Nonlinear modeling of piezoelectric stack actuators with flexure based displacement amplifier mechanisms

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2022-8-26
Yurdakul, Ozan
In this thesis, modeling methods for piezoelectric stack actuators (PSA) are studied. Both linear and nonlinear modeling methodologies are provided. FEM which is derived from constitutive piezoelectric equations is implemented to model linear behavior of piezoelectricity. Validation of the FEM model is performed through experiments. It is observed that modeling and test results are matched with high quality. Rhombus type amplifier mechanism (RTAM) is selected for this study after conducting a detailed literature survey about flexure-based displacement amplifier mechanisms (FDAMs). The amplifier mechanism is designed and optimized via FEM. After manufacturing the mechanism, it is also validated via tests. In addition, accuracy of both analytical and geometrical formulas in literature are compared. Although linear modeling is sufficient to design an actuator, the model should be made more accurate by adding nonlinearities for precise engineering applications. PSAs exhibits highly nonlinear behavior, and the major source of this nonlinearity is hysteresis. Bouc-Wen model is utilized to represent hysteretic behavior for this work. Modified Bouc-Wen models in the literature are compiled comprehensively. As these models only work well in limited voltage ranges with symmetrical hysteresis shapes, a new type modified model named as Multivalued Bouc-Wen model (MVB-W) is developed to increase matching performance in extended input voltage ranges up to 150 V. Moreover, creep, another cause of nonlinearity, is modeled, and its parameters are identified through testing. Since PSAs are generally utilized in an amplifier mechanism under prestress, effect of prestress on hysteresis and creep is also investigated.

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Citation Formats
O. Yurdakul, “Nonlinear modeling of piezoelectric stack actuators with flexure based displacement amplifier mechanisms,” M.S. - Master of Science, Middle East Technical University, 2022.