A comprehensive energy flow model for piezoelectric energy harvesters: understanding the relationships between material properties and power output

A comprehensive energy flow model for piezoelectric energy harvesters: understanding the relationships between material properties and power output
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DOI:
10.1016/j.mtener.2023.101396
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发表时间:
2023-08
影响因子:
9.3
通讯作者:
Zihe Li;J. Roscow;H. Khanbareh;John Taylor;Geoffrey Haswell;C. Bowen
Zihe Li;J. Roscow;H. Khanbareh;John Taylor;Geoffrey Haswell;C. Bowen
中科院分区:
材料科学3区
文献类型:
--
作者:
Zihe Li;J. Roscow;H. Khanbareh;John Taylor;Geoffrey Haswell;C. Bowen

文献摘要

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压电材料具有很大的机械收获潜力,在决定功率输出方面具有重要的影响。虽然能量收集优值系数(F O M I J)经常被用来评价能量收集材料的性能,但F o M i j与功率输出之间的不一致使得材料的设计和选择变得复杂。为了应对这一挑战,本文建立了一个新的综合能量流模型,以评估材料的机械、压电和介电性质对整个收获过程的影响。在一系列激励条件下,通过详细的实验评估,该模型得到了实验验证,制备的压电材料产生了对比性能。该综合模型提供了强大的功能,可以(I)分析材料改性对能量流的影响,(Ii)精确量化功率输出对材料性质的依赖,以及(Iii)预测收割机的功率输出,其中能量流模型将预测输出功率与测量输出功率之间的最大误差显著减少∼70%。因此,这项工作提供了一种新的整体方法来填补在理解材料性能和收获性能之间的关系方面的知识空白,从而为未来在材料设计、选择和修改方面的研究提供信息。
Piezoelectric materials have significant potential for mechanical harvesting and have an important influence in determining the power output. While the energy harvesting figure of merit (F o M i j) is frequently used to evaluate the performance of an energy harvesting material, inconsistencies between the F o M i j and power output makes material design and selection complex. To address this challenge, this paper establishes a new comprehensive energy flow model to assess the influence of the mechanical, piezoelectric and dielectric properties of a material on the complete harvesting process. The model is experimentally verified via detailed experimental evaluation at a range of excitation conditions, with piezoelectric materials fabricated to yield contrasting properties. The comprehensive model provides powerful capabilities to enable (i) analysis of the influence of material modification on energy flow,(ii) precise quantification of the dependence of power output on material properties and (iii) prediction of the power output of a harvester, where the energy flow model significantly reduces the maximum error between predicted and measured output power by∼ 70%. This work therefore provides a new holistic approach to fill the knowledge gap in understanding the relationships between material properties and harvesting performance to inform future research in material design, selection and modification.