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Articles 1 - 6 of 6
Full-Text Articles in Power and Energy
Electrical Modeling For Dynamic Performance Prediction And Optimization Of Mcpms Layout, Quang Minh Le
Electrical Modeling For Dynamic Performance Prediction And Optimization Of Mcpms Layout, Quang Minh Le
Graduate Theses and Dissertations
In recent years, the fast development of Multichip Power Modules (MCPM) packaging and Wide Bandgap (WBG) technology has enabled higher voltage and current ratings, better thermal performance, lower parasitic parameters, and higher mechanical reliability. However, the design of the MCPM layout is a multidisciplinary problem leading to many time-consuming analyses and tedious design processes. Because of these challenges, the design automation tool for MCPM layout has become an emerging research area and gained much attention from the power electronics community. The two critical objectives of a design automation tool for MCPM layout are fast and accurate models for design insights …
Constraint-Aware, Scalable, And Efficient Algorithms For Multi-Chip Power Module Layout Optimization, Imam Al Razi
Constraint-Aware, Scalable, And Efficient Algorithms For Multi-Chip Power Module Layout Optimization, Imam Al Razi
Graduate Theses and Dissertations
Moving towards an electrified world requires ultra high-density power converters. Electric vehicles, electrified aerospace, data centers, etc. are just a few fields among wide application areas of power electronic systems, where high-density power converters are essential. As a critical part of these power converters, power semiconductor modules and their layout optimization has been identified as a crucial step in achieving the maximum performance and density for wide bandgap technologies (i.e., GaN and SiC). New packaging technologies are also introduced to produce reliable and efficient multichip power module (MCPM) designs to push the current limits. The complexity of the emerging MCPM …
Analog Spiking Neural Network Implementing Spike Timing-Dependent Plasticity On 65 Nm Cmos, Luke Vincent
Analog Spiking Neural Network Implementing Spike Timing-Dependent Plasticity On 65 Nm Cmos, Luke Vincent
Graduate Theses and Dissertations
Machine learning is a rapidly accelerating tool and technology used for countless applications in the modern world. There are many digital algorithms to deploy a machine learning program, but the most advanced and well-known algorithm is the artificial neural network (ANN). While ANNs demonstrate impressive reinforcement learning behaviors, they require large power consumption to operate. Therefore, an analog spiking neural network (SNN) implementing spike timing-dependent plasticity is proposed, developed, and tested to demonstrate equivalent learning abilities with fractional power consumption compared to its digital adversary.
Cybersecurity Methods For Grid-Connected Power Electronics, Stephen Joe Moquin
Cybersecurity Methods For Grid-Connected Power Electronics, Stephen Joe Moquin
Graduate Theses and Dissertations
The present work shows a secure-by-design process, defense-in-depth method, and security techniques for a secure distributed energy resource. The distributed energy resource is a cybersecure, solar inverter and battery energy storage system prototype, collectively called the Cybersecure Power Router. Consideration is given to the use of the Smart Green Power Node for a foundation of the present work. Metrics for controller security are investigated to evaluate firmware security techniques. The prototype's ability to mitigate, respond to, and recover from firmware integrity degradation is examined. The prototype shows many working security techniques within the context of a grid-connected, distributed energy resource. …
Model Development And Assessment Of The Gate Network In A High-Performance Sic Power Module, William Austin Curbow
Model Development And Assessment Of The Gate Network In A High-Performance Sic Power Module, William Austin Curbow
Graduate Theses and Dissertations
The main objective of this effort is to determine points of weakness in the gate network of a high-performance SiC power module and to offer remedies to these issues to increase the overall performance, robustness, and reliability of the technology. In order to accomplish this goal, a highly accurate model of the gate network is developed through three methods of parameter extraction: calculation, simulation, and measurement. A SPICE model of the gate network is developed to analyze four electrical issues in a high-speed, SiC-based power module including the necessary internal gate resistance for damping under-voltage and over-voltage transients, the disparity …
Automatic Performance Optimization On Heterogeneous Computer Systems Using Manycore Coprocessors, Chenggang Lai
Automatic Performance Optimization On Heterogeneous Computer Systems Using Manycore Coprocessors, Chenggang Lai
Graduate Theses and Dissertations
Emerging computer architectures and advanced computing technologies, such as Intel’s Many Integrated Core (MIC) Architecture and graphics processing units (GPU), provide a promising solution to employ parallelism for achieving high performance, scalability and low power consumption. As a result, accelerators have become a crucial part in developing supercomputers. Accelerators usually equip with different types of cores and memory. It will compel application developers to reach challenging performance goals. The added complexity has led to the development of task-based runtime systems, which allow complex computations to be expressed as task graphs, and rely on scheduling algorithms to perform load balancing between …