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首页> 外文期刊>Journal of intelligent material systems and structures >Optimization of a piezoelectric energy harvester considering electrical fatigue
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Optimization of a piezoelectric energy harvester considering electrical fatigue

机译:考虑电疲劳的压电能源收割机优化

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摘要

The application of piezoelectric materials in energy harvesting devices has become an interesting topic for designers in recent years. Most of the reported works consider electrical power as a major parameter throughout the design procedure. What is less discussed is considering other design factors like the fatigue life of the harvester as well as the financial costs of the device. In this research, a methodology is introduced to design an optimum harvester, taking into account the aforementioned design factors. The finite element model of a piezoelectric harvester used in roadways is developed and validated. The fatigue test constants of the piezoelectric material are extracted via a novel approach. A parametric study is conducted on the model to generate a dataset containing electrical and mechanical characteristics, where it is used as an input for training an artificial neural network to model the behavior of the harvester. In order to evaluate the level of importance of the optimization objectives, two methods are employed: the Shannon entropy method and equal weighting factors. Results show the effectiveness of the model, where considering the electromechanical characteristics of the module is important in terms of overall performance, efficiency, durability, and financial costs.
机译:压电材料在能量收集装置中的应用已成为近年来设计师的有趣话题。大多数报告的作品将电力视为整个设计过程中的主要参数。讨论的是考虑到其他设计因素,如收割机的疲劳寿命以及设备的财务成本。在这项研究中,引入了一种方法来设计一个最佳的收割机,考虑到上述设计因素。开发并验证了道路上使用的压电收割机的有限元模型。通过新方法提取压电材料的疲劳试验常数。在模型上进行参数研究以产生包含电气和机械特性的数据集,其中用作培训人工神经网络以模拟收割机行为的输入。为了评估优化目标的重要性水平,采用了两种方法:Shannon熵方法和相等的加权因子。结果显示了该模型的有效性,考虑到模块的机电特性,就整体性能,效率,耐用性和财务成本而言是重要的。

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