Kinetic energy harvesting from human walking and running using a magnetic levitation energy harvester
Introduction
Developments in wireless and low power portable electronics have led to new applications for wearable electronics in consumer products and healthcare monitoring [1], [2]. A drawback of current electronics is that battery lifetime is limited. To alleviate this problem, researchers have focused on developing devices to harvest energy from human motion and vibrations during daily activities such as walking [3]. Harvesting and converting ambient energy into electrical energy is of great interest because it can extend battery life or completely replace batteries. In vibration (or kinetic) energy harvesting, mechanical kinetic energy is converted into useful electrical energy by utilizing piezoelectric [4], [5], [6], electromagnetic [7], [8], electrostatic [9], [10], or magnetostrictive [11] transduction mechanisms.
One device well-suited for converting human kinetic energy is a magnetic levitation energy harvester [12], [13], [15], [16], [17], [18], [19], [20]. This device can achieve a very low resonant frequency, which is ideal for converting human kinetic energy into useful electric energy because human kinetic energy is concentrated at frequencies below 10 Hz. An additional advantage of the device is that there is no physical spring, thus leading to a long lifetime because the physical spring is the most common point of failure.
In this paper, we measure, for the first time, the power output of a magnetic levitation vibration energy harvester on human participants while they walk and run on a treadmill. A potential issue with magnetic levitation energy harvesters is damping of the levitating magnet due to the guide box or guiding system design. The damping likely increases in a real world application, where the energy harvester may not always be vertical and perfectly aligned with the excitation force due to different body types, gait style, and variation in device attachment. Therefore, before testing on human participants, we explore techniques to reduce damping by implementing designs with different guide rail systems and materials.
Section snippets
Magnetic levitation energy harvester
A diagram of the magnetic levitation vibration energy harvester is shown in Fig. 1. The energy harvester consists of a levitating magnet, fixed magnets, guide box and coil. The polarity of the magnets are arranged so the levitating magnet experiences a repulsive force due to the fixed magnets. In the diagram, fixed magnets are only shown on the bottom of the box, but they could also be added to both top and bottom ends of the box. When the box experiences an acceleration, the levitating magnet
Energy harvester model
The model of the energy harvester was developed in [16] and [21]. The differential equation of the model was obtained by summing the forces on the levitating magnet with the equation:
where m is the levitating magnet mass, ce(z(t)) is the electrical damping, cp is the parasitic viscous damping coefficient, FFric is parasitic dry friction damping, Fmag(z(t)) is the the magnetic force, g is gravity, y(t) is the displacement of the device frame due
Experimental results on electrodynamic shaker
The fabricated devices are shown in Fig. 4. Three different boxes were made: acrylic box without guide rail, acrylic box with guide rail, and Teflon box with guide rail. The boxes were machined using computer numeric control (CNC) machining from the respective materials. All dimensions are the same for each box, as shown in Table 1 and the 1000-turn coil was wrapped using 42 AWG (63.5 μm diameter) wire with a resistance of 450 Ω. The magnets are grade N42 Neodymium magnets.
The device was tested
Discussion of electrodynamic shaker results
The open circuit ringdown waveforms in Fig. 6 illustrate the modeled damping (Fd) for each configuration. The graphs show that the acrylic device with guide rail has lower damping than the device without the guide rail. In fact, the damping force (Fd) was reduced by almost 50%. Additionally, changing the material to Teflon further reduced damping as was expected due to its lower coefficient of friction. Therefore, in order to optimize the device performance, it is recommended that the designer
Testing on human subjects
The testing in this section was performed under the approval and guidance of Purdue University's Institutional Review Board (IRB). All procedures were followed according to the testing protocol approved by the IRB. The testing was completed at Purdue's Recreational Sports Center under the supervision of the staff at the center.
Conclusion
In this work, we have experimentally studied and compared several designs to optimize power output from a magnetic levitation vibration energy harvester and tested the optimal device on human subjects. When tested on 10 participants while walking at 3 mph, the power output averaged 71 μW with a standard deviation of 30 μW. When running at 6 mph, the power increased to 342 μW with a standard deviation of 86 μW. The model in this paper predicted the power on average within 14% of the measured power
Acknowledgments
This work was supported in part by a grant from LANDAUER Inc. (Glenwood, IL, USA) grant no. 13065978. The authors would like to thank Birck Nanotechnology Center, Herrick laboratories, and Professor Jeffrey Rhoads at Purdue for support in fabrication and testing of the devices, and all the study participants for taking time to participate in this study. Finally, the authors want to thank the staff at Purdue's Recreational Sports Complex for the use of their facilities and the wonderful support
David F. Berdy received his B.S. degree in computer engineering from Rose-Hulman Institute of Technology, Terre Haute, IN, in 2008 and his Ph.D. in Electrical Engineering from Purdue University in West Lafayette, IN in 2013. His research interests include energy harvesting, MEMS transducers, wireless systems and their applications.
References (25)
- et al.
A study of low level vibrations as a power source for wireless sensor nodes
Comp. Commun.
(2003) - et al.
Electromagnetic generator for harvesting energy from human motion
Sens. Actuators A: Phys.
(2008) - et al.
Energy harvesting from the nonlinear oscillations of magnetic levitation
J. Sound Vib.
(2009) - et al.
Multi-frequency electromagnetic energy harvester using a magnetic spring cantilever
Sens. Actuators A: Phys.
(2012) - et al.
Design and optimization of a magnetically sprung block magnet vibration energy harvester
Sensors and Actuators A: Physical
(2014) Recent developments in flexible wearable electronics for monitoring applications
Trans. Inst. Meas. Control
(2007)- et al.
Body sensor network – a wireless sensor platform for pervasive healthcare monitoring
- et al.
Energy harvesting from human and machine motion for wireless electronic devices
Proc. IEEE
(2008) - et al.
A piezoelectric vibration based generator for wireless electronics
Smart Mater. Struct.
(2004) - et al.
An experimentally validated bimorph cantilever model for piezoelectric energy harvesting from base excitations
Smart Mater. Struct.
(2009)
Low-frequency meandering piezoelectric vibration energy harvester
IEEE Trans. Ultrason. Ferroelectr. Freq. Control
Analysis of a micro-electric generator for microsystems
Proc. Int. Solid-State Sens. Actuators Conf. – TRANSDUCERS’95
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David F. Berdy received his B.S. degree in computer engineering from Rose-Hulman Institute of Technology, Terre Haute, IN, in 2008 and his Ph.D. in Electrical Engineering from Purdue University in West Lafayette, IN in 2013. His research interests include energy harvesting, MEMS transducers, wireless systems and their applications.
Daniel J. Valentino received his Ph.D. in Biomedical Physics from the University of California at Los Angeles in 1990. He was an Associate Professor of Radiology at UCLA, a founding member of the Biomedical Engineering Program at UCLA, and a founding member of the NIH-funded Center for Computational Biology. At UCLA, his research interests included imaging informatics, image processing and image databases for neuroimaging, and computational fluid dynamics for brain vascular mapping. He was the PI or co-PI on several large NIH-funded program project grants, and grants from the NSF and state of California. He is the author of over 200 peer-reviewed papers. He was the Chief Technology Officer for iCRco, Inc., where he led the research and development of new imaging devices, image processing algorithms, and image data management systems. He is currently the Vice President of Technology & Innovation for LANDAUER, Inc., where he leads the research and development of innovative new radiation detection systems and products.
Dimitrios Peroulis received his Ph.D. in Electrical Engineering from the University of Michigan at Ann Arbor in 2003. He has been with Purdue University since August 2003 where he is currently leading a group of graduate students on a variety of research projects in the areas of RF MEMS, sensing and power harvesting applications as well as RFID sensors for the health monitoring of sensitive equipment. He has been a PI or a co-PI in numerous projects funded by government agencies and industry in these areas. He is currently a key contributor in two DARPA projects at Purdue focusing on (1) very high quality (Q > 1000) RF tunable filters in mobile form factors (DARPA Analog Spectral Processing Program, Phases I, II and III) and on (2) developing comprehensive characterization methods and models for understanding the viscoelasticity/creep phenomena in high-power RF MEMS devices (DARPA M/NEMS S&T Fundamentals Program, Phases I and II). Furthermore, he is leading the experimental program on the Center for the Prediction of Reliability, Integrity and Survivability of Microsystems (PRISM) funded by the National Nuclear Security Administration. In addition, he is heading the development of the MEMS technology in a U.S. Navy project (Marines) funded under the Technology Insertion Program for Savings (TIPS) program focused on harsh-environment wireless micro-sensors for the health monitoring of aircraft engines. He has over 130 refereed journal and conference publications in the areas of microwave integrated circuits, sensors and antennas. He received the National Science Foundation CAREER award in 2008. His students have received numerous student paper awards and other student research-based scholarships. He is a Purdue University Faculty Scholar and has also received eight teaching awards including the 2010 HKN C. Holmes MacDonald Outstanding Teaching Award and the 2010 Charles B. Murphy award, which is Purdue University's highest undergraduate teaching honor.