• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文学位 >Coupled electromagnetic/thermal machine design optimization based on finite element analysis using high-throughput computing.
【24h】

Coupled electromagnetic/thermal machine design optimization based on finite element analysis using high-throughput computing.

机译：基于使用高通量计算的有限元分析的电磁/热机耦合优化设计。

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Comprehensive optimization of an electrical machine design requires that its electromagnetic (EM) and thermal performance must be analyzed and optimized simultaneously since electric machines are heavily constrained by thermal limits. This research presents a coupled EM/thermal model that can efficiently identify the maximum current density for a given machine during static operation, together with the integration of this coupled model into an iterative machine design optimization program. An artificial neural network (ANN) that is capable of effectively characterizing input/output relationships for nonlinear multivariable functions is incorporated into the optimization program, resulting in a significant reduction of the total computation time.;For demanding applications such as traction motors, the electric machine is frequently required to run at peak power conditions for short periods of time, causing large thermal swings. In addition to steady-state operating conditions, a transient version of the coupled EM/thermal model has been developed. This makes it significantly easier for machine designers to maximize the winding current density to achieve the highest possible torque/power ratings within thermal limits set by the winding insulation or demagnetization threshold requirements. Furthermore, this transient model has been integrated into the optimization program to give it the capability of optimizing the machine designs for both steady-state and short-duration transient operating conditions.;Although finite element (FE) analysis is a powerful analytical tool for electric machines, it is rarely used in iterative machine design optimization programs since it is computationally intensive, requiring excessive calculation times. This research introduces an approach for overcoming this obstacle using a high-throughput computing (HTC) environment that harnesses the parallel processing capabilities of large numbers of computers to evaluate many candidate designs simultaneously. Differential evolution has been selected as the optimization algorithm that applies FE analysis to maximize the electromagnetic performance according to an objective function in a computationally-efficient manner. Tests comparing the computational speeds achieved using the same optimization software with the HTC resources and a single computer have demonstrated a major reduction (approx. 30:1) of the computation time using the HTC approach.
机译：电机设计的全面优化要求必须同时分析和优化其电磁（EM）和热性能，因为电机受热极限的限制很大。这项研究提出了一种耦合的EM /热模型，该模型可以有效地确定给定机器在静态运行期间的最大电流密度，并且可以将此耦合模型集成到迭代的机器设计优化程序中。优化程序中集成了能够有效表征非线性多元函数的输入/输出关系的人工神经网络（ANN），从而显着减少了总计算时间。经常需要使机器在峰值功率条件下短时间运行，从而导致较大的热摆幅。除了稳态工作条件外，还开发了耦合的EM /热模型的瞬态版本。这使电机设计人员更容易地最大程度地提高绕组电流密度，以在绕组绝缘或退磁阈值要求设置的热极限内实现最大可能的转矩/功率额定值。此外，此瞬态模型已集成到优化程序中，从而使其能够针对稳态和短期瞬态运行条件对机器设计进行优化。;尽管有限元（FE）分析是电气分析的强大工具机器，它很少用于迭代的机器设计优化程序中，因为它的计算量很大，需要大量的计算时间。这项研究介绍了一种使用高通量计算（HTC）环境克服这一障碍的方法，该环境利用大量计算机的并行处理能力来同时评估许多候选设计。已选择差异演化作为优化算法，该算法应用FE分析以计算效率高的方式根据目标函数最大化电磁性能。使用相同的优化软件与HTC资源和一台计算机比较获得的计算速度的测试表明，使用HTC方法可大大减少（大约30：1）的计算时间。

著录项

  • 作者

    Jiang, Wenying.;

  • 作者单位

    The University of Wisconsin - Madison.;

  • 授予单位 The University of Wisconsin - Madison.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2014
  • 页码 242 p.
  • 总页数 242
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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