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Parameter optimization of thermoelectric modules using a genetic algorithm

机译:基于遗传算法的热电模块参数优化

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Thermoelectric modules (TEM) are solid state components which are able to convert thermal to electric energy without moving parts and therefore are generally recognized as durable and reliable. However, the performance of TEM is strongly depending on the temperature difference driving the heat flux and causing thermo-mechanical stress within the module. This study introduces a multi-objective optimization procedure based on a genetic algorithm with which this conflict in objectives can be solved under realistic boundary conditions. Therefore a finite element model is presented and an optimization model is derived. The results of the optimization show that a significant improvement in electric power output and mechanical stability can be achieved by regarding all relevant design parameters in the module. (C) 2015 Elsevier Ltd. All rights reserved.
机译:热电模块(TEM)是固态组件,能够在不移动部件的情况下将热能转换为电能,因此通常被认为是耐用且可靠的。但是,TEM的性能很大程度上取决于驱动热通量并在模块内引起热机械应力的温度差。本研究介绍了一种基于遗传算法的多目标优化程序,利用该程序可以在现实的边界条件下解决目标冲突。因此,提出了有限元模型并推导了优化模型。优化结果表明,通过考虑模块中的所有相关设计参数,可以显着提高电力输出和机械稳定性。 (C)2015 Elsevier Ltd.保留所有权利。

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