Design and Control for Piezoelectric Energy Harvester Based on a Heuristic Optimization Algorithms

Energy harvesting represents a significant focus of attention for researchers to make optimal use of the energy available around in the environment, whether it is a natural phenomenon or resulting from human movement, equipment, and structures. This energy is available in several forms, such as solar, wind energy, temperature changes, and kinetic energy due to mechanical vibration. The framework of this paper includes the modeling of an intelligent controller for an efficient piezoelectric vibration energy harvester. In addition, it suggested two controllers to control the output voltage for this harvester. The Proportional-Integrated-Derivative (PID) control is applied in this paper as a main controller. The parameters of the second controller will be optimized by using various heuristic algorithms. (Ant Colony Optimization (ACO), Modified Camel Traveling Algorithm (MCTA), and Particle Swarm Optimization (PSO)). MATLAB/Simulink software will be used to build the model of the proposed circuit, where the model be verified under various testing conditions. The model output response is improved after adjusting the PID controller in line with optimization algorithms as compared with the conventional PID controller. The simulation findings indicate the capability of the proposed model of harvester with PSO-PID controller to give the best performance to get the desired output under different forces compared with the two other controllers (ACO-PID and MCTA-PID).

Abstract licence: CC BY-NC-ND

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