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Dynamic modeling and actuation performances of donut-HASEL actuators
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DOI:10.1088/1361-665X/ae5b06.png)
Abstract
En 中文
Soft actuators are a core technology for enhancing the adaptability of robots to complex environments and ensuring safety in human–machine interactions. However, existing soft actuator types have slow response times or rely on bulky external devices. The emerging donut hydraulically amplified self-healing electrostatic (donut-HASEL) actuator can successfully overcome these challenges. However, existing simulations of the donut-HASEL focus mainly on static analyses, with no available dynamic models and dynamic performance analysis, limiting both research and application. This study was aimed at bridging this information gap by establishing a dynamic finite element (FE) modeling framework of the donut-HASEL actuator. The viscoelasticity of biaxially oriented polypropylene film and the dynamic viscosity of the dielectric liquid were incorporated into the model. Subsequently, the static actuation capabilities and dynamic performances of the donut-HASEL actuator were evaluated. The model effectively predicted both the nonlinear static and dynamic characteristics of the donut-HASEL actuator. Simplified dynamic models were established based on the dynamic responses obtained from FE analysis. Furthermore, the static actuation capabilities and dynamic performance of the nine-layer stacked donut-HASEL actuator were experimentally compared with those of pneumatic bowl of the same size and with the same free deformation. The static actuation capability of a nine-layer stacked donut-HASEL at 9 kV was found comparable to that of a pneumatic bowl of the same size under an air pressure of 7 kPa, while its operational bandwidth reaches 18 Hz, significantly higher than the 4 Hz bandwidth of the pneumatic bowl. These findings provide a technical foundation for design optimization and control of donut-HASEL actuators.
Keywords:
donut-HASEL actuator
dynamic modeling
finite element analysis
viscoelasticity
actuation performance
Journal
IF:
3.8
Papers:
8.5K
Citations:
2.5W
