A novel 50 kW fast charger was proposed for electric vehicles. The proposed fast charger is divided into two main sections an AC-DC converter performing a PFC function and a DC-DC converter performing a charging funct...A novel 50 kW fast charger was proposed for electric vehicles. The proposed fast charger is divided into two main sections an AC-DC converter performing a PFC function and a DC-DC converter performing a charging function. A transformer including leakage inductances was used in the AC-DC converter in order to obtain isolation and inductance. A series-connection topology was used in the DC-DC converter between the DC-bus and outlet. This topology enables high power conversion efficiency up to 95% for the DC-DC converter. In order to reduce the impact of the 50 kW charging on the AC grid, the proposed fast charger system includes a buffering battery unit between the two main power conversion units. This leads to reductions in the power installation costs of power companies and to improvements in the power quality were verified through simulations and experimental results. on the AC grid. The performances of the proposed fast charger system展开更多
A novel technique is proposed to improve the performance of voice activity detection(VAD) by using deep belief networks(DBN) with a likelihood ratio(LR). The likelihood ratio is derived from the speech and noise spect...A novel technique is proposed to improve the performance of voice activity detection(VAD) by using deep belief networks(DBN) with a likelihood ratio(LR). The likelihood ratio is derived from the speech and noise spectral components that are assumed to follow the Gaussian probability density function(PDF). The proposed algorithm employs DBN learning in order to classify voice activity by using the input signal to calculate the likelihood ratio. Experiments show that the proposed algorithm yields improved results in various noise environments, compared to the conventional VAD algorithms. Furthermore, the DBN based algorithm decreases the detection probability of error with [0.7, 2.6] compared to the support vector machine based algorithm.展开更多
基金Project supported by Changwon National University in 2011-2012
文摘A novel 50 kW fast charger was proposed for electric vehicles. The proposed fast charger is divided into two main sections an AC-DC converter performing a PFC function and a DC-DC converter performing a charging function. A transformer including leakage inductances was used in the AC-DC converter in order to obtain isolation and inductance. A series-connection topology was used in the DC-DC converter between the DC-bus and outlet. This topology enables high power conversion efficiency up to 95% for the DC-DC converter. In order to reduce the impact of the 50 kW charging on the AC grid, the proposed fast charger system includes a buffering battery unit between the two main power conversion units. This leads to reductions in the power installation costs of power companies and to improvements in the power quality were verified through simulations and experimental results. on the AC grid. The performances of the proposed fast charger system
基金supported by the KERI Primary Research Program through the Korea Research Council for Industrial Science & Technology funded by the Ministry of Science,ICT and Future Planning (No.15-12-N0101-46)
文摘A novel technique is proposed to improve the performance of voice activity detection(VAD) by using deep belief networks(DBN) with a likelihood ratio(LR). The likelihood ratio is derived from the speech and noise spectral components that are assumed to follow the Gaussian probability density function(PDF). The proposed algorithm employs DBN learning in order to classify voice activity by using the input signal to calculate the likelihood ratio. Experiments show that the proposed algorithm yields improved results in various noise environments, compared to the conventional VAD algorithms. Furthermore, the DBN based algorithm decreases the detection probability of error with [0.7, 2.6] compared to the support vector machine based algorithm.
