Strategic and societal concerns are driving current research and engineering efforts to produce more fuel-efficient, less polluting vehicles in the United States. Associated pollution problems such as the production of photochemical smog and ozone, with their adverse health effects are also important and compelling reasons to develop advanced methods of control for next generation vehicle engines. Advanced technology engines presently achieve emissions reduction by utilizing multi-point fuel injection, high compression ratios and high swirl combustion chamber design and by incorporating exhaust gas after-treatment using catalytic convertors. Future engine design will be significantly more radical in approach and will utilize lean burn combustion to meet increasingly strict emissions regulations. Currently envisioned ICE