ML-ACCEPT: Machine-Learning-enhanced Automated Circuit Configuration and Evaluation of Power Converters

NSF I-Corps Team for Customer Discovery:

DOE ARPA-E R&D Project:

Compared to existing methods, the ML-ACCEPT software suite makes the design of power converters more cost- and time-efficient (e.g., 100X faster than human expert design with comparable performance) by 

1) integrating recent breakthroughs in machine learning, power electronics, simulation software, and optimization to research, develop, and demonstrate a suite of machine-learning-enhanced hypothesis generation tools for power converter design; and 

2) facilitating the integration of the proposed software tools into existing power-converter design work-flows. 

The project is in part supported by the. U.S. Department of Energy - Advanced Research Projects Agency–Energy (ARPA-E), the U.S. National Science Foundation (NSF), and the University of Michigan.

More information is available upon request.

Please email Dr. Wencong Su <>.

Selected Publication:

Pending Patent: