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Automated Ortho- Planar Spring Design for Vibration Energy Harvesters
Mid Sweden University, Faculty of Science, Technology and Media, Department of Computer and Electrical Engineering (2023-).ORCID iD: 0000-0003-3423-2806
Mid Sweden University, Faculty of Science, Technology and Media, Department of Computer and Electrical Engineering (2023-).ORCID iD: 0000-0003-3222-7165
Mid Sweden University, Faculty of Science, Technology and Media, Department of Computer and Electrical Engineering (2023-).ORCID iD: 0000-0001-9572-3639
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2024 (English)In: 2024 IEEE Sensors Applications Symposium, SAS 2024 - Proceedings, IEEE conference proceedings, 2024Conference paper, Published paper (Refereed)
Abstract [en]

Energy harvesting has been proposed to support or replace battery-based energy supplies in low-power loT systems. However, manual design and optimization is currently required to implement energy harvesters. This implies significant time and cost requirements, reducing the competitiveness of energy harvesting solutions in many applications. In this paper, we propose and study a method for the automated design of ortho-planar springs in vibration energy harvesters. The proposed method uses a Python tool that has been developed to translate parametric descriptions of the spring into 2D and 3D spring CAD models. The tool is combined with a black-box optimization algorithm in order to identify optimized spring parameters. An evaluation of the proposed method on a case study of an electromagnetic vibration energy harvester demonstrates that the approach successfully results in spring designs that perform well in the energy harvesting application. Consequently, the requirement of expert competence to adjust an energy harvester to new application constraints is significantly reduced, contributing to the availability and competitiveness of energy harvesting solutions in real world applications. 

Place, publisher, year, edition, pages
IEEE conference proceedings, 2024.
Keywords [en]
design automation, low-power sensing systems, ortho-planar springs, vibration energy harvesting
National Category
Computational Mathematics
Identifiers
URN: urn:nbn:se:miun:diva-52590DOI: 10.1109/SAS60918.2024.10636429ISI: 001304520300028Scopus ID: 2-s2.0-85203713371ISBN: 9798350369250 (print)OAI: oai:DiVA.org:miun-52590DiVA, id: diva2:1900638
Conference
2024 IEEE Sensors Applications Symposium, SAS 2024 - Proceedings
Available from: 2024-09-24 Created: 2024-09-24 Last updated: 2024-11-25Bibliographically approved

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Phan, TraXu, YeOelmann, BengtBader, Sebastian

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