STTR Phase I: Online Optimization for Induction Motor Efficiency

This Small Business Technology Transfer (STTR) Phase I research project will develop a new control method to automatically maximize the operating efficiency of electric machines. This research will apply recent developments in a particular type of optimal control to the important challenge of energy efficiency, will research into observers for machine power processing, and connection of the method to vibrational control. Efficiency maximization has been studied, especially for induction machines, but methods that adapt over wide load ranges are not available. The new approach leverages recent advances in ripple correlation control (RCC) to provide a fast, robust power minimizer. RCC uses inherent ripple in a power electronic system to force the average operating point to an optimum. RCC has been applied to solar power, but has been difficult to extend to motor control. RCC will be connected to vibrational control, a well established field that exploits variation in a system but with different objectives. The effort promises substantial electrical energy savings, works with electronic motor drives and will increase understanding of machine efficiency. Electric motors account for at least 60% of electricity consumption in the U.S., and about 2/3 globally. Widespread application of the technology developed through this project would reduce total electricity consumption by 7-10%, for an annual savings of about $23 billion in the U.S. alone. Even modest adoption of this technology would significantly reduce energy use in industrial and commercial arenas, and would establish technology solutions for efficiency control. The new approach is also important in advanced motor applications. It would extend the range of hybrid electric vehicles (HEVs) and plug-in HEVs.