Author ORCID Identifier

https://orcid.org/0000-0002-7171-4647

Year of Publication

2018

Degree Name

Master of Science in Electrical Engineering (MSEE)

Document Type

Master's Thesis

College

Engineering

Department

Electrical and Computer Engineering

First Advisor

Dr. Aaron Cramer

Abstract

Power electronics have a significant role in modern electrical devices, for instance, hybrid electric vehicles. Power electronics are the technology in between the source and the load circuits and can convert the power from dc to ac or from dc to ac. There are also many types of dc-dc converters, like such as boost and buck converters, which exhibit switching ripple behavior. A boost converter increases the output voltage (with respect to the input voltage) and reduces the output current. A buck converter decreases the output voltage and increases the output current. Many models are used to predict the behavior of the boost and buck converters. The detailed (DET), state-space averaged (SSA), and generalized averaging method (GAM) models are capable of predicting the average behavior of dc-dc converters. For DET and GAM models, the rippling behavior can also be predicted. These models differ in terms of required run time, existence of constant equilibrium points, and accuracy. The DET model has a long run time and does not have constant equilibrium, but it is very accurate. The SSA technique is a mathematical and time-invariant model that capable of describing the behavior of a dc-dc boost converters. It can derive the small signal ac equations of a switching converter and is used to illustrate the average behavior of any linear or nonlinear system in converters. The SSA does not take extensive runtime simulation and has constant equilibrium points, and can be applied to continuous, discrete and sample data systems. The GAM model can predict the average and ripple behavior in power electronic systems and has constant equilibrium and fast run time. However, it has a numerical stability issue. The integrator stabilized multifrequency averaging (ISMFA) model is employed to solve the stability issue in the GAM model, but it is a complicated dynamic method and has restrictions in its process. In the present study, a simplified but stable GAM model is introduced to predict the average and ripple behavior of boost dc-dc converters and to overcome the limitations of other methods. In this work, the stabilized GAM model has been used for a dc-dc boost converters. The stability of the proposed model is analyzed. The performance of the improved GAM model is compared with the DET, SSA, and GAM models. The results show that the stabilized GAM model is stable with the additional poles created by the GAM assignable by parameter choice. The new GAM model predicts the same results as the existing GAM method without the underlying stability concerns. The stabilized GAM model exhibits constant ii equilibrium point and requires significantly lower run times than the DET model, but it is also able to predict the ripple performance of the converter. The stabilized GAM model does not take a long run time, is less complicated, has fewer restrictions, has constant equilibrium and internal stability, and has more straightforward implementation than other models, like the ISMFA model. It represents a suitable alternative to DET models when high accuracy simulations are desired without long simulation run times.

Digital Object Identifier (DOI)

https://doi.org/10.13023/etd.2018.296

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