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首页> 外文期刊>Sensors and materials >Multi-objective Optimal Parameter Design of Nanofilters and Heat Sink Fins in Train Traction Motor Drive System
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Multi-objective Optimal Parameter Design of Nanofilters and Heat Sink Fins in Train Traction Motor Drive System

机译:火车牵引电动机驱动系统中纳米过滤器和散热片的多目标最佳参数设计

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In this paper, the multi-objective parameter design of the heat sink modules of the converter and inverter in a train traction motor drive system was studied. The high-power insulated gate bipolar transistor (IGBT) devices embedded in converter and inverter modules usually generate considerable heat due to pulse width modulation (PWM) switching behavior. An appropriate heat dissipation system should be designed to reduce the temperature rise of the devices and to ensure their safe operation. The response surface method (RSM) was used to build a statistical model of the studied problem. The optimal design for the heat dissipation system is to minimize the objective functions of both the inlet temperature and outlet temperature of the heat sink modules. The three major control factors selected for the RSM are the mileage of nanofilter usage, the nanofilter type, and the limited current of the inverter. Since it is difficult to find an appropriate mathematical model associated with the three control factors that are based on physical principles, the optimal design of experiments (DOE) technique was used to describe the relation among the three control factors. In order to obtain the optimal inlet temperature and outlet temperature of the heat sink modules, multi-objective optimal design of the heat sink modules was addressed. The multiple performance characteristics index (MPCI) method was used to combine the two objective functions into one integrated index. To solve the nonlinear statistical model, orthogonal particle swarm optimization was used to efficiently find the optimal solution. Results showed that the obtained optimal solution provided the lowest inlet temperature and lowest outlet temperature for the heat sink modules in the train traction motor drive system. The statistical model can also be uploaded onto a cloud server to provide an effective cloud model. The optimal parameter design of the heat sink modules in the train traction motor drive system can be applied to provide effective information for an intelligent maintenance system (IMS) of the heat sink modules. The developed IMS is expected to increase the availability and reliability of nanofilters and heat sink fins using Internet of Things (IoT) and Industry 4.0 techniques.
机译:在本文中,研究了流动牵引电动机驱动系统中转换器和逆变器的散热器模块的多目标参数设计。嵌入转换器和逆变器模块中的高功率绝缘栅双极晶体管(IGBT)器件通常由于脉冲宽度调制(PWM)切换行为而产生相当大的热量。应设计适当的散热系统以降低器件的温度升高,并确保其安全操作。响应表面方法(RSM)用于构建研究问题的统计模型。散热系统的最佳设计是最小化散热器模块的入口温度和出口温度的目标功能。为RSM选择的三个主要控制因子是纳米过滤器使用的里程,纳米过滤式和逆变器的有限电流。由于难以找到与基于物理原则的三个控制因子相关的适当数学模型,因此使用实验(DOE)技术的最佳设计来描述三种控制因子之间的关系。为了获得散热器模块的最佳入口温度和出口温度,解决了散热器模块的多目标最佳设计。多个性能特征索引(MPCI)方法用于将两个目标函数组合成一个集成索引。为了解决非线性统计模型,使用正交粒子群优化来有效地找到最佳解决方案。结果表明,所获得的最优溶液为火车牵引电动机驱动系统中的散热器模块提供最低的入口温度和最低出口温度。统计模型也可以上传到云服务器上以提供有效的云模型。列车牵引电动机驱动系统中的散热器模块的最佳参数设计可以应用于提供散热器模块的智能维护系统(IMS)的有效信息。开发的IMS预计将增加纳米过滤器和散热片的可用性和可靠性,使用物联网(物联网)和工业4.0技术。

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