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Optimization of solder joints in embedded mechatronic systems via Kriging-assisted CMA-ES algorithm

机译:克里格辅助CMA-ES算法优化嵌入式机电系统中的焊点

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In power electronics applications, embedded mechatronic systems (MSs) must meet the severe operating conditions and high levels of thermomechanical stress. The thermal fatigue of the solder joints remains the main mechanism leading to the rupture and a malfunction of the complete MS. It is the main failure to which the lifetime of embedded MS is often linked. Consequently, robust and inexpensive design optimization is needed to increase the number of life cycles of solder joints. This paper proposes an application of metamodel-assisted evolution strategy (MA-ES) which significantly reduces the computational cost of ES induced by the expensive finite element simulation, which is the objective function in optimization problems. The proposed method aims to couple the Kriging metamodel with the covariance matrix adaptation evolution strategy (CMA-ES). Kriging metamodel is used to replace the finite element simulation in order to overcome the computational cost of fitness function evaluations (finite element model). Kriging is used together with CMA-ES and sequentially updated and its fidelity (quality) is measured according to its ability in ranking of the population through approximate ranking procedure (ARP). The application of this method in the optimization of MS proves its efficiency and ability to avoid the problem of computational cost.
机译:在电力电子应用中,嵌入式机电系统(MS)必须满足严苛的工作条件和高水平的热机械应力。焊点的热疲劳仍然是导致整个MS破裂和故障的主要机制。这是嵌入式MS的寿命通常与之相关的主要故障。因此,需要鲁棒且便宜的设计优化来增加焊点的寿命周期数。本文提出了一种应用元模型辅助进化策略(MA-ES)的方法,该策略可显着降低昂贵的有限元仿真所引起的ES的计算成本,而有限元仿真是优化问题中的目标函数。提出的方法旨在将Kriging元模型与协方差矩阵适应进化策略(CMA-ES)耦合。为了克服适应度函数评估(有限元模型)的计算成本,使用克里格元模型代替了有限元模拟。 Kriging与CMA-ES一起使用,并进行顺序更新,并根据其通过近似排名程序(ARP)对人群进行排名的能力来测量其保真度(质量)。该方法在MS优化中的应用证明了其效率和避免计算成本问题的能力。

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