2,131 research outputs found
Energy harvesting from ambient vibrations using piezoelectric polymeric materials: computational insights for structural monitoring applications
No full textAdvances in sensing technologies and wireless transmission can facilitate the large-scale implementation of sensor networks for structural monitoring applications, thereby allowing assessment and intelligent management of the civil constructions throughout their lifetime. On the other hand, the massive implementation of wireless nodes also poses new and challenging technological issues, such as the search for energy-efficient sensing devices and the use of energy harvesting technologies. In this perspective, advanced, yet efficient, modelling of electro-mechanical systems for energy harvesting and sensing is a fundamental task in order to develop reliable self-powered autonomous electronic devices designated for structural monitoring applications. In the present talk, therefore, we address some important computational issues related to the analysis and optimum design of vibrational energy harvesting devices made of piezoelectric polymeric materials, with focus on electrospun PVDF nanofibers. Specifically, the talk will cover the advanced finite element-based numerical modeling of piezoelectric systems as well as the semi-analytical probabilistic analysis of piezoelectric beams subjected to random vibrations by means of reduced-order models
Energy harvesting from vertical pedestrian-induced vibrations of footbridges
No full textThe use of advanced sensing systems can facilitate the remote health and serviceability survey of existing infrastructures. In particular, the large number of footbridges built in many countries can greatly benefit from the implementation of smart technological solutions for data transmission and power management. Within this framework, the present paper is con-cerned with the possibility of using piezoelectric energy harvesters as electrical power source for wireless sensor nodes installed on footbridges. An efficient probabilistic computational framework has been implemented in order to provide preliminary useful results in this regard. Specifically, the vertical dynamic response of a single-span footbridge under multiple walkers is simulated by considering its first mode of vibration only, and the pedestrian load is mod-elled as a moving sinusoidal force. The scavenging device is a cantilever bimorph with piezo-electric layers made of electrospun PVDF nanofibers. It is assumed that the uncertainties are mainly related to the pedestrians’ dynamics. Therefore, the randomness of the walkers’ char-acteristics is taken into account by means of existing probability distributions whereas the arrival time is modelled through the Poisson distribution. Monte Carlo simulations have been finally performed for a particular case-study in order to estimate the electrical energy generat-ed by the device
Reduced-order modeling with multiple scales of electromechanical systems for energy harvesting
No full textNew technologies that aim at powering wireless nodes by scavenging the energy from ambient vibrations can be a practical solution for some structural monitoring applications in the near future. In view of possible large-scale applications of piezoelectric energy harvesters, an accurate modeling of the interfaces in these devices is needed for more advanced and reliable simulations, since they might have large influence on functionality and performance of smart monitoring infrastructures. In this perspective, a novel multiscale and multiphysics hybrid approach is proposed to assess the dynamic response of piezoelectric energy harvesting devices. Within the framework of the presented approach, the FE2 method is employed to compute stress and strain levels at the microscale in the most critical interfaces. The displacement-load curve of the whole device (so-called capacity curve or pushover curve) is then obtained by means of the application of a suitable pattern of static forces. Finally, the parameters of a reduced-order model are calibrated on the basis of the nonlinear static analysis. This reduced-order model, in turn, is employed for the efficient dynamic analysis of the energy harvesting device
Computational and experimental analysis of surface acoustic wave propagation on piezoelectric GaAs layer
No full textNonlinear modelling of t-shaped piezoelectric device for structural health monitoring and fluid energy harvesting
No full textThis contribution focuses on modeling the dynamic behavior of T-shaped piezoelectric energy harvester devices. Nonlinearities arising from different aspects, such as material and geometrical effects, are taken into account. Classical reduced-order modeling approaches have been enhanced by including effects of large deformations, yielding to effective circuit representations that allows for an intuitive insight in the energy transduction processes characterizing the considered class of devices
Modelling and parameter identification of electromechanical systems for energy harvesting and sensing
No full textAdvanced modelling of electro-mechanical systems for energy harvesting (EH) and sensing is important to develop reliable self-powered autonomous electronic devices and for structural health monitoring (SHM). In this perspective, a novel computational approach is here proposed for both real-time and off-line parameter identification (PI). The system response is governed by a set of four partial differential equations (PDE) where the three displacement components and the electrical potential are the unknowns. Firstly, the finite element (FE) method is used to reduce the PDE problem into a set of ordinary differential equations (ODE). Then, a state-space model is derived with the aim to limit the PI problem to a subset of unknowns. After that, an identification error is introduced and the Lyapunov theory is used to derive the PI algorithm. The numerical implementation is based on a sensitivity analysis feedback block. The overall proposed computational strategy is robust and results in an exponential asymptotic convergence. The accuracy of the PI method is demonstrated by analysing the time-domain response of an array of piezoelectric bimorphs subjected to low-frequency structural random vibrations. The selected case-study is an existing cable-stayed bridge, for which an extensive dynamic monitoring campaign has provided the experimental data. Once time histories of the device response are obtained through time-dependent dynamic FE simulations, the PI algorithm is used to determine the unknown lumped coefficients of the state-space model. The comparison between FE method and lumped parameters model in terms of tip displacement and output voltage demonstrates the superior predictive capability of the new PI algorithm. As a result of the sensitivity analysis, guidelines to assess the optimal array configuration are also provided
Energy harvesting from piezoelectric strips attached to systems under random vibrations
No full textThe possibility of adopting vibration-powered wireless nodes has been largely investigated in the last years. Among the available technologies based on the piezoelectric effect, the most common ones consist of a vibrating beam covered by electroactive layers. Another energy harvesting strategy is based on the use of piezoelectric strips attached to a hosting structure subjected to dynamic loads. The hosting structure, for example, can be the system to be equipped with wireless nodes. Such strategy has received few attentions so far and no analytical studies have been presented yet. Hence, the original contribution of the present paper is concerned with the development of analytical solutions for the electrodynamic analysis and design of piezoelectric polymeric strips attached to relatively large linear elastic structural systems subjected to random vibrations at the base. Specifically, it is assumed that the dynamics of the hosting structure is dominated by the fundamental vibration mode only, and thus it is reduced to a linear elastic single-degree-of-freedom system. On the other hand, the random excitation at the base of the hosting structure is simulated by filtering a white Gaussian noise through a linear second-order filter. The electromechanical force exerted by the polymeric strip is negligible compared with other forces generated by the large hosting structure to which it is attached. By assuming a simplified electrical interface, useful new exact analytical expressions are derived to assess the generated electric power and the integrity of the harvester as well as to facilitate its optimum design
Identification of Piezoelectric Energy Harvester Parameters Using Adaptive Models
No full textIn this work, a dynamic system method is proposed to identify modal parameters of piezoelectric energy harvesting devices. A gradient based technique is implemented through which the identification problem can be approached as the design of a stable artificial dynamic system which equilibrium point provides the unknown parameters. The Lyapunov theory guarantees that this set of dynamic equations is characterized by an asymptotic convergence. Simulation studies are here reported to confirm the effectiveness of the proposed methodology for identifying unknown parameters of electromechanical vibration based energy harvesters. The sensitivity problem, resulting from the gradient based algorithm, is dealt with frequency and time domain procedures. The main advantage of the proposed strategy is that voltage measurements can directly be used for online parameter identification
A Two-Step Hybrid Approach for Modeling the Nonlinear Dynamic Response of Piezoelectric Energy Harvesters
No full textAn effective hybrid computational framework is described here in order to assess the nonlinear dynamic response of piezoelectric energy harvesting devices. The proposed strategy basically consists of two steps. First, fully coupled multiphysics finite element (FE) analyses are performed to evaluate the nonlinear static response of the device. An enhanced reduced-order model is then derived, where the global dynamic response is formulated in the state-space using lumped coefficients enriched with the information derived from the FE simulations. The electromechanical response of piezoelectric beams under forced vibrations is studied by means of the proposed approach, which is also validated by comparing numerical predictions with some experimental results. Such numerical and experimental investigations have been carried out with the main aim of studying the influence of material and geometrical parameters on the global nonlinear response. The advantage of the presented approach is that the overall computational and experimental efforts are significantly reduced while preserving a satisfactory accuracy in the assessment of the global behavior
Analysis of piezoelectric energy harvester under modulated and filtered white Gaussian noise
No full textThis paper proposes a comprehensive method for the electromechanical probabilistic analysis of piezoelectric energy harvesters subjected to modulated and filtered white Gaussian noise (WGN) at the base. Specifically, the dynamic excitation is simulated by means of an amplitude-modulated WGN, which is filtered through the Clough-Penzien filter. The considered piezoelectric harvester is a cantilever bimorph modeled as Euler-Bernoulli beam with a concentrated mass at the free-end, and its global behavior is approximated by the fundamental vibration mode (which is tuned with the dominant frequency of the dynamic input). A resistive electrical load is considered in the circuit. Once the Lyapunov equation of the coupled electromechanical problem has been formulated, an original and efficient semi-analytical procedure is proposed to estimate mean and standard deviation of the electrical energy extracted from the piezoelectric layers
- …
