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Titel: A Physics-Based Hybrid Dynamical Model of Hysteresis in Polycrystalline Shape Memory Alloy Wire Transducers
VerfasserIn: Mandolino, Michele A.
Scholtes, Dominik
Ferrante, Francesco
Rizzello, Gianluca
Sprache: Englisch
Titel: IEEE/ASME Transactions on Mechatronics
Bandnummer: 28
Heft: 5
Seiten: 2529-2540
Verlag/Plattform: IEEE
Erscheinungsjahr: 2023
Freie Schlagwörter: Hybrid systems
hysteresis
minor loops
modeling
polycrystalline
shape memory alloy (SMA) wire actuator
DDC-Sachgruppe: 500 Naturwissenschaften
Dokumenttyp: Journalartikel / Zeitschriftenartikel
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 der Erstveröffentlichung: 10.1109/TMECH.2023.3253250
URL der Erstveröffentlichung: https://ieeexplore.ieee.org/document/10081109
Link zu diesem Datensatz: 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
Datum des Eintrags: 7-Nov-2023
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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