Hole bypassing N/sup +/ emitter structure of the trench IGBT for the safe switching operation

Author(s):  
H.-S. Kim ◽  
T.-S. Lee ◽  
C.-M. Yun ◽  
K.-H. Oh ◽  
P.-G. Im ◽  
...  
Keyword(s):  
Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 849
Author(s):  
Sung-An Kim

A modeling of a turbo air compressor system (TACS), with a multi-level inverter for driving variable speed, combining an electrical model of an electric motor drive system (EMDS) and a mechanical model of a turbo air compressor, is essential to accurately analyze dynamics characteristics. Compared to the mechanical model, the electrical model has a short sampling time due to the high frequency switching operation of the numerous power semiconductors inside the multi-level inverter. This causes the problem of increased computational time for dynamic characteristics analysis of TACS. To solve this problem, the conventional model of the multi-level inverter has been proposed to simplify the switching operation of the power semiconductors, however it has low accuracy because it does not consider pulse width modulation (PWM) operation. Therefore, this paper proposes an improved modeling of the multi-level inverter for TACS to reduce computational time and improve the accuracy of electrical and mechanical responses. In order to verify the reduced computational time of the proposed model, the conventional model using the simplified model is compared and analyzed using an electronic circuit simulation software PSIM. Then, the improved accuracy of the proposed model is verified by comparison with the experimental results.


1988 ◽  
Vol 24 (7) ◽  
pp. 415 ◽  
Author(s):  
K.G. Ravikumar ◽  
K. Shimomura ◽  
T. Kikugawa ◽  
A. Izumi ◽  
S. Arai ◽  
...  

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2904 ◽  
Author(s):  
Hyebin Park ◽  
Yujin Lim

In 5G networks, heterogeneous cloud radio access network (H-CRAN) is considered a promising future architecture to minimize energy consumption and efficiently allocate resources. However, with the increase in the number of users, studies are performed to overcome the energy consumption problems. In this study, we propose a power control algorithm with mobility prediction to provide a high-energy efficiency for 5G H-CRAN. In particular, the proposed algorithm predicts UE mobility in vehicular mobility scenarios and performs remote radio head (RRH) switching operations based on % prediction results. We formulate an optimization problem to maximize the energy efficiency while satisfying the outage probability requirement. We then propose an RRH switching operation based on Markov mobility prediction and optimize the transmission power based on a gradient method. Simulation results demonstrate the improved energy efficiency compared with those of existing RRH switching-operation algorithms.


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