Wirelessly controlled harvester/sensor of air speed

Monitoring air speed is required for operation and decision-making in different applications. One application is in smart buildings where the need is to ensure proper operation of the heating, ventilation, and air conditioning system for the purpose of reducing energy and operating expenses by controlling temperature, humidity, and air flow in various zones. Another application is the need to acquire wind speed over different sections of a bridge or a high-rise building and relate those measurements to wind-induced vibrations of these structures. In these and other applications, the number of required sensors, the unavailability of power, or the location of the sensing device may preclude the options of using wired power or batteries that need to be replaced regularly. One solution is to revert to harvesting ambient wind energy and use it to power air speed sensors, wirelessly transmit data, and initiate decision-making.

Harvesting the kinetic energy of wind to operate a sensor can be achieved through a turbine or aeroelastic vibrations including flutter Erturk et al. (2010), vortex-induced vibrations Mehmood et al. (2013), and Grouthier et al. (2014) or galloping Bibo and Daqaq (2014) of bodies placed in the air stream. The level of harvested power depends on the size of the harvester, the transduction mechanism, and the air speed. Different studies have shown that air flow harvesters of few \(\mathrm{cm}^2\) in area or \(\mathrm{cm}^3\) in volume can yield power levels of 0.1–100’s \(\mathrm{mW}\) when placed in wind speeds up to 15 m/s. Rancourt et al. (2007) obtained a power level of 9.39 \(\mathrm{mW/cm}^2\) from a 4 \(\mathrm{cm}\) micro-wind turbine that operated at a speed of 11.8 \(\mathrm{m/s}\). Using a turbine that is 2.6 \(\mathrm{cm}\) in diameter, Zakaria et al. (2015) generated power levels that increased from 0.1 and 2 \(\mathrm{mW/cm}^2\) as the incident flow speed was increased from 4 to 10 \(\mathrm{m/s}\). Myers et al. (2007) proposed and optimized the performance of a small-scale piezoelectric windmill that can continuously harvest 5 \(\mathrm{mW}\) at speeds of about 5 \(\mathrm{m/s}\). Fu and Yeatman (2015) proposed and tested a piezoelectric turbine that extracts flow energy at low speeds and uses a self-regulating mechanism to harvest power at high speeds. Comparable levels of energy harvesting can be achieved also from aeroelastic vibrations. Kwon (2010) showed that a 10\(\times \)6\(\times \)3 \(\mathrm{cm}^3\) T-shaped piezoelectric cantilever can harvest 4 \(\mathrm{mW}\) from air flow at a speed of 4 \(\mathrm{m/s}\). Zakaria et al. (2015) harvested 0.17 \(\mathrm{mW}\) from sustained oscillations of a 26\(\times \)2\(\times \)0.05 \(\mathrm{cm}^3\) flexible beam when placed in an air flow with a speed of 9 \(\mathrm{m/s}\) at specific preset angles of attack. Yet, when it comes to a specific application, one must consider the output voltage and current, because these factors determine the ability of the harvester to charge a battery or to wirelessly transmit a signal across a specific platform.

Different approaches have been proposed to combine energy harvesting and sensing devices for monitoring air speed. One approach is to power the sensor with ambient energy harvested from a different source. Another approach would be to use a wind energy harvester to charge a capacitor or a battery and then use that power to operate a sensor that is different from the harvester. Liu et al. (2012) assessed the performance of a piezoelectric PZT microcantilever in terms of flow sensing and energy harvesting capability. They proposed employing one PZT microcantilever for flow sensing and integrating an array of other PZT microcantilevers to harvest enough energy from wind-induced vibrations to power the sensing microcantilever. To the authors’ knowledge, there has not been any investigation for wirelessly operating one device that can harvest the wind energy over a specific period and then use the harvested power to sense and transmit the wind speed over a different period.

In this paper, we develop a wirelessly controlled self-powered multi-functional system that harvests the air flow energy and senses and transmits its speed using a battery charged with its own harvested power. This self-powered autonomous air speed sensor eliminates the need for separate devices or components for sensing and energy harvesting and, thereby, reduces the size and cost of wireless sensing nodes. The system is controlled wirelessly through a single board computer that is also powered by the harvested energy.

For the current experiments, the need was to charge a 5 V battery that is required to power a single board computer and a relay. Towards this end, a 9-cm micro-turbine as shown in Fig. 1 was used as the energy harvester. The parameters of this turbine are presented in Table 1. The turbine was connected to a micro-DC generator that is also shown in the picture of Fig. 1.

All tests of the proposed system were performed in a suction-type open circuit wind tunnel powered by a 15-hp centrifugal fan. This fan forces the flow to pass through a square (1.5 \(\mathrm{m}\) \(\times \) 1.5 \(\mathrm{m}\)) honeycomb inlet made of straws that are 0.001 \(\mathrm{m}\) in diameter and 0.09 \(\mathrm{m}\) long. This inlet is followed by turbulence reduction screens that ensure a uniform flow with a variation across the 52 \(\mathrm{cm}\) \(\times \) 52 \(\mathrm{cm}\) square test section that is less than 2.5\(\%\) and a turbulence intensity that is less than 2\(\%\). The turbine used in these tests was placed in the center of the test section with the Pitot-static tube set 10 \(\mathrm{cm}\) away from the axis of rotation and 20 \(\mathrm{cm}\) ahead of the turbine. The flow velocity is measured with an accuracy of 70.5\(\%\) based on the reading recorded from the Pitot-static tube that uses a differential pressure scani-valve. To determine the power that can be harvested from this turbine, the generator’s output was measured using a DATAQ instruments unit. The data sampling rate was set to 2500 \(\mathrm{Hz}\) and each data segment was recorded over a period of 5 s.

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Table 1

Parameters of wind turbine

Total diameter	Hub diameter	Mass	Midpoint chord
9 cm	2.5 cm	5.2 g	3.2 cm

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A self-powered multi-functional system that uses its own harvested power to sense a voltage was designed and tested. The tested system is based on a micro-wind turbine that harvests kinetic energy of air flow to charge a battery. The battery is then used to power a wirelessly controlled single board computer that is connected to a relay and a data acquisition system. The relay is used to switch the function of the system from harvesting air flow energy to sensing its speed and vice versa. The results show that switching between the two functions is achieved smoothly. The charging voltage, power, and current as a function of the air speed were analyzed. The accuracy of the system was assessed by comparing the sensing voltage of the multi-functional system against the open circuit voltage that is directly related to the air speed.