Soft Switching ARCP Inverter Using Series Connected SiC MOSFETs for Medium Voltage Motor Drive Applications

2024 IEEE Applied Power Electronics Conference and Exposition (APEC)(2024)

引用 0|浏览2
暂无评分
摘要
HV SiC MOSFETs can significantly improve the efficiency and power density of medium voltage (MV) motor drives by enabling higher fundamental frequencies. A major constraint, however, is the high dv/dt at motor terminals, leading to the use of external dv/dt filters. Employing auxiliary resonant commutation to realize soft switching allows dv/dt control and potentially eliminates the dv/dt filter. In this work, it has been proposed to use series connected devices in an auxiliary resonant commutated pole (ARCP) inverter with the resonant capacitor split across the series connected devices, providing dynamic voltage balancing. Series connection of devices offers lower specific on-resistance and semiconductor cost compared to an equivalent voltage blocking single device. RC snubbers typically used for dynamic voltage balancing across series connected devices in a conventional hard switching converter decrease the device turn-off loss but result in high turn-on loss due to snubber capacitor discharge. This paper proposes to overcome this limitation by realizing ZVS turn-on through auxiliary resonant commutation and leveraging the split resonant capacitor for dynamic voltage balancing. This results in soft turn-on and turn-off along with controllable output dv/dt eliminating the need for an external dv/dt filter. The operating principle and design criteria for the soft switching converter with series connected devices have been discussed. A 2-level ARCP inverter with 3.6 kV dc bus using two series connected 3.3 kV SiC MOSFETs per switch has been designed and built, and it has been characterized through pulsed tests as a first step under hard and soft switching conditions validating the concept.
更多
查看译文
关键词
ARCP,soft switching,SiC MOSFET,medium voltage,series connection,3.3 kV,6.5 kV,voltage balancing,motor drive,high speed
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要