Na Kong

Education
  • Virginia Tech, Blacksburg, Ph.D. candidate, Electrical Engineering (August 2006 - present)
  • Tsinghua University, Beijing, China, M.S., Biomedical Engineering (August 2004 - July 2006)
  • Tsinghua University, Beijing, China, B.S., Biomedical Engineering (August 2000 - July 2004)

Research Interests
  • Digital controller design for switching power converters
  • Prototyping with FPGAs and digital VLSI design
  • Analog and mixed-signal IC design

Experience
  • (Aug 2006 - present) Graduate Research Assistant with Virginia Tech: Digital Control Design for Switching Mode Power Supplies
    • Digital constant on-time control with off-time prediction was proposed to reduce the oscillation amplitude of a DC-DC buck converter. This method relaxes the need for high resolution DPWMs and high throughput A/D converters.
    • A mixed signal simulation platform implemented in VHDL-AMS was developed which can model the power converters with digital control and estimated the system performance when applying proposed digital controller.
  • (May 2008 – Aug 2008) Intern with Texas Instruments
    • Automated system identification algorithm for digitally-controlled DC-DC converters
    • Application of digital constant on-time control to multiphase buck converters

Publications

  • Na Kong, Dong Sam Ha, Jian Li, and Fred C. Lee, "Off-time prediction in digital constant on-time modulation for DC-DC converters", IEEE International Symposium on Circuits and Systems, pp. 3270 – 3273, May 2008.
  • Na Kong, Ali Davoudi, Mark Hagen, Eric Oettinger, Ming Xu, Dong Sam Ha and Fred C. Lee, “Automated System Identification of Digitally-Controlled Multiphase Dc-Dc Converters,” Submitted to Applied Power Electronics Conference and Exhibition (APEC 09) on July 2008.

Relevant Courses

  • Power Electronics: Power Electronics, Power Semiconductor Devices
  • VLSI: CMOS VLSI Design, Analog IC Design, RFIC Design
  • Control Theory: Automatic Control, Power Converter Modeling and Control
  • Signal Processing: Signal and System, Modern Digital Signal Processing