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Non-linear identification of a Peltier cell model using evolutionary multi-objective optimization

机译:基于进化多目标优化的珀耳帖单元模型非线性识别

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In this paper a technique for identifying a first principles model of a Peltier cell using Multi-Objective Evolutionary optimization and experimental data is proposed. The methodology of multi-objective optimization applied together with the method of representation of the Pareto front called level diagram enables the analysis of the set of models obtained for the temperatures of a Peltier cell in different scenarios. Level diagrams facilitate the selection of a compromise model to characterize the thermoelectric module successfully. The main advantage of the multi-objective design methodology is to easily understand the trade-off among several Pareto optimal solutions. The designer can select the final solution according to his/her preferences without missing the knowledge available from the set of optimal solutions.
机译:本文提出了一种利用多目标进化优化和实验数据识别珀尔帖单元第一原理模型的技术。多目标优化方法与帕累托前沿称为水平图的表示方法一起应用,可以分析在不同情况下针对珀耳帖单元温度获得的一组模型。水平图有助于选择折衷模型以成功表征热电模块。多目标设计方法的主要优点是可以轻松地理解多个Pareto最佳解决方案之间的权衡。设计人员可以根据自己的喜好选择最终解决方案,而不会错过最佳解决方案集中的可用知识。

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