Design of vibratory energy harvesters under stochastic parametric uncertainty: a new optimization philosophy
Design of vibratory energy harvesters under stochastic parametric uncertainty: a new optimization philosophy
复制标题
DOI：
10.1088/0964-1726/25/5/055023
复制
发表时间：
2016-05-01
影响因子：
4.1
通讯作者：
Turitsyn, Konstantin
中科院分区：
文献类型：
--
作者：
Hosseinloo, Ashkan Haji;Turitsyn, Konstantin
振动能量采集器作为传统电池的潜在替代品，并不像电池那样坚固。在其参数存在不确定性的情况下，它们的性能会急剧恶化。参数不确定性对于任何物理设备都是不可避免的，主要是由于制造公差、缺陷以及温度和湿度等环境影响。因此，不确定性传播分析和优化下的不确定性似乎是必不可少的任何能量采集器的设计。在这里，我们提出了一个新的建模理念下的不确定性优化;优化的最坏情况下（最小功率），而不是合奏期望的功率。所提出的优化理念实际上是非常有用的，当有一个最低要求的收获功率。我们以通用且与架构无关的方式阐述了不确定性传播和不确定性下的优化问题，然后将其应用于不同参数具有不确定性的单自由度线性压电能量采集器。仿真结果表明，有一个显着的改善，在最坏情况下的功率设计收割机相比，天真优化（确定性优化）收割机。例如，对于采集器的自然频率的10%的不确定性（就其标准偏差而言），该改进约为570%。
Vibratory energy harvesters as potential replacements for conventional batteries are not as robust as batteries. Their performance can drastically deteriorate in the presence of uncertainty in their parameters. Parametric uncertainty is inevitable with any physical device mainly due to manufacturing tolerances, defects, and environmental effects such as temperature and humidity. Hence, uncertainty propagation analysis and optimization under uncertainty seem indispensable with any energy harvester design. Here we propose a new modeling philosophy for optimization under uncertainty; optimization for the worst-case scenario (minimum power) rather than for the ensemble expectation of the power. The proposed optimization philosophy is practically very useful when there is a minimum requirement on the harvested power. We formulate the problems of uncertainty propagation and optimization under uncertainty in a generic and architecture-independent fashion, and then apply them to a single-degree-of-freedom linear piezoelectric energy harvester with uncertainty in its different parameters. The simulation results show that there is a significant improvement in the worst-case power of the designed harvester compared to that of a naively optimized (deterministically optimized) harvester. For instance, for a 10% uncertainty in the natural frequency of the harvester (in terms of its standard deviation) this improvement is about 570%.