Transducer configurations for enhanced power density in cylindrical electromagnetic vibration energy harvesters
Bibliographic record
Abstract
• A systematic comparison of cylindrical electromagnetic VEH transducers is presented. • A novel fully enclosed back iron design is proposed to concentrate the magnetic flux. • Simulations show the novel transducer improves magnetic flux density by 74 percent. • The magnetic flux leakage is reduced by over 99 percent for the novel transducer. • Tests show a max power of 44.50 mW and 4.25m W/cm 3 power density in 1 g vibrations. Vibration energy harvesters (VEHs) convert the mechanical energy of vibrations into electrical energy and can power wireless sensor networks. However, there are challenges to overcome in the development of practical VEHs that include maximizing the converted energy and energy density. This work presents a systematic comparison of cylindrical electromagnetic VEH transducers and a novel transducer configuration to address these challenges. An enclosure and spring system was designed, and a basic single cylindrical magnet transducer was established as a baseline. Multiple transducers were developed to investigate the use of opposing magnets and back irons to concentrate the magnetic flux. A novel transducer was introduced that incorporates a fully enclosed back iron. The transducers were simulated, fabricated, and tested experimentally. Simulations showed that the novel transducer enhanced the magnetic flux density by 74 percent from 0.23 T to 0.40 T over the coil and reduced the magnetic flux leakage by over 99 percent from 0.15 T to 3.6 × 10 −5 T below the transducer. These results show that the novel transducer effectively channels the magnetic flux over the coil and nearly eliminates magnetic flux leakage. Experimental tests in vibrations of 60 Hz and 1 g RMS demonstrated a maximum power generation of 44.50 mW and a power density of 4.25 mW/cm 3 for the novel design, representing an improvement in power density of 103 percent over the basic transducer. This study demonstrates that opposing magnets and back irons can be used to enhance the power density of electromagnetic VEH transducers and improve the overall practicality of VEHs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".