Commutation Technique for High Frequency Link Inverter without Operational Limitations and Dead Time

An improved commutation technique for the ac-ac output converter circuit of a pulse width modulated high frequency link (HF-link) inverter has been investigated. The high frequency link inverter converts a DC input voltage into line frequency AC output voltage using a high-frequency transformer for voltage step-up and galvanic isolation, without an intermediate rectification and DC bus. In this topology, there is a direct ac-ac converter, which processes the HF-link square-wave voltage into the desired sinusoidal ac output voltage. To do this requires a commutation method to prevent shoot-through when output current changes direction or commutates from one switch to the next. Conventionally, dead time is used but this adds distortion to the output waveform. Previously a commutation technique without dead time was introduced, but it required a number of assumptions on the inverter load impedance and link voltage characteristics that made it useful for a stand-alone R-L load but not practical for grid connection. The commutation method in this paper does not require dead time and does not impose any limitation on the output inductance and link voltage magnitude and frequency. Simulations, results experimental results and detailed analysis of output current THD values are presented

Commutation Technique for High Frequency Link Inverter without Operational Limitations and Dead Time

An improved commutation technique for the ac-ac output converter circuit of a pulse width modulated high frequency link (HF-link) inverter has been investigated. The high frequency link inverter converts a DC input voltage into line frequency AC output voltage using a high-frequency transformer for voltage step-up and galvanic isolation, without an intermediate rectification and DC bus. In this topology, there is a direct ac-ac converter, which processes the HF-link square-wave voltage into the desired sinusoidal ac output voltage. To do this requires a commutation method to prevent shoot-through when output current changes direction or commutates from one switch to the next. Conventionally, dead time is used but this adds distortion to the output waveform. Previously a commutation technique without dead time was introduced, but it required a number of assumptions on the inverter load impedance and link voltage characteristics that made it useful for a stand-alone R-L load but not practical for grid connection. The commutation method in this paper does not require dead time and does not impose any limitation on the output inductance and link voltage magnitude and frequency. Simulations, results experimental results and detailed analysis of output current THD values are presented

Embedded System Performance Analysis for Implementing a Portable Drowsiness Detection System for Drivers

Drowsiness on the road is a widespread problem with fatal consequences; thus, a multitude of systems and techniques have been proposed. Among existing methods, Ghoddoosian et al. utilized temporal blinking patterns to detect early signs of drowsiness, but their algorithm was tested only on a powerful desktop computer, which is not practical to apply in a moving vehicle setting. In this paper, we propose an efficient platform to run Ghoddosian's algorithm, detail the performance tests we ran to determine this platform, and explain our threshold optimization logic. After considering the Jetson Nano and Beelink (Mini PC), we concluded that the Mini PC is the most efficient and practical to run our embedded system in a vehicle. To determine this, we ran communication speed tests and evaluated total processing times for inference operations. Based on our experiments, the average total processing time to run the drowsiness detection model was 94.27 ms for Jetson Nano and 22.73 ms for the Beelink (Mini PC). Considering the portability and power efficiency of each device, along with the processing time results, the Beelink (Mini PC) was determined to be most suitable. Also, we propose a threshold optimization algorithm, which determines whether the driver is drowsy or alert based on the trade-off between the sensitivity and specificity of the drowsiness detection model. Our study will serve as a crucial next step for drowsiness detection research and its application in vehicles. Through our experiment, we have determinend a favorable platform that can run drowsiness detection algorithms in real-time and can be used as a foundation to further advance drowsiness detection research. In doing so, we have bridged the gap between an existing embedded system and its actual implementation in vehicles to bring drowsiness technology a step closer to prevalent real-life implementation.Comment: 26 pages, 13 figures, 4 table