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doi:10.22028/D291-29777
Titel: | Performance Prediction and Scaling Laws of Circular Dielectric Elastomer Membrane Actuators |
VerfasserIn: | Hau, Steffen York, Alexander Rizzello, Gianluca Seelecke, Stefan |
Sprache: | Englisch |
Titel: | Journal of mechanical design |
Bandnummer: | 140 |
Heft: | 11 |
Startseite: | 1 |
Endseite: | 12 |
Verlag/Plattform: | ASME |
Erscheinungsjahr: | 2018 |
Dokumenttyp: | Journalartikel / Zeitschriftenartikel |
Abstract: | For a number of emerging mechatronics applications, dielectric elastomers (DEs) appear as a more energy efficient, lightweight, and low-cost solution with respect to established actuation technologies based, e.g., on solenoids or pneumatic cylinders. In addition to large strain, low power consumption, and high flexibility, DE actuators (DEA) are also highly scalable. Since DE membranes can be easily manufactured in different sizes and shapes, an effective approach to scale their performance is based on properly designing the material geometry. Clearly, to perform an optimal scaling the relation between material geometry and performance has to be properly investigated. In this paper, performance scaling by means of geometry is studied for circular out-of-plane (COP) DEAs. Such actuators consist of a silicone elastomer membrane sandwiched between two electrodes (carbon black silicone mixture). DEAs with six different geometries are manufactured, and a model-based strategy is used to find an experimental relationship between geometry and electro-mechanical behavior. In addition, an effective and computationally efficient method for predicting force–displacement characteristics of different geometries is presented. The proposed method allows to easily adapt DEAs to different applications in terms of stroke and force requirement, while minimizing at the same time both characterization and prototyping effort. |
DOI der Erstveröffentlichung: | 10.1115/1.4039104 |
URL der Erstveröffentlichung: | https://asmedigitalcollection.asme.org/mechanicaldesign/article-abstract/140/11/113501/366182/Performance-Prediction-and-Scaling-Laws-of?redirectedFrom=fulltext |
Link zu diesem Datensatz: | hdl:20.500.11880/28183 http://dx.doi.org/10.22028/D291-29777 |
ISSN: | 1528-9001 1050-0472 |
Datum des Eintrags: | 24-Okt-2019 |
Fakultät: | NT - Naturwissenschaftlich- Technische Fakultät |
Fachrichtung: | NT - Systems Engineering |
Professur: | NT - Prof. Dr. Stefan Seelecke |
Sammlung: | SciDok - Der Wissenschaftsserver der Universität des Saarlandes |
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