Parameter identification of modified fractional Zener model for thermorheological materials

• The principle theory and process of parameter identification are studied.
• The detailed parameter identification procedure is given.
• CBFR-NR100N550 is utilized to test the methodology.
• The proposed approach is compared with genetic algorithm.
• The results show that this method provides an effective way to get parameters.

Parameter identification of an analytical model plays significant role in predicting the dynamic mechanical properties of thermorheological materials over wide frequency range. A deterministic parameter identification method for modified fractional Zener (MFZ) model is studied in this paper. Three of the parameters can be determined directly by deduced formulations, and the other two can be carried out by exhaustive search method within a finite search space. Firstly, parameters of MFZ model are obtained by our method using the dynamic mechanical thermal analysis (DMTA) data. Secondly, the master curves of this model are calculated. The calculated master curves of MFZ model with identified parameters agree well with the DMTA data's master curves obtained by time–temperature superposition principle (TTSP). Finally, the proposed algorithm is compared with genetic algorithm (GA). The results indicate that the presented parameter identification approach of MFZ model is effective. The investigation in this paper has some significant meanings for the industrial applications of thermorheological materials.