Enhancing the Output Performance of Energy Harvesters Using Hierarchical Auxetic Structure and Optimization Techniques

In this article, we proposed a novel piezoelectric energy harvester based on hierarchical auxetic structures to improve the power output. The auxetic structure can harvest more energy compared with a traditional flat energy harvester since the piezoelectric element in two directions can be stretched simultaneously due to the effects of the negative Poisson's ratio. Furthermore, the hierarchical auxetic structure can produce a smaller negative Poisson's ratio and deform more sufficiently to improve the energy harvesting efficiency. Therefore, the proposed hierarchical auxetic energy harvester (HAEH) can produce higher power than the normal reentrant auxetic one. A numerical model is established by employing COMSOL Multiphysics software to investigate the performance of the HAEH and verified by comparing it with the experimental results of the physical prototype fabricated by machining. In addition, an optimization framework based on a machine learning model and multiobjective nondominated sorting genetic algorithm optimization is developed to optimize the HAEH for better energy harvesting performance. The HAEH has a bright future for battery-free sensors in various engineering fields.