Browsing by Author "Choi, Jae-Young"

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    Analysis of Inductor-Coupled Zero-Voltage-Transition Converters
    Choi, Jae-Young (Virginia Tech, 2001-07-24)
    As is the case for DC-DC converters, multi-phase converters require both high-quality power control and high power-density. Although a higher switching frequency not only improves the quality of the converter output but also decreases the size of the converter, it increases switching losses and electromagnetic interference (EMI) noise. Since the soft-switching topologies reduce the switching losses of the converter main switches, the topologies make converters partially independent from the switching frequency. However, the conventional soft-switching topologies have already proposed most of the possible ways to improve converter performance. In addition, the trends of the newly generated power devices reduce the advantages of soft-switching topologies. This critical situation surrounding soft-switching topologies gives research motivations: What features of soft-switching topologies facilitate their practical applications? Given this motivation, the dissertation discusses two aspects = simplifying auxiliary circuits and accounting for the effects of soft-switching operations on the converter control. Engineers working with medium- and high-power multi-phase converters require simplified soft-switching topologies that have the same level of performance as the conventional soft-switching topologies. This demand is the impetus behind one of the research objectives = simplifying the auxiliary circuits of Zero-Voltage-Transition (ZVT) inverters. Simplifying the auxiliary circuits results in both a smaller number of and lower cost for auxiliary components, without any negative impact on performance. This dissertation proposes two major concepts for the simplification - the Single-Switch Single-Leg (S3L) ZVT cell and the Phase-Lock (PL) concept. Throughout an effort to eliminate circulating currents of inductor-coupled (IC) ZVT converters, the S3L ZVT cell is developed. The proposed cell allows a single auxiliary switch to achieve zero-voltage conditions for both the top and bottom main switches, and it achieves the same level of performance as the conventional ZVT cell, as well. This proposal makes IC ZVT topologies more attractive to multi-phase converter applications. Because all of the top main switches generally have identical sequences for zero-voltage turn-on commutations, one auxiliary switch might handle the commutations of all of the top main switches. This possibility introduces the PL concept, which allows the two auxiliary switches to provide a zero-voltage condition for any main switch commutation. In order to compensate for restrictions of this concept, a modified space-vector modulation (SVM) scheme also is introduced. A soft-switching topology changes the duty ratios of the converter, which affects the controllability of the converter. Therefore, this dissertation selects resolution of this issue as one of the research objectives. This dissertation derives the generalized timing equations of ZVT operations, and the generalized equations formulize the effect of ZVT operation on both duty ratios and DC current. Moreover, the effect of SVM schemes is also investigated. An average model of the ZVT converter is developed using both the timing analysis and the investigation of SVM schemes, and small-signal analysis using the average model predicts the steady-state characteristics of the converter.
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    Data-driven Target Tracking and Hybrid Path Planning Methods for Autonomous Operation of UAV
    Choi, Jae-Young (Virginia Tech, 2023)
    The present study focuses on developing an efficient and stable unmanned aerial system traffic management (UTM) system that utilizes a data-driven target tracking method and a distributed path planning algorithm for multiple Unmanned Aerial Vehicle (UAV) operations with local dynamic networks, which can provide flexible scalability, enabling autonomous operation of a large number of UAVs in dynamically changing environment. Traditional dynamic motion-based target tracking methods often encounter limitations due to their reliance on a finite number of dynamic motion models. To address this, data-driven target tracking methods were developed based on the statistical model of the Gaussian mixture model (GMM) and deep neural networks of long-short term memory (LSTM) model, to estimate instant and future states of UAV for local path planning problems. The estimation accuracy of the data-driven target tracking methods were analyzed and compared with dynamic model-based target tracking methods. A hybrid dynamic path planning algorithm was proposed, which selectively employs grid-free and -based path search methods depending on the spatio-temporal characteristics of the environments. In static environment, the artificial potential field (APF) method was utilized, while the $A^*$ algorithm was applied in the dynamic state environment. Furthermore, the data-driven target tracking method was integrated with the hybrid path planning algorithm to enhance deconfliction. To ensure smooth trajectories, a minimum snap trajectory method was applied to the planned paths, enabling controller tracking that remains dynamically feasible throughout the entire operation of UAVs. The methods were validated in the Software-in-the-loop (SITL) demonstration with the simple PID controller of the UAVs implemented in the software program.
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    Prediction of Dynamic Stability Using Mapped Chebyshev Pseudospectral Method
    Choi, Jae-Young; Im, Dong Kyun; Park, Jangho; Choi, Seongim Sarah (Hindawi, 2018-08-01)
    A mapped Chebyshev pseudospectral method is extended to solve three-dimensional unsteady flow problems. As the classical Chebyshev spectral approach can lead to numerical instabilities due to ill conditioning of the spectral matrix, the Chebyshev points are evenly redistributed over the domain by an inverse sine mapping function. The mapped Chebyshev pseudospectral method can be used as an alternative time-spectral approach that uses a Chebyshev collocation operator to approximate the time derivative terms in the unsteady flow governing equations, and the method can make general applications to both nonperiodic and periodic problems. In this study, the mapped Chebyshev pseudospectral method is employed to solve three-dimensional periodic problem to verify the spectral accuracy and computational efficiency with those of the Fourier pseudospectral method and the time-accurate method. The results show a good agreement with both of the Fourier pseudospectral method and the time-accurate method. The flow solutions also demonstrate a good agreement with the experimental data. Similar to the Fourier pseudospectral method, the mapped Chebyshev pseudospectral method approximates the unsteady flow solutions with a precise accuracy at a considerably effective computational cost compared to the conventional time-accurate method.
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    Towards Autonomous Operation of UAVs Using Data-Driven Target Tracking and Dynamic, Distributed Path Planning Methods
    Choi, Jae-Young; Prasad, Rachit; Choi, Seongim (MDPI, 2024-09-03)
    A hybrid real-time path planning method has been developed that employs data-driven target UAV trajectory tracking methods. It aims to autonomously manage the distributed operation of multiple UAVs in dynamically changing environments. The target tracking methods include a Gaussian mixture model, a long short-term memory network, and extended Kalman filters with pre-specified motion models. Real-time vehicle-to-vehicle communication is assumed through a cloud-based system, enabling virtual, dynamic local networks to facilitate the high demand of vehicles in airspace. The method generates optimal paths by adaptively employing the dynamic A* algorithm and the artificial potential field method, with minimum snap trajectory smoothing to enhance path trackability during real flights. For validation, software-in-the-loop testing is performed in a dynamic environment composed of multiple quadrotors. The results demonstrate the framework’s ability to generate real-time, collision-free flight paths at low computational costs.