TY - JOUR
T1 - The optimization of an electromagnetic vibration energy harvester based on developed electromagnetic damping models
AU - Hasani, Milad
AU - Irani Rahaghi, Mohsen
N1 - Funding Information:
We would like to express our great appreciation to Professor Chris Bowen (University of Bath, United Kingdom) and Dr. Masoud Hasany (Technical University of Denmark, Denmark) due to their invaluable advices in preparing the final edition of this research work. This work was partially supported by the University of Kashan, Iran under Grant 785407.
Publisher Copyright:
© 2022
PY - 2022/2/15
Y1 - 2022/2/15
N2 - The optimization of electromagnetic energy harvesters is the main goal of this work to enhance power generation performance. The optimization procedure requires a flexible computational framework to predict the characteristics of various electromagnetic energy harvesters with different architectures. The electromagnetic damping is one of the challenging topics in this field, which depends on the architecture of energy harvester, base excitation condition, and electrical resistance. In this regard, two innovative computational models were developed to predict electromagnetic damping without any dependency on experimental results. The results showed that the developed models are 270 times faster than traditional approaches such as the finite element method. The developed semi-analytical framework was implemented in the optimization procedure to enhance energy harvester performance. The optimization determined optimal characteristics for control parameters, including the number of coils turns, the configuration of winding coil, and magnets dimensions. Moreover, a prototype was constructed based on optimal characteristics derived from the optimization. The developed models were validated by experimental results and the FEM method. The experimental results indicated that the optimization presented in the current study led to significant improvements in the outputs of the optimal harvester compared to previous studies. These outputs include power 999.7 mW, normalized power 129.15 mW/g2, and power density 2.16 mW/cm3, to name a few. In addition, the middle coil measures environmental vibration as a self-powered sensor, which can be used for condition monitoring and self-tuning. These achievements make the optimized energy harvester exceptionally suitable for various applications in large-scale systems.
AB - The optimization of electromagnetic energy harvesters is the main goal of this work to enhance power generation performance. The optimization procedure requires a flexible computational framework to predict the characteristics of various electromagnetic energy harvesters with different architectures. The electromagnetic damping is one of the challenging topics in this field, which depends on the architecture of energy harvester, base excitation condition, and electrical resistance. In this regard, two innovative computational models were developed to predict electromagnetic damping without any dependency on experimental results. The results showed that the developed models are 270 times faster than traditional approaches such as the finite element method. The developed semi-analytical framework was implemented in the optimization procedure to enhance energy harvester performance. The optimization determined optimal characteristics for control parameters, including the number of coils turns, the configuration of winding coil, and magnets dimensions. Moreover, a prototype was constructed based on optimal characteristics derived from the optimization. The developed models were validated by experimental results and the FEM method. The experimental results indicated that the optimization presented in the current study led to significant improvements in the outputs of the optimal harvester compared to previous studies. These outputs include power 999.7 mW, normalized power 129.15 mW/g2, and power density 2.16 mW/cm3, to name a few. In addition, the middle coil measures environmental vibration as a self-powered sensor, which can be used for condition monitoring and self-tuning. These achievements make the optimized energy harvester exceptionally suitable for various applications in large-scale systems.
KW - Ambient vibration
KW - Damping modeling
KW - Electromagnetic energy harvesting
KW - Optimization
KW - Self-powered sensor
UR - http://www.scopus.com/inward/record.url?scp=85123770466&partnerID=8YFLogxK
U2 - 10.1016/j.enconman.2022.115271
DO - 10.1016/j.enconman.2022.115271
M3 - Journal article
AN - SCOPUS:85123770466
SN - 0196-8904
VL - 254
JO - Energy Conversion and Management
JF - Energy Conversion and Management
M1 - 115271
ER -