Please use this identifier to cite or link to this item: doi:10.22028/D291-40960
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Title: A Physics-Based Hybrid Dynamical Model of Hysteresis in Polycrystalline Shape Memory Alloy Wire Transducers
Author(s): Mandolino, Michele A.
Scholtes, Dominik
Ferrante, Francesco
Rizzello, Gianluca
Language: English
Title: IEEE/ASME Transactions on Mechatronics
Volume: 28
Issue: 5
Pages: 2529-2540
Publisher/Platform: IEEE
Year of Publication: 2023
Free key words: Hybrid systems
hysteresis
minor loops
modeling
polycrystalline
shape memory alloy (SMA) wire actuator
DDC notations: 500 Science
Publikation type: Journal Article
Abstract: Shape memory alloys (SMAs) are a class of smart materials that exhibit a macroscopic contraction of up to 5% when heated via an electric current. This effect can be exploited for the development of novel unconventional actuators. Despite having many features such as compactness, lightweight, and high energy density, commercial SMA wires are characterized by a highly nonlinear behavior, which manifests itself as a load-, temperature-, and rate-dependent hysteresis exhibiting a complex shape and minor loops. Accurate modeling and compensation of such hysteresis are fundamental for the development of highperformance SMA applications. In this work, we propose a new dynamical model to describe the complex hysteresis of polycrystalline SMA wires. The approach is based on a reformulation of the Müller–Achenbach–Seelecke model for uniaxial SMA wires within a hybrid dynamical framework. In this way, we can significantly reduce the numerical complexity and computation time without losing accuracy and physical interpretability. After describing the model, an extensive experimental validation campaign is carried out on a 75-µm diameter SMA wire specimen. The new hybrid model will pave the development of hybrid controllers and observers for SMA actuators.
DOI of the first publication: 10.1109/TMECH.2023.3253250
URL of the first publication: https://ieeexplore.ieee.org/document/10081109
Link to this record: urn:nbn:de:bsz:291--ds-409606
hdl:20.500.11880/36776
http://dx.doi.org/10.22028/D291-40960
ISSN: 1941-014X
1083-4435
Date of registration: 7-Nov-2023
Faculty: NT - Naturwissenschaftlich- Technische Fakultät
Department: NT - Systems Engineering
Professorship: NT - Prof. Dr. Stefan Seelecke
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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