System identification of a low-order heat transfer model for shape memory alloy wires. (June 2018)

• Record Type: Journal Article
• Authors: Wright, Cody; Bilgen, Onur
• Is Part Of: Journal of intelligent material systems and structures. Volume 29:Number 10(2018)
• Page Start: 2122
• Page End: 2136
• Publication Date: 2018-06
• Subjects: Shape memory alloy -- smart material -- heat transfer -- system identification -- parameter estimation -- modeling; Smart materials -- Periodicals; Intelligent control systems -- Periodicals; Artificial intelligence -- Periodicals; Matériaux intelligents -- Périodiques; Commande intelligente -- Périodiques; Intelligence artificielle -- Périodiques; 620.11
• DOI: 10.1177/1045389X17754260
• Languages: English
• ISSNs: 1045-389X

Abstract

Shape memory alloys exhibit a strong thermomechanical coupling. This coupling has been modeled extensively using energy-based constitutive models. Equally as important in the dynamics of shape memory alloy–based systems is the heat transfer behavior. The literature is comprehensive on parameter identification for constitutive models but is lacking in a complete resource for identification of the parameters for the heat transfer behavior. In this article, the parameters for a low-order differential equation heat transfer model are determined through experimental system identification. This is completed with two objectives in mind: keeping the order of the model low and accurately modeling the response within an acceptable tolerance. A comparison of identified model parameters to nominal values shows similar magnitudes in all parameters with exception to a significant difference in the heat transfer coefficient. For all parameters, it is shown that a methodical system identification is necessary to develop an accurate predictive model. This article details a clear method to identify the parameters of the low-order heat transfer model.