Motor optimized design method based on fuzzy expert system multi-target particle team

A fuzzy expert system and multi-objective particle swarm technology, applied in the manufacture of motor generators, computing, electrical components, etc., can solve the problems of premature convergence of the algorithm and strong selection dependence, so as to speed up the development cycle, improve the accuracy and effect of speed

Inactive Publication Date: 2010-12-22
TIANJIN UNIV
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Problems solved by technology

Although the traditional optimal design strategy has achieved certain results in the practice of guiding motor design, due to the highly nonlinear objective function and constraint conditions of motor optimal design, competition and conflict between objective functions, there is still a gap between the optimization result and the initial solution. A series of problems such as strong dependence on selection and premature convergence of the algorithm to local extreme points

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  • Motor optimized design method based on fuzzy expert system multi-target particle team
  • Motor optimized design method based on fuzzy expert system multi-target particle team
  • Motor optimized design method based on fuzzy expert system multi-target particle team

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Embodiment Construction

[0045] Cost and efficiency are important indicators of the motor. How to use the existing technology to improve the cost performance of the motor as much as possible is a problem that the motor design engineers must solve. The traditional single-objective optimization restricts the designer to optimize only one objective, or to give the importance (weight) of different objectives, making the selection of the optimization objective one of the most difficult decisions in the optimal design of the motor. The present invention can optimize multiple objectives at the same time, and obtain the Pareto solution set of the comprehensive optimization scheme.

[0046] In this embodiment, the cost and efficiency indexes of commonly used three-phase asynchronous motors are optimized. The design variables to be optimized include: air gap δ, winding wire diameter d, number of winding turns N, number of stator slots Q 1 , the number of rotor slots Q 2 , Stator outer diameter D 1 , Stator i...

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Abstract

The invention relates to a motor optimization design method for a multi-objective particle swarm optimization algorithm based on a fuzzy expert system. The method performs motor optimization design by adopting the multi-objective particle swarm optimization algorithm based on the object distance, utilizes the fuzzy expert system to introduce expertise experiences for the motor design in and guidethe particle swarm to move towards the optimum solution set and finally obtains the optimum solution set of the motor design. Since the invention utilizes the expertise experiences to guide the particle swarm to move towards the optimum solution set, the influence of the initial solution selected at random to the solving result is reduced, the precision and the speed of solution of the multi-objective particle swarm optimization algorithm are improved, and the development cycle is quickened.

Description

technical field [0001] The invention relates to the field of motor optimization design, in particular to an intelligent optimization design method. Background technique [0002] In addition to considering the efficiency, motor design also needs to compare the volume, power, cost and other indicators of the motor under each design scheme. The optimization can be expressed as a constrained, nonlinear, mixed discrete multi-objective programming problem in a complex high-dimensional space. Due to the competition and conflict among various optimization objectives, there is no optimal solution for each optimization objective at the same time, so the selection of optimization algorithm is very critical to the quality of the design results. [0003] The traditional motor optimization design method is based on the assumption that the design variables are differentiable, and uses global optimization theory to solve the optimal design through mathematical modeling. It mainly includes t...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H02K15/00G06F17/00G06F17/50
CPCY02T10/82
Inventor 夏长亮陈炜史婷娜
Owner TIANJIN UNIV
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