Instantaneous peak 2.1 W-level hybrid energy harvesting from human motions for self-charging battery-powered electronics

doi:10.1016/j.nanoen.2020.105629

Nano Energy

Volume 81, March 2021, 105629

https://doi.org/10.1016/j.nanoen.2020.105629 Get rights and content

Highlights

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Novel hybridization of high-performance piezo stack and electromagnetic generators.
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Adopting abrupt magnetic flux density change in the electromagnetic generator.
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Matched impedance of piezo generator lowered to 100 Ω by frequency conversion effect.
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Total instantaneous power reaching 2.1 W of a millimeter-size configuration.
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Achieving fast charging towards a 180mAh Li-on battery based on running motions.

Abstract

In this article, we report a wearable millimeter-size energy generator that yields instantaneous power of 2.1 W level from kinetic energy of human running motions. The generator, with a hybridization of piezoelectric and electromagnetic transductions, integrates mainly two major novel techniques: impact induced frequency up conversion effect for the piezoelectric generation and abrupt magnetic flux density change for the electromagnetic generation. The generator proves to be able to effectively harness energy from human motions, producing a power density over one order of magnitude higher than that of state-of-the-art work. This result is further validated by the charging performance, i.e. high charging rate and voltage into mF-level capacitors. Moreover, this wearable generator demonstrates the capability to charge a Li-on battery in dozens of minutes. This work can be of much significance for the development of self-charging battery powered wearable electronic devices.

Graphical Abstract

Introduction

The last two decades have witnessed booming development of wearable electronic devices powered by batteries [1], [2]. An increasing number of sensors are getting integrated into the devices, e.g. GPS tracking, health monitoring, and communications. More feature embedment requires more power consumption, posing more and more challenges in battery lifespan. Researchers have proposed harvesting kinetic energy into electricity from wearers based on transduction mechanisms including piezoelectric [3], [4], [5], [6], electromagnetic [7], [8], [9], triboelectric [10], [11] and hybrid [12], [13], [14], [15], expecting to charge the battery with harvested electric power. The kinetic energy can be exemplified as running motion and walking characterized as large-amplitude (millimeter level) and ultra-low-frequency (usually lower than 5 Hz) vibrations [16]. Harvesting vibration energy of such frequency demands that the resonant frequency of harvesters should be ultra-low to yield the best electric outputs such as power and voltage. A critical factor that determines the battery charging rate is power density [17], i.e. power/total volume, of the harvesters. The power density of most proposed harvesters can only reach a few hundred [18] microwatt/cm³. Various methods and techniques have been proposed to improve power density, such as variation of the configuration [19], [20], [21], [22], [23], [24] and excitation angles [25]. Nevertheless, very limited number of researchers have investigated the feasibilities of charging batteries of small capacity or of long charging time with energy harvesters and proposed circuits based on different configurations, e.g. a hybrid generator charging a 0.4mAh coin battery in 15 min [26], a piezoelectric energy harvester (PEH) harnessing cardiac energy that charged a coin cell in 3 h [27], a piezoelectric plate charging different sized batteries and a homemade Li-ion battery charged within 32 min [28]. This rareness can be mostly attributed to unsatisfying charging power which can hardly breach the battery charging threshold [29]. Accordingly, seeking breakthrough in power density has been a heated challenge in the field of energy harvesting for further development of self-charging battery-powered wearable electronic devices.

Section snippets

Configuration of the generator

Many hybrid energy harvesters have been proposed and yet much further work is still needed before the harvesters are able to meet the power requirements of wearable devices of most sensors and electronics with real-time signal transmission functions under low-frequency excitations. To enhance the power density of the harvesters, an alternative arrangement of magnet in an array was proposed by Kim et al. in 2016 [30]. Later, we investigated the power density potential of such arranged planar

Discussion and conclusion

Most energy harvesters, PEHs, EMEHs or hybrid ones in millimeter scale, generated power of milliwatt level [4]. The power density is defined as P.D. = power/volume, namely how much power can be generated per unit volume. We then compared the P.D. from this hybrid scheme with that of state-of-the-art work and displayed the results in Table 1. Most of the referred harvesters yield lower than 6.5 mW/cm³ and work at the resonant frequency of dozens of or even over one hundred hertz. The

Fabrication of the prototype

The piezoelectric stack was designed by our group with piezo ceramics (PZT-5 H) as the core material. The fabrication was contracted to Core Tomorrow Science and Technology Co., Ltd. The stack consists of approximately 180 layers and each the thickness of each layer is 10 µm. The material of the electrode is silver. The rest connecting components were fabricated by CNC machining and 3D printing.

COMSOL simulation

The flux density distribution of two adjacent magnets, as plotted in Fig. 1(d), was calculated using

CRediT authorship contribution statement

Zhongjie Li, Hani Naguib conceived the idea. Zhongjie Li wrote the paper, formulated the magnetic field, and conducted the experiments. Jun Luo and Shaorong Xie analyzed the data and provided financial support. Zhibing Xu and Yan Peng proposed and helped fabricated the configuration. Dong Zhang simulated the model. Peilun Yin designed the piezoelectric stack. Huaya Pu and Yan Peng provided experiment equipment and helped with data processing. Zhengbao Yang designed the experiments. Zhengbao

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

Research was supported by The National Science Fund for Distinguished Young Scholars (No.: 61625304) and the National Natural Science Foundation of China (No.: 61827812, No.: 1813217).

Zhongjie Li received the bachelor’s and master’s degrees in engineering at Harbin Institute of Technology, China in 2013 and 2015, respectively. He obtained his Ph.D. at the University of Toronto, Toronto, Canada, concentrating on vibration energy harvesting using piezoelectric materials. He is now an assistant professor at Shanghai University with research focuses on self-powered systems for wearable electronics, energy harvesting techniques and smart functional materials.

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Jun Luo received the B.S. and M.S. degrees in mechanical engineering from Henan Polytechnic University in 1994 and 1997, respectively, and the Ph.D. degree from the Research Institute of Robotics, Shanghai Jiao Tong University in 2000. He is a professor in the School of Mechatronics Engineering and Automation, Shanghai University. His research areas include energy harvesting, robot sensing, sensors, mechatronics, and man-machine interfaces.

Shaorong Xie is Dean of School of Computer Engineering and Science, Director of Engineering Research Center of Marine Intelligent Unmanned System Equipment of the Ministry of Education, and Associate Dean of Unmanned Surface Vehicle Engineering Research Institute at Shanghai University. She received her Ph.D. from the Institute of Intelligent Machines, Tianjin University and the Institute of Robotics and Information Automation, Nankai University in 2001. Her main research areas are intelligent and autonomous robots, including energy harvesting techniques, cooperative control technology of multi-autonomous robots, and intelligent systems.

Liming Xin received his B.Sc. (Eng.) from Jilin University (2004), and Ph.D. from Chinese Academy of Science (2009). He completed a Postdoctoral Fellowship at the University of Toronto (2015–2019) before working at the University of Toronto as a research associate in 2019. Liming Xin’s research is focus on robotics. In recent years, he has extended his research to energy harvesting and biomedical instruments.

Hengyu Guo received his B. S. and Ph.D. degree in Applied Physics from Chongqing University, China. Then he worked as a postdoctoral fellow in Zhong Lin Wang’s group, Georgia Institute of Technology, US. Now he is a professor in department of physics, Chongqing University, China. His current research interest is triboelectric nanogenerator based energy and sensor systems.

Huayan Pu received the M.Sc. and Ph.D. degrees in mechatronics engineering from the Huazhong University of Science and Technology, Wuhan, China, in 2007 and 2011, respectively. She is currently a Professor with the School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China. Her current research interests include energy harvesting, vibration controlling and robotics.

Peilun Yin received the B.S. degree in Electrical Engineering and Automation from Shanghai University in 2018. Currently, he is pursuing M.S. degree of Electrical Engineering at Shanghai University. His research interests include piezoelectric, electromagnetic, and triboelectric energy harvesting, flexible energy materials, and vibration controlling.

Zhibing Xu received his B.E. from Shanghai University (2018). He is currently completing his master's degree at Shanghai University since 2018. Zhibing Xu’s research is focus on piezoelectric energy harvesting.

Dong Zhang is a M.E. candidate in School of Mechatronic Engineering and Automation, Shanghai University, China. His current research interests mainly include harvesting energy from ambient mechanical vibration and human motion, electromagnetic energy harvesters, triboelectric nanogenerators, hybrid energy harvesters and self-powered applications.

Yan Peng received the Ph.D. degree in pattern recognition and intelligent systems from Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China, in 2009. She is currently a Professor with Shanghai University, Shanghai, China, where she is the Dean of the Research Institute of USV Engineering. Her current research interests include modeling and control of energy harvesting, unmanned surface vehicles, field robotics, and locomotion systems. Her work has been supported by The National Youth Talent Support Program.

Zhengbao Yang received the B.Eng. degree in mechanical design and mechatronics from the Harbin Institute of Technology, Harbin, China, in 2012, and the Ph.D. degree in mechanical engineering from the University of Toronto, Toronto, ON, Canada, in 2016. Since 2017, he has been an Assistant Professor with the City University of Hong Kong. His research interests include vibrations and mechatronics with a special focus on the development of smart structures and dynamical systems for energy harvesters, sensors and actuators.

Hani Naguib received the Ph.D. degree in mechanical engineering from the University of Toronto, Toronto, ON, Canada. He is a Professor and an Associate Chair with the Department of Mechanical and Industrial Engineering, the University of Toronto and the Director of the Toronto Institute for Advanced Manufacturing. His research interest includes the area of energy harvesting, smart and active materials, nanostructured polymers and composites.

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Instantaneous peak 2.1 W-level hybrid energy harvesting from human motions for self-charging battery-powered electronics

Highlights

Abstract

Graphical Abstract

Introduction

Section snippets

Configuration of the generator

Discussion and conclusion

Fabrication of the prototype

COMSOL simulation

CRediT authorship contribution statement

Declaration of Competing Interest

Acknowledgements

Energy Convers. Manag.

Compos. Struct.

Energy Convers. Manag.

Sens. Actuators A Phys.

Nat. Commun.

Nano Energy

Joule

Energy Convers. Manag.

J. Mech. Phys. Solids

Energy Convers. Manag.

Nano Energy

Energy Convers. Manag.

Energy Convers. Manag.

Sens. Actuators A Phys.

Energy Convers. Manag.

Appl. Energy

Sens. Actuators A Phys.

Wearable energy-dense and power-dense supercapacitor yarns enabled by scalable graphene–metallic textile composite electrodes

Nat. Commun.

Large-scale pattern growth of graphene films for stretchable transparent electrodes

Nature

Piezoelectric-nanowire-enabled power source for driving wireless microelectronics

Nat. Commun.

A review of energy harvesting using piezoelectric materials: state-of-the-art a decade later (2008–2018)

Smart Mater. Struct.

Energy harvesting from human motion: exploiting swing and shock excitations

Smart Mater. Struct.

Quantifying the triboelectric series

Nat. Commun.