...
首页> 外文期刊>Arabian Journal for Science and Engineering >Simultaneous Efficiency and Starting Torque Optimization of a Line‑Start Permanent‑Magnet Synchronous Motor Using Two Different Optimization Approaches
【24h】

Simultaneous Efficiency and Starting Torque Optimization of a Line‑Start Permanent‑Magnet Synchronous Motor Using Two Different Optimization Approaches

机译:使用两种不同优化方法的线路启动永磁同步电动机的同时效率和起始扭矩优化

获取原文
获取原文并翻译 | 示例
           

摘要

Line-start permanent-magnet synchronous motors (LSPMSMs) have poorer starting performance than induction motors.Optimization focusing only on transient performance improvement of the LSPMSM may degrade steady-state performance,and vice versa. In fact, an optimization focusing on maximizing starting torque may reduce efficiency by up to approximately7% and optimizing efficiency may cause degradation in starting torque by 5%. Hence, simultaneous steady-stateand transient performance optimization of a 4-kW LSPMSM under a multi-objective function is examined in this study.Efficiency maximization and starting torque maximization are nominated as objective functions. Two different optimizationapproaches, a gradient-based algorithm and gradient-free algorithm, are employed to optimize the LSPMSM. Sequentialnonlinear programming is used as the gradient-based algorithm in this study, and the gradient-free algorithm used is thegenetic algorithm (GA). A comparative study of the algorithms’ performance is presented. To provide an inclusive comparisonof both algorithms’ performance, a similar optimization study is implemented for a baseline induction motor. Theresults demonstrate that the multi-objective optimization improves steady-state and start-up performance of both motors.Results indicate that both algorithms converge reliably to almost the same optimum (objective) value. Depending on thenature of the optimization problem, number of design variables, and degree of convergence, the genetic algorithm requiresmany more evaluations than the gradient-based algorithm. Accordingly, optimization time required by the GA is more thanthe gradient-based algorithm under similar conditions.
机译:线路启动永磁同步电动机(LSPMSMS)的起始性能较差,而不是感应电机。仅在LSPMSM的瞬态性能改进上专注的优化可能会降低稳态性能,反之亦然。事实上,对最大化起始扭矩的优化可以降低效率最多7%和优化效率可能导致启动扭矩下降5%。因此,同时稳态在本研究中检查了在多目标函数下4-KW LSPMSM的瞬态性能优化。效率最大化和启动扭矩最大化被提名为客观功能。两种不同的优化采用梯度基算法和梯度算法的方法来优化LSPMSM。顺序非线性编程用作本研究中的基于梯度的算法,并且使用的渐变算法是遗传算法(GA)。提出了对算法的比较研究。提供包容性比较在算法的性能中,为基线感应电动机实施了类似的优化研究。这结果表明,多目标优化提高了两个电机的稳态和启动性能。结果表明,两种算法都会可靠地收敛到几乎相同的最佳(目标)值。取决于优化问题的性质,设计变量数量和收敛程度,遗传算法需要比基于梯度的算法更多的评估。因此,GA所需的优化时间超过基于梯度的算法在类似条件下。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号