Abstract
This paper studies the effect of electromagnetic damping ratio on the optimum load resistance of an electromagnetic vibration energy harvester. A mathematical model describing the power output of the harvester was derived and analyzed. It was found that for cases where the electromagnetic damping is much lower than the mechanical damping of the harvester, the optimum load resistance value is equal to the coil resistance value. However, if the electromagnetic damping is high, then the optimum load resistance does not equal to coil resistance. In addition, this optimum value is not necessarily obtained when the electromagnetic damping is equal to the mechanical damping. For this case, the optimum value will depend on the mechanical damping ratio, electromagnetic damping ratio, coil resistance and load resistance. A good correlation was observed between the mathematical model and experimental measurements.
| Original language | English |
|---|---|
| Title of host publication | 2nd International Conference on Smart Grid and Smart Cities, ICSGSC 2018 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 127-132 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781538681022 |
| DOIs | |
| Publication status | Published - 20 Nov 2018 |
| Externally published | Yes |
| Event | 2nd International Conference on Smart Grid and Smart Cities, ICSGSC 2018 - Kuala Lumpur, Malaysia Duration: 12 Aug 2018 → 14 Aug 2018 |
Publication series
| Name | 2nd International Conference on Smart Grid and Smart Cities, ICSGSC 2018 |
|---|
Conference
| Conference | 2nd International Conference on Smart Grid and Smart Cities, ICSGSC 2018 |
|---|---|
| Country/Territory | Malaysia |
| City | Kuala Lumpur |
| Period | 12/08/18 → 14/08/18 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 11 Sustainable Cities and Communities
Free Keywords
- electromagnetic damping ratio
- load resistance
- power
- vibration energy harvester
ASJC Scopus subject areas
- Artificial Intelligence
- Energy Engineering and Power Technology
- Renewable Energy, Sustainability and the Environment
- Waste Management and Disposal
- Water Science and Technology
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