Maximum power point tracking algorithms of a piezoelectric energy harvester under forced excitation.

This paper deals with the power production from a piezoelectric biodynamic harvesting scheme via the local step optimization point of the algorithm. In addition, the sensitivity and error of the maximum power point tracking (MPPT) algorithm are determined in this work due to its non-linear extrapolation approach in order to provide a real-time adaptation of the circuit impulses and to obtain matching of the target load impedance. The presented method provides a non-linear extrapolation model for the combined harvester design based on an artificial neural network (ANN). An analytical model of harvestable electrical power for piezoelectric vibration energy generation is proposed. Furthermore, steering stability is enhanced by a strong active front steering and an active differential drive control. The applicability of this approach outperformed the conventional method of observing perturbations under various operational requirements. [ABSTRACT FROM AUTHOR]