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Description
Buck converters are electronic devices that changes a voltage from one level to a lower one and are present in many everyday applications. However, due to factors like aging, degradation or failures, these devices require a system identification process to track and diagnose their parameters. The system identification process should

Buck converters are electronic devices that changes a voltage from one level to a lower one and are present in many everyday applications. However, due to factors like aging, degradation or failures, these devices require a system identification process to track and diagnose their parameters. The system identification process should be performed on-line to not affect the normal operation of the device. Identifying the parameters of the system is essential to design and tune an adaptive proportional-integral-derivative (PID) controller.

Three techniques were used to design the PID controller. Phase and gain margin still prevails as one of the easiest methods to design controllers. Pole-zero cancellation is another technique which is based on pole-placement. However, although these controllers can be easily designed, they did not provide the best response compared to the Frequency Loop Shaping (FLS) technique. Therefore, since FLS showed to have a better frequency and time responses compared to the other two controllers, it was selected to perform the adaptation of the system.

An on-line system identification process was performed for the buck converter using indirect adaptation and the least square algorithm. The estimation error and the parameter error were computed to determine the rate of convergence of the system. The indirect adaptation required about 2000 points to converge to the true parameters prior designing the controller. These results were compared to the adaptation executed using robust stability condition (RSC) and a switching controller. Two different scenarios were studied consisting of five plants that defined the percentage of deterioration of the capacitor and inductor within the buck converter. The switching logic did not always select the optimal controller for the first scenario because the frequency response of the different plants was not significantly different. However, the second scenario consisted of plants with more noticeable different frequency responses and the switching logic selected the optimal controller all the time in about 500 points. Additionally, a disturbance was introduced at the plant input to observe its effect in the switching controller. However, for reasonable low disturbances no change was detected in the proper selection of controllers.
ContributorsSerrano Rodriguez, Victoria Melissa (Author) / Tsakalis, Konstantinos (Thesis advisor) / Bakkaloglu, Bertan (Thesis advisor) / Rodriguez, Armando (Committee member) / Spanias, Andreas (Committee member) / Arizona State University (Publisher)
Created2016
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Description
This work analyzes and develops a point-of-load (PoL) synchronous buck converter using enhancement-mode Gallium Nitride (e-GaN), with emphasis on optimizing reverse conduction loss by using a well-known technique of placing an anti-parallel Schottky diode across the synchronous power device. This work develops an improved analytical switching model for the

This work analyzes and develops a point-of-load (PoL) synchronous buck converter using enhancement-mode Gallium Nitride (e-GaN), with emphasis on optimizing reverse conduction loss by using a well-known technique of placing an anti-parallel Schottky diode across the synchronous power device. This work develops an improved analytical switching model for the GaN-based converter with the Schottky diode using piecewise linear approximations.

To avoid a shoot-through between the power switches of the buck converter, a small dead-time is inserted between gate drive switching transitions. Despite optimum dead-time management for a power converter, optimum dead-times vary for different load conditions. These variations become considerably large for PoL applications, which demand high output current with low output voltages. At high switching frequencies, these variations translate into losses that contribute significantly to the total loss of the converter. To understand and quantify power loss in a hard-switching buck converter that uses a GaN power device in parallel with a Schottky diode, piecewise transitions are used to develop an analytical switching model that quantifies the contribution of reverse conduction loss of GaN during dead-time.

The effects of parasitic elements on the dynamics of the switching converter are investigated during one switching cycle of the converter. A designed prototype of a buck converter is correlated to the predicted model to determine the accuracy of the model. This comparison is presented using simulations and measurements at 400 kHz and 2 MHz converter switching speeds for load (1A) condition and fixed dead-time values. Furthermore, performance of the buck converter with and without the Schottky diode is also measured and compared to demonstrate and quantify the enhanced performance when using an anti-parallel diode. The developed power converter achieves peak efficiencies of 91.7% and 93.86% for 2 MHz and 400 KHz switching frequencies, respectively, and drives load currents up to 6A for a voltage conversion from 12V input to 3.3V output.

In addition, various industry Schottky diodes have been categorized based on their packaging and electrical characteristics and the developed analytical model provides analytical expressions relating the diode characteristics to power stage performance parameters. The performance of these diodes has been characterized for different buck converter voltage step-down ratios that are typically used in industry applications and different switching frequencies ranging from 400 KHz to 2 MHz.
ContributorsKoli, Gauri (Author) / Kitchen, Jennifer (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Ozev, Sule (Committee member) / Arizona State University (Publisher)
Created2020