Responses, optimization and prediction of energy harvesters under galloping and base excitations

In this paper, the complexification-averaging method is firstly used to derive the theoretical solutions and analyze the dynamical performance of the energy harvesters under galloping and base excitations. Based on the distributed parameter model of the energy harvesters, the model equations can be turned into a set of high-order ordinary differential equations by solving the ordinary differential equations with coupled terms, then the equation of the amplitude frequency and the analytical relationship to determine the displacement amplitude and the voltage amplitude are derived. In addition, the influence of parameters such as the wind speed, the electromechanical coupling parameter and the base excitation frequency on the nonlinear behaviors of the energy harvesters are explored. It is found that there exists very good consistency between the theoretical results and the numerical results. The response properties are verified by means of the phase portraits and time histories. Additionally, according to the implicit function derivative theorem, the critical condition for identifying the unstable region is obtained. And with the different system parameters, the critical unstable boundary can be identified. In order to improve the efficiency of energy harvesting, the parameters of the energy harvesters are optimized based on the purpose of maximum voltage amplitude. Finally, the results are predicted by means of the multilayer feedforward neural network, and the excellent prediction results can be found.