A review of flow-induced vibration energy harvesters

Magnetically coupled piezoelectric galloping-based energy harvester using a tandem configuration

This paper proposes a novel finite element model (FEM) that can completely characterize the galloping based piezoelectric energy harvester (GPEH) systems. The challenges faced by conventional analy...

A finite element model to analyze the dynamic characteristics of galloping based piezoelectric energy harvester

This paper presents a magnetically coupling bending-torsion piezoelectric energy harvester based on vortex-induced vibration from low-speed wind. The theoretical model of the energy harvester was f...

Modeling and experimental investigation of magnetically coupling bending-torsion piezoelectric energy harvester based on vortex-induced vibration:

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. 

Uncertainty analysis of galloping based piezoelectric energy harvester system using polynomial neural network

In the present work, a non-linear electromechanical distributed parameter model is proposed for galloping based piezoelectric energy harvester (GPEH) and the impact of different order polynomial representation of aerodynamic force coefficient on the dynamic behavior of the system is investigated. Both geometric and aerodynamic nonlinearity (till 9 th order polynomial) is introduced in the proposed model. The derived model is universally valid for both series and parallel connection of piezoelectric bimorph patches. The dynamic responses of the system, for different order representations of aerodynamic force, are extensively studied and then compared with experimental results from the literature. It is shown that a minimum till 7 th order polynomial should be chosen for representing the galloping force coefficient in order to get a good agreement with experimental results. It is also shown from the model that the overall efficiency of the system is highest near the onset of galloping speed and decreases with an increase in wind speed. Further, a parametric study is done to find the effect of load resistance on the dynamic behavior of the system. It is seen that the error between experimental and predicted power decreases with an increase in the order of polynomial at a particular value of load resistance. The present analysis based on the proposed model emphasizes the importance of representation of aerodynamic force coefficients and geometric nonlinearity in predicting the accurate response for GPEH.

Dynamic stability and performance analysis of a galloping-based piezoelectric energy harvester for different order representations of the aerodynamic force

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 \(7\;{\text{m/s}}\).

Nonlinear Modeling and Stability Analysis of Piezoelectric Energy Harvesting Mechanism Under Aeroelastic Vibration

In the present study, a geometrically non-linear finite element (FE) method has been developed to find the dynamic characteristics of the galloping based piezoelectric energy harvesters (GPEH). The...

Rakesha Chandra Dash

Papers

Dynamic stability and performance analysis of a galloping-based piezoelectric energy harvester for different order representations of the aerodynamic force

A finite element model to analyze the dynamic characteristics of galloping based piezoelectric energy harvester

Uncertainty analysis of galloping based piezoelectric energy harvester system using polynomial neural network

Nonlinear Modeling and Stability Analysis of Piezoelectric Energy Harvesting Mechanism Under Aeroelastic Vibration

Nonlinear dynamic analysis of galloping based piezoelectric energy harvester employing finite element method