Wirelessly controlled harvester/sensor of air speed
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Abstract
A wirelessly controlled self-powered multi-functional system that uses a relay to change from harvesting air flow energy to sensing its speed and vice versa is developed. Both functions are achieved through the use of the same micro-wind turbine. When the relay is in the on position, the turbine harvests the air’s kinetic energy to charge a battery. When a measurement is needed, the relay is turned off wirelessly and energy harvesting is shut down. The charged battery is then used to turn on a wirelessly controlled single board computer that controls a data acquisition system to sense the rotational speed of the turbine, which is proportional to the air speed. The system is tested and results from a broad range of wind speeds are presented and analyzed. The system presented here can be used for autonomous sensing of air speed without a need for wired connections to an external power source or batteries that need to be regularly replaced, which makes it ideal for integration within the Internet of things as a platform for a smart building system.
Keywords
Energy harvesting Harvester/sensor configuration Self-powered sensors Micro-turbine Air speed sensor1 Introduction
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.
2 Experimental setup
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.
Picture of the tested micro-turbine and DC generator
Parameters of wind turbine
Total diameter | Hub diameter | Mass | Midpoint chord |
---|---|---|---|
9 cm | 2.5 cm | 5.2 g | 3.2 cm |
Variation of the calculated mean power with the load resistance at different incident air speeds
3 Harvesting/sensing system
3.1 Harvesting power of micro-wind turbine
Figure 2 shows the variations of the harvested power from the micro-turbine with the load resistance for different flow speeds. The plots show that, for each speed, the harvested power increases at a high rate as the resistance is increased from 50 \(\Omega \) to reach a maximum near about 300 \(\Omega \). With further increase in the load resistance, the level of harvested power decreases. These results indicate that the optimal load resistance for energy harvesting is near 300 \(\Omega \). It is also important to note that as the flow speed is decreased from 8 to 6 and 4 \(\mathrm{m/s}\), the corresponding level of harvested power is decreased by one order of magnitude from about 500 \(\mathrm{mW}\) to about 200 and 50 \(\mathrm{mW}\).
Measured open and closed circuit voltages as a function of the flow speed. The closed circuit voltage was obtained using a load resistance of 300 \(\Omega \)
When charging a battery, the output voltage of the turbine would be smaller than that of the open circuit voltage, because the battery acts like a damper by drawing energy from the turbine. Therefore, the voltage used to charge the battery cannot be directly related to the wind speed, because it depends on the battery characteristics and its charge level. On the other hand, the open circuit voltage is directly related to the wind speed.
3.2 Design of system
Functional system diagram of the air speed harvester/sensor
Picture of the connected components in the experimental setup
Time series of the voltage as the system function is changed between charging and sensing modes. Results are presented for five different incident air speeds
3.3 Testing and analysis
Variations of the measured mean power and charging current at different air speeds
Comparison of the variation of the open circuit voltage as obtained from the experiments and measurements
Assessment of the system’s performance must also be based on the levels of harvested power and charging current. The variations of the mean values of these quantities with the incident air speed are plotted in Fig. 7. The plots show that the charging current increases from about 2 \(\mathrm{mA}\) at 3 m/s to 85.6 \(\mathrm{mA}\) at 8 \(\mathrm{m/s}\) and 153.3 \(\mathrm{mA}\) at 11 \(\mathrm{m/s}\), which indicates an increase of about two orders of magnitude in the value of the charging current as the flow speed is increased from 3 to 11 \(\mathrm{m/s}\). The power plot in the figure shows almost a similar trend for the charging power, which increases from about 12 \(\mathrm{mW}\) at flow speed of 3 \(\mathrm{m/s}\) to about 450 \(\mathrm{mW}\) at a speed of 8 \(\mathrm{m/s}\) and to about 800 \(\mathrm{mW}\) at a speed of 11 \(\mathrm{m/s}\).
A comparison of the measured mean open circuit voltage and the measured mean value of the harvester/sensor device when operating in the sensing mode as a function of the air speed is presented in Fig. 8. Based on the observed agreement, it is concluded that the measured voltage by the proposed system reflects accurately the open circuit voltage that is directly related to the air speed as discussed above.
4 Conclusions
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.
Notes
Acknowledgements
Muhammad Hajj acknowledges the support of the Center for Energy Harvesting Materials and Systems and the National Science Foundation under Grant 1035042.
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