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Optimization Design of Three-phase Asynchronous Motor Based on Multi-objective Ant Colony Algorithm

Author: ChenQingFeng
Tutor: LiGuoLi
School: Zhejiang University of Technology
Course: Applied Computer Technology
Keywords: three-phase asynchronous motor optimization design mathematical model multi-objective ant colony algorithm
CLC: TP18
Type: Master's thesis
Year: 2012
Downloads: 111
Quote: 1
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Abstract


The motor optimization design is a research focus of electrical engineering, which is a design technology to optimize the motor efficiency, torque, power factor and other performance indicators meanwhile meeting the national standards, user requirements and specific constraints. It can be described as a complex nonlinear programming problem with constraint, multi-objective, multi-variable and multi-peak.Therefore, to find an optimization algorithm with good global optimization ability and high convergence speed becomes an important research topic with practical significance. Based on the research of Multi-Objective Ant Colony Algorithm (MOACA), this paper will apply MOACA to three-phase asynchronous motor design. Typical examples will be used to indicate the effectiveness of the method.The main works are as follows:1. Based on the research of optimization algorithms commonly used for motor design, this paper focus on the basic principles and characteristics of Ant Colony Algorithm and extends it to Multi-Objective Ant Colony Algorithm.2. Using six representative test functions to verify the validity of Multi-Objective Ant Colony Algorithm.3. Establishing the multi-objective optimization mathematical model of three-phase asynchronous motor, the objective functions, optimization variables and constraints for multi-objective optimization are also given.4. The MOACA is applied into the multi-objective optimization system of three-phase asynchronous motor. The optimization results of typical examples compared with other optimization algorithms proposed in our group’s previous work, the result shows that the convergence speed, the number of non-inferior solution of the algorithm can meet the requirements of the motor multi-objective optimization design.The research work of this paper is supported by the important science & technology specific projects of Zhejiang (2008C01011-1).

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