Please use this identifier to cite or link to this item: doi:10.22028/D291-30919
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Title: An accurate dynamic model for polycrystalline shape memory alloy wire actuators and sensors
Author(s): Rizzello, Gianluca
Mandolino, Michele A.
Schmidt, Marvin
Naso, David
Seelecke, Stefan
Language: English
Title: Smart materials and structures
Volume: 28
Issue: 2
Pages: 20
Publisher/Platform: IOP Publishing
Year of Publication: 2019
Publikation type: Journal Article
Abstract: Thermal shape memory alloy (SMA) wires exhibit a mechanical hysteresis of which the shape depends on both temperature and loading rate. Commercially available actuator wires typically exhibit polycrystalline behavior, which also depends on training effects. Polycrystallinity may lead to complex hysteresis loops, differing substantially from standard box shapes often employed in modeling attempts. In addition, actuation often results in loading trajectories leading through the interior of the hysteresis, making accurate modeling and control of SMA systems a highly challenging task. In this paper, we present a novel dynamic model for polycrystalline SMA actuator wires based on a modified version of the Müller–Achenbach–Seelecke model. The model permits to predict time evolution of stress and resistance of a one-dimensional SMA wire under arbitrary input strain and Joule heating profiles. The constitutive equations are developed by properly exploiting the concept of a representative single-crystal, resulting in an optimal trade-off between physical interpretation and computational efficiency. After developing constitutive model equations, experimental validation is performed by means of two case studies, given by a superelastic NiTi wire and a quasi-plastic NiTi wire, respectively. The experiments are intended to illustrate the model capabilities in predicting internal hysteresis loops, loading rate effects, as well as actuation and sensing behavior at the same time. A remarkable accuracy is observed in all of the investigated experimental scenarios, making the model particularly suitable for high-precision control and self-sensing applications.
DOI of the first publication: 10.1088/1361-665X/aae3b8
URL of the first publication:
Link to this record: hdl:20.500.11880/29132
ISSN: 0964-1726
Date of registration: 12-May-2020
Faculty: NT - Naturwissenschaftlich- Technische Fakultät
Department: NT - Systems Engineering
Professorship: NT - Prof. Dr. Stefan Seelecke
Collections:UniBib – Die Universitätsbibliographie

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