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Estimation of Thermal Network Models Parameters Based on Particle Swarm Optimization Algorithm

机译:基于粒子群算法的热网模型参数估计

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One of the biggest challenges in the Design for Reliability (DfR) methodology implementation into the development process are the extremely short delivery dates of Minimum Viable Product (MVP). This impediment is frequently encountered in the development of power supplies for plasma processing. In such case it is impossible to perform comprehensive but time-consuming simulations and the whole DfR process is focused on the stressors levels evaluation in working device. The goal for simulation stage is thus to choose most promising solution fulfilling specified requirements and rough estimation of chosen stressors levels. Time limitations and the demand on high quality already at the MVP stadium of the power supply development, raise a need to develop a simple and fast method for thermal modeling of critical components used in the designed power supply. In this paper, the particle swarm optimization (PSO) is introduced as an effective approach for the parameter estimation for thermal modelling of the power semiconductor modules used in power supplies for plasma processing.
机译:在开发过程中实施可靠性设计(DfR)方法的最大挑战之一是最小可行产品(MVP)的交货日期极短。在开发用于等离子体处理的电源时经常遇到这种障碍。在这种情况下,不可能执行全面但耗时的模拟,并且整个DfR过程都集中在工作设备中的压力源水平评估上。因此,仿真阶段的目标是选择满足指定要求的最有前途的解决方案,并对所选压力源水平进行粗略估算。电源开发的MVP体育场已经存在时间限制和对高质量的需求,因此需要开发一种简单快速的方法来对设计电源中使用的关键组件进行热建模。在本文中,引入了粒子群优化(PSO)作为对等离子处理电源中使用的功率半导体模块进行热建模的参数估计的有效方法。

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