Behavioral modeling of a piezoelectric harvester with adaptive energy-investment for improved battery charging
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Behavioral modeling of a piezoelectric harvester with adaptive energyinvestment for improved battery charging Tales Luiz Bortolin1 • Andre´ Luiz Aita2 Received: 6 April 2020 / Revised: 30 June 2020 / Accepted: 21 August 2020 Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract This work describes the behavior of a piezoelectric energy harvesting system that uses a single inductor and the concept of energy investment for the whole of building a behavioral model for the harvester and a high-level system analysis approach. The harvester modules and control were specified and described in Verilog-A to fully model the energy harvester operation. Simulation results have shown the harvesting mechanism based on the concept of energy-investment and model accuracy, and the effect of the invested energy on the battery charging profile, highlighting the trade-off a constant energy investment time poses to the harvester, unable to meet the requirements a non-constant input vibration sets to system. An adaptive energy investment time based on a P&O algorithm was proposed to cope with this trade-off and added to the harvester model. Performed simulations with adaptive energy investment have shown improved energy harvesting, and that such improvement increases as the input power increases, since the system can tune the energy investing mechanism to the input vibrations. Keywords Piezoelectric energy harvesters Energy-investing harvesters Verilog-A behavioral modeling and simulation Perturb and observe algorithm
1 Introduction The same technological evolution that allows the design of continuously smaller micro-sensors and microcircuits for e.g. IoT (Internet of Things), also imposes limitations to their operation, as the batteries required to supply them are also very small, with very limited energy capacity [1]. Although these microcircuits might be designed to work with an ultra-low power consumption, this only helps to extend their operating life-time, without however eliminating the need to replace the source of energy, eventually [2]. Since the replacement of these batteries is impractical & Andre´ Luiz Aita [email protected] Tales Luiz Bortolin [email protected] 1
Post-graduation Course on Computer Science - PPGCC, Federal University of Santa Maria - UFSM, Santa Maria, RS, Brazil
2
Department of Electronics and Computing, Federal University of Santa Maria - UFSM, Santa Maria, RS, Brazil
in many situations due to technical reasons or costs, e.g. smart-dust or biomedical implants [3, 4], the challenge is therefore to keep these systems running autonomously. As the vibrations are abundant in many environments, solutions for electrical energy harvesting from piezoelectric transducers [5, 6] have emerged as promising alternatives [7]. And many challenges concerning the design of these circuits remain unaddressed showing a promising field of study. This work, however, instead of looking for novel circuits and solutions, contributes differently, developing a behavioral model for a particular ha
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