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引用次数: 1
摘要
提出了一种基于粒子群算法的多相感应电动机优化设计方法。优化算法以活性材料成本为目标函数，以九个性能相关项为约束条件。在两台7.5 kW和110 kW的测试电机上实现了PSO算法，并将其结果与约束Rosen Brock方法(Hill算法)和常规设计进行了比较。优化变量由SPEED (Scottish Power Electronics and Electric Drives)软件实现。优化设计结果在理论上是合理的。采用一些标准的基准测试问题来验证粒子群算法。c++代码用于实现整个算法。
Cost minimization and its realization on induction motor design via SPEED/PC-IMD
This paper presents an optimal design of poly-phase induction motor using Particle Swarm Optimization (PSO). The optimization algorithm considers the cost of active material as objective function and nine performance related items as constraints. The PSO algorithm was implemented on two test motors (7.5 kW and 110 kW) and their results are compared with the Constrained Rosen Brock Method (Hill algorithm) and normal design. Optimized variables are realized by SPEED (Scottish Power Electronics and Electric Drives) software. Optimal design results are theoretically justified. Some standard benchmarking problems are used to validate the PSO algorithm. C++ code is used for implementing entire algorithms.
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