MEMS piezoelectric vibrational energy harvesters and circuits for IoT applications
Bibliographic record
Abstract
In the Internet of Things (IoT) world, more and more sensor nodes are being deployed and more mobile power sources are required. Alternative solutions to batteries are the subjects of worldwide extended research. Among the possibilities is the harvesting of energy from the ambient. A novel energy harvesting system to power wireless sensor nodes is a necessity and inevitable path, with more and more market interest. \n \nMicroelectromechnaical systems (MEMS) based piezoelectric vibrational energy harvesters (PVEH) are considered in this thesis due to their good energy densities, conversion efficiency, suitability for miniaturization and CMOS integration. Cantilever beams are favored for their relatively high average strains, low frequencies and simplicity of fabrication. Proof masses are essential in micro scale devices in order to decrease the resonance frequency and increase the strain along the beam to increase the output power. In this thesis, the effects of proof mass geometry on piezoelectric vibration energy harvesters are studied. Different geometrical dimension ratios have significant impact on the resonance frequency, e.g., beam to mass lengths, and beam to mass widths. The responses of various prototypes are studied. Furthermore, the impact of geometry on the performance of cantilever-based PVEH is investigated. Namely, rectangular and trapezoidal T-shaped designs are fabricated and tested. Optimized cross-shaped geometries are fabricated using a commercial technology PiezoMUMPs process from MEMSCAP. They are characterized for their resonant frequency, strain distribution and output power. \n \nThe output of an energy harvester is not directly suited as a power supply for circuits because of variations in its power and voltage over time, therefore a power management circuit is required. The circuit meets the requirements of responding to an input voltage that varies with the ambient conditions to generate a regulated output voltage, and the ability to power multiple outputs from a fixed input voltage. In this thesis, new design architectures for a reconfigurable circuit are considered. A charge pump which modifies dynamically the number of stages to generate a plurality of voltage levels has been designed and fabricated using a CMOS 0.13 μm technology. This provides biasing voltages for electrostatic MEMS devices. Electrostatic MEMS require relatively high and variable actuation voltages and the fabricated circuit serves this goal and attains a measured maximum output voltage of 10.1 V from a 1.2 V supply. \n \nIn this thesis, design recommendations are given and MEMS piezoelectric harvesters are implemented and validated through fabrications. T-shaped harvesters bring improvements over cantilever designs, namely the trapezoidal T-shaped structures. A cross-shaped design has the advantage of utilizing four beams and the proposed proof mass improves the performance significantly. A cross-coupled circuit rectifies the output efficiently towards an optimal energy harvesting solution.
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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 | 0.000 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".