variables to be optimized in motor design and establishing a partial objective functional equation and a constraint equation; (2) determining a noninferior solution set which is then taken as a strategy set in Game Theory; (3) taking an optimization objective as a player and taking a partial objective function and taking definite purpose as utilities of each player, disintegrating design variables into strategies for each player according to the correlation between the utilities and each partial objective function, and changing the solving problem of the optimal motor design scheme into a Game problem according to the above steps, wherein each player can cooperate with each other so as to maximize the utility of each player; and (4) adopting a method of cooperative Game for integratedly optimizing each optimization objective from Nash equilibrium solution, thus obtaining the global optimum solution. The design method of motor optimization fully takes the relation among different optimization objectives into account so as to search the integrated optimum solution, thus shortening the motor design cycle, lowering development difficulty and laying foundation for the intelligentization of motor optimization design.

Description

technical field [0001] The invention relates to the technical field of motor optimization design and manufacture. Background technique [0002] With the continuous development of optimization algorithms, the optimal design method of electric motors that optimizes multiple conflicting objectives at the same time and obtains the Pareto solution set of design schemes has become a research hotspot in recent years. This multi-objective optimization design method can solve the set of non-inferior design schemes that satisfy the constraints, and designers can flexibly choose suitable design schemes according to actual needs. However, in order to ensure the dispersion of solutions, this multi-objective optimization algorithm obtains a large number of non-inferior solutions, and selecting the optimal solution requires strong professional knowledge and a long time. [0003] Researching the algorithm of searching optimal solution from non-inferior solutions can reduce labor intensity ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H02K15/00H02K17/42
Inventor 夏长亮陈炜史婷娜
Owner TIANJIN UNIV
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