Call number: LD2668 .T4 1951 R55 / Master of Science

by Ng Chiu-king. / Chinese title: / Bibliography: leaves 68-69 / Thesis (M.Phil.)--Chinese University of Hong Kong, 1983

Thesis. 1976. B.S.--Massachusetts Institute of Technology. Dept. of Physics. / Microfiche copy available in Archives and Science. / Bibliography: leaves 36-37. / B.S.

With the introduction of high speed semiconductor power devices and the increased application of adjustable speed drives (ASDs) for efficient speed control of ac motors, there has been a growing number of costly motor-drive related process failures. It has been found that the high dv/dt and high switching frequency have caused premature motor insulation failures due to motor terminal over-voltages (exacerbated by longer cable lengths). It is also acknowledged that high dv/dt and high frequency common-mode voltages generated by pulse-width modulated (PWM) inverters contribute significantly to electromagnetic interference (EMI) and may also cause damaging bearing and leakage currents. In response to these problems, a variety of mitigation techniques have been proposed in the past. However, the known solutions usually address these problems one at a time and some of the mitigation techniques are not highly effective. The major objective of this research is to search for solutions to these ASD application issues with an emphasis on solving all of the problems at the source. Therefore, theoretical analysis of all the above adverse effects are presented and the existing mitigation techniques are evaluated in this dissertation. It is found that common-mode voltage is the major cause of both bearing currents and the conducted EMI, thus the research is focused on new inverter topologies and control strategies in order to eliminate the common-mode voltage. To achieve the goal of common-mode voltage cancellation, a novel dual-bridge inverter (DBI) is proposed and studied. The DBI employs an additional inverter output stage to drive a standard three-phase dual-voltage induction motor and is controlled to generate balanced excitation of the motor resulting in a zero common-mode voltage. It is shown through experimental results that the motor bearing current is eliminated and the conducted EMI is significantly reduced. In addition to the DBI, multilevel inverter topologies have also been studied. It has been found in this research that with proper selections of the switching states, certain multilevel PWM inverters will not generate common-mode voltages. This new control method is verified in simulation by using both sine-triangle intersection PWM (SPWM) and voltage space-vector modulation (SVM). / Graduation date: 1999

Flow speed describes general traffic operation conditions on a segment of roadway. It is also used to diagnose special conditions such as congestion and incidents. Accurate speed estimation plays a critical role in traffic management or traveler information systems. Data from loop detectors have been primary sources for traffic information, and single loop are the predominant loop detector type in many places. However, single loop detectors do not produce speed output. Therefore, speed estimation using single loop outputs has been an important issue for decades. This dissertation research presents two methodologies for speed estimation using single loop outputs. Based on findings from past studies and examinations in this research, it is verified that speed estimation is a nonlinear system under various traffic conditions. Thus, a methodology of using Unscented Kalman Filter (UKF) is first proposed for such a system. The UKF is a parametric filtering technique that is suitable for nonlinear problems. Through an Unscented Transformation (UT), the UKF is able to capture the posterior mean and covariance of a Gaussian random variable accurately for a nonlinear system without linearization. This research further shows that speed estimation is a nonlinear non-Gaussian system. However, Kalman filters including the UKF are established based on the Gaussian assumption. Thus, another nonlinear filtering technique for non-Gaussian systems, the Particle Filter (PF), is introduced. By combining the strengths of both the PF and the UKF, the second speed estimation methodology - Unscented Particle Filter (UPF) is proposed for speed estimation. The use of the UPF avoids the limitations of the UKF and the PF. Detector data are collected from multiple freeway locations and the microscopic traffic simulation program CORSIM. The developed methods are applied to the collected data for speed estimation. The results show that both proposed methods have high accuracies of speed estimation. Between the UKF and the UPF, the UPF has better performance but has higher computation cost. The improvement of speed estimation will benefit real-time traffic operations by improving the performance of applications such as travel time estimation using a series of single loops in the network, incident detection, and large truck volume estimation. Therefore, the work enables traffic analysts to use single loop outputs in a more cost-effective way.

Flow speed describes general traffic operation conditions on a segment of roadway. It is also used to diagnose special conditions such as congestion and incidents. Accurate speed estimation plays a critical role in traffic management or traveler information systems. Data from loop detectors have been primary sources for traffic information, and single loop are the predominant loop detector type in many places. However, single loop detectors do not produce speed output. Therefore, speed estimation using single loop outputs has been an important issue for decades. This dissertation research presents two methodologies for speed estimation using single loop outputs. Based on findings from past studies and examinations in this research, it is verified that speed estimation is a nonlinear system under various traffic conditions. Thus, a methodology of using Unscented Kalman Filter (UKF) is first proposed for such a system. The UKF is a parametric filtering technique that is suitable for nonlinear problems. Through an Unscented Transformation (UT), the UKF is able to capture the posterior mean and covariance of a Gaussian random variable accurately for a nonlinear system without linearization. This research further shows that speed estimation is a nonlinear non-Gaussian system. However, Kalman filters including the UKF are established based on the Gaussian assumption. Thus, another nonlinear filtering technique for non-Gaussian systems, the Particle Filter (PF), is introduced. By combining the strengths of both the PF and the UKF, the second speed estimation methodology—Unscented Particle Filter (UPF) is proposed for speed estimation. The use of the UPF avoids the limitations of the UKF and the PF. Detector data are collected from multiple freeway locations and the microscopic traffic simulation program CORSIM. The developed methods are applied to the collected data for speed estimation. The results show that both proposed methods have high accuracies of speed estimation. Between the UKF and the UPF, the UPF has better performance but has higher computation cost. The improvement of speed estimation will benefit real-time traffic operations by improving the performance of applications such as travel time estimation using a series of single loops in the network, incident detection, and large truck volume estimation. Therefore, the work enables traffic analysts to use single loop outputs in a more cost-effective way.

This thesis deals with the development of high speed InPmesa HBT’s with power gain cut—off frequencies up toand above 300 GHz, with high current density and low collectordischarging times. Key developments are Pd—based base ohmics yielding basecontact resistances as low as 10 Ωµm2, base—collector grades to enable to use ofInP in the collector, and an increase in the maximum currentdensity through collector design and thermal optimization.HBT’s with a linear doping gradient in the base are forthe first time reported and compared to HBT’s with abandgap graded base. The effect of degenerate base doping issimulated, as well as the base transit time. Key results include a DHBT with a 215 nm thick collector andan fτ= 280GHz, and fmax=400 GHz. This represents the highest fmaxreported for a mesa HBT. Results also include aDHBT with a 150 nm thick collector and an fτ= 300 GHz, and fmax=280 GHz. The maximum operating current densityhas been increased to above 10 mAµm while maintaining fτand fmax≥ 200 GHz. A mesa DHBT process with and as much yield and simplicity aspossible has been developed, while maintaining or pushingworld—class performance.

Flow speed describes general traffic operation conditions on a segment of roadway. It is also used to diagnose special conditions such as congestion and incidents. Accurate speed estimation plays a critical role in traffic management or traveler information systems. Data from loop detectors have been primary sources for traffic information, and single loop are the predominant loop detector type in many places. However, single loop detectors do not produce speed output. Therefore, speed estimation using single loop outputs has been an important issue for decades. This dissertation research presents two methodologies for speed estimation using single loop outputs. Based on findings from past studies and examinations in this research, it is verified that speed estimation is a nonlinear system under various traffic conditions. Thus, a methodology of using Unscented Kalman Filter (UKF) is first proposed for such a system. The UKF is a parametric filtering technique that is suitable for nonlinear problems. Through an Unscented Transformation (UT), the UKF is able to capture the posterior mean and covariance of a Gaussian random variable accurately for a nonlinear system without linearization. This research further shows that speed estimation is a nonlinear non-Gaussian system. However, Kalman filters including the UKF are established based on the Gaussian assumption. Thus, another nonlinear filtering technique for non-Gaussian systems, the Particle Filter (PF), is introduced. By combining the strengths of both the PF and the UKF, the second speed estimation methodology—Unscented Particle Filter (UPF) is proposed for speed estimation. The use of the UPF avoids the limitations of the UKF and the PF. Detector data are collected from multiple freeway locations and the microscopic traffic simulation program CORSIM. The developed methods are applied to the collected data for speed estimation. The results show that both proposed methods have high accuracies of speed estimation. Between the UKF and the UPF, the UPF has better performance but has higher computation cost. The improvement of speed estimation will benefit real-time traffic operations by improving the performance of applications such as travel time estimation using a series of single loops in the network, incident detection, and large truck volume estimation. Therefore, the work enables traffic analysts to use single loop outputs in a more cost-effective way.

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My thesis describes a tool which creates speed-lines automatically in 3D computer animations. Speed-lines are usually used in comic books to express fast motions in a still image. They are also used in 2D animations. Although animations don't need speed-lines for motions, they are interesting graphic elements and give more sense of speed to the audience. However, speed-lines are not used in the 3D computer animation, so I have implemented the graphic element into the 3D computer animation. The combination of the 2D-looking speed-lines and the 3D computer animations makes a unique look that some animators might want. In addition, making speed-lines based on motions of moving objects or cameras, this tool can make 3D speed-lines which are very difficult to draw by hand.