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This paper deals with the impact of uncertain input parameters on the electrical power generation of galloping-based piezoelectric energy harvester (GPEH). A distributed parameter model for the system is derived and solved by using Newmark beta numerical integration technique. Nonlinear systems tend to behave in a completely different manner in response to a slight change in input parameters. Due to the complex manufacturing process and various technical defects, randomness in system properties is inevitable. Owing to the presence of randomness within the system parameters, the actual power output differs from the expected one. Therefore, stochastic analysis is performed considering uncertainty in aerodynamic, mechanical, and electrical parameters. A polynomial neural network (PNN) based surrogate model is used to analyze the stochastic power output. A sensitivity analysis is conducted and highly influenced parameters to the electric power output are identified. The accuracy and adaptability of the PNN model are established by comparing the results with Monte Carlo simulation (MCS). Further, the stochastic analyses of power output are performed for various degrees of randomness and wind velocities. The obtained results showed that the influence of the electromechanical coefficient on power output is more compared to other parameters.

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The present research work is focused on the mechanism of harvesting electrical energy from the oscillation of the bluff body placed in airflow. A rectangular bluff body is attached to the tip of a cantilever beam which has a portion embedded with piezoelectric layers. A geometrically nonlinear distributed parameter model is derived using extended Hamilton's principle for both parallel and series connections of piezoelectric patches and solved using Newmark-beta method. Polynomial representation of aerodynamic force is done using quasi-steady hypothesis. It is found that nonlinear damping coefficients play a significant role in determining the stability of the system. System bifurcates (Hopf-bifurcation) and goes into a limit cycle after a particular wind speed. The radius of the limit cycle increases with wind speed. Approximately, 0.36 mW electric power can be generated at a wind speed of 7 m/s.