Skip to main content

Advertisement

SpringerLink
Log in

Modelling and Optimization of a Magnetic Spring Based Electromagnetic Vibration Energy Harvester

  • Original Article
  • Published:
Journal of Electrical Engineering & Technology Aims and scope Submit manuscript

Abstract

This paper presents the development of an AA battery size electromagnetic vibration energy harvester with an aim to maximize the output power density. A tube shape and stacked opposing permanent magnets with magnetic spring were used to suit the shape constraint as well as to achieve high flux linkages. An initial prototype of electromagnetic vibration harvester with AA battery size was built and tested on a controllable shaker to obtain its output voltage and power level at different frequencies for fixed accelerations. A single magnet was fixed at the bottom of the harvester to provide levitation force in this development in order to lower the resonant frequency. A special time-domain based analytical model was also developed using both Finite Element Analysis and Simulink simulation. The time-domain analytical model is easier to implement than other frequency domain based analytical models which generally applied in literatures for modelling of the electromagnetic vibration energy harvesters. The analytical model was verified by the measured results obtained from the initial prototype. The validated analytical model was successfully applied to optimize the harvester. Two more generator prototypes were further built and tested after the optimization study. The optimized harvester using three stacked opposing permanent magnets could achieve a normalized power density of 12,655 μWcm−3 g−2 at 9.9 Hz frequency with 0.22 g acceleration, which is significantly higher than other reported electromagnetic vibration energy harvesters.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21

Similar content being viewed by others

References

  1. Wang Y, Zhang Q, Zhao L, Kim ES (2017) Non-resonant electromagnetic broad-band vibration-energy harvester based on self-assembled ferrofluid liquid bearing. J MEMS 4:809–819

    Article  Google Scholar 

  2. Gutierrez M et al (2015) Design and characterization of a low frequency 2-dimensional magnetic levitation kinetic energy harvester. Sens Actuators A Phys 236:1–10

    Article  Google Scholar 

  3. Berdy DF, Valentino DJ, Peroulis D (2014) Design and optimization of a magnetically sprung block magnet vibration energy harvester. Sens Actuators A Phys 218:69–79

    Article  Google Scholar 

  4. Saha CR et al (2008) Electromagnetic generator for harvesting energy from human motion. Sens Actuators A 1:248–253

    Article  MathSciNet  Google Scholar 

  5. Saha CR et al (2006) Optimization of an electromagnetic energy harvesting device. IEEE Trans Magn 10:3509–3511

    Article  Google Scholar 

  6. Halim MA, Kim DH, Park JY (2016) Low frequency vibration energy harvester using stopper-engaged dynamic magnifier for increased power and wide bandwidth. J Electr Eng Technology 3:707–714

    Article  Google Scholar 

  7. Khan FU, Iqbal M (2018) Electromagnetic bridge energy harvester utilizing bridge’s vibrations and ambient wind for wireless sensor node application. J Sens 1–18

  8. Khan FU, Ahmad I (2016) Review of energy harvesters utilizing bridge vibrations. Shock Vib 1–21

  9. Halim MA et al (2016) A miniaturized electromagnetic vibration energy harvester using flux-guided magnet stacks for human-body-induced motion. Sens Actuators A Phys 249:23–31

    Article  Google Scholar 

  10. Kurt E, Kale MM, Akbaba S, Bizon N (2018) Analytical and experimental studies on a new linear energy harvester. Can J Phys 96:727–7330

    Article  Google Scholar 

  11. Wang W et al (2017) Magnetic-spring based energy harvesting from human motions: design, modeling and experiments. Energy Convers Manag 132:189–197

    Article  Google Scholar 

  12. Chae SH et al (2017) Electromagnetic linear vibration energy harvester using sliding permanent magnet array and ferrofluid as a lubricant. Micromachines-Basel 10:288

    Article  Google Scholar 

  13. Drezet C, Kacem N, Bouhaddi N (2018) Design of a nonlinear energy harvester based on high static low dynamic stiffness for low frequency random vibrations. Sens Actuators A Phys 283:54–64

    Article  Google Scholar 

  14. Sun K, Liu G, Xu X, Hou ZX (2012) Nonlinear resonant generator for harvesting energy from human wrist vertical shaking. Appl Mech Mater 128–129:923–927

    Google Scholar 

  15. Shirvanimoghaddam M et al (2019) Towards a green and self-powered internet of things using piezoelectric energy harvesting. IEEE Access 7:94533–94556

    Article  Google Scholar 

  16. Khaligh A, Zeng P, Zheng C (2010) Kinetic energy harvesting using piezoelectric and electromagnetic technologies-state of the art. IEEE Trans Ind Electron 3:850–860

    Article  Google Scholar 

  17. Xia H, Xia Y, Ye Y, Qian L, Shi G, Chen R (2018) Analysis and simulation of synchronous electric charge partial extraction technique for efficient piezoelectric energy harvesting. IEEE Sens J 15:6235–6244

    Article  Google Scholar 

  18. Roundy S, Zhang Y (2005) Toward self-tuning adaptive vibration based micro-generators. In: AlSarawi SF (ed) Proceedings of the society of photo-optical instrumentation engineers (SPIE), vol 5649. pp 373–384

  19. Wu Z et al (2020) Largely enhanced electrostatic generator based on a bipolar electret charged by patterned contact micro-discharge and optimized substrates. Nano Energy 71:104602

    Article  Google Scholar 

  20. Zhang Y et al (2018) Micro electrostatic energy harvester with both broad bandwidth and high normalized power density. Appl Energ 212:362–371

    Article  Google Scholar 

  21. Sadowski S, Spachos P (2018) Solar-powered smart agricultural monitoring system using internet of things devices

  22. Tang S et al (2012) Smartmote: energy and voi aware solar-powered sensor network design for environment monitoring

  23. Wang C et al (2018) Combining solar energy harvesting with wireless charging for hybrid wireless sensor networks. IEEE Trans Mob Comput 3:560–576

    Article  Google Scholar 

  24. Wang Y et al (2019) Flexible thermoelectric materials and generators: challenges and innovations. Adv Mater 31:180791629

    Google Scholar 

  25. Guo X et al (2020) A new hybrid system composed of high-temperature proton exchange fuel cell and two-stage thermoelectric generator with Thomson effect: energy and exergy analyses. Energy 195:117000

    Article  Google Scholar 

  26. Saha CR, Donnell TO, Wang N, McCloskey P (2008) Electromagnetic generator for harvesting energy from human motion. Sens Actuators A 1:248–253

    Article  Google Scholar 

  27. Wu S et al (2017) An electromagnetic wearable 3-DoF resonance human body motion energy harvester using ferrofluid as a lubricant. Appl Energy 197:364–374

    Article  Google Scholar 

  28. Pan Y et al (2019) Modeling and field-test of a compact electromagnetic energy harvester for railroad transportation. Appl Energy 247:309–321

    Article  Google Scholar 

  29. Lin T et al (2018) Modeling and field testing of an electromagnetic energy harvester for rail tracks with anchorless mounting. Appl Energy 213:219–226

    Article  Google Scholar 

  30. Wang S, Ke Y, Huang P, Hsieh P (2018) Electromagnetic energy harvester interface design for wearable application. IEEE Trans Circ-II 5SI 65:667–671

    Google Scholar 

  31. Green PL et al (2013) On the identification and modelling of friction in a randomly excited energy harvester. J Sound Vib 19:4696–4708

    Article  Google Scholar 

  32. http://www.industrycortex.com/datasheets/profile/1001410661, VEH-460

Download references

Funding

Partial financial support from General Scientific Research Project from Zhejiang Department of Education (Grant No. Y201942330) and Zhejiang Provincial Natural Science Foundation [Grant No. LD21F040001].

Author information

Authors and Affiliations

  1. School of Electronics and Information Engineering, Hangzhou Dianzi University, Hangzhou, China

    Haojun Liao, Yu Pang, Ciaran Feeney, Zhengmin Zhang & Ningning Wang

  2. Department of Computing, Electronics and Mathematics, Coventry University, Coventry, UK

    Chitta Saha

  3. School of Cyberspace, Hangzhou Dianzi University, Hangzhou, China

    Tingcong Ye

Authors
  1. Haojun Liao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tingcong Ye
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yu Pang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ciaran Feeney
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Lei Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Zhengmin Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Chitta Saha
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ningning Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by HL and NW. The first draft of the manuscript was written by HL and NW, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Tingcong Ye or Ningning Wang.

Ethics declarations

Conflict of interest

The authors have no conflicts of interest to declare that are relevant to the content of this article.

Data Availability

All authors confirm that all data and materials support the published claims and comply with field standards.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liao, H., Ye, T., Pang, Y. et al. Modelling and Optimization of a Magnetic Spring Based Electromagnetic Vibration Energy Harvester. J. Electr. Eng. Technol. 17, 463–474 (2022). https://doi.org/10.1007/s42835-021-00904-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s42835-021-00904-4

Keywords

Search

Navigation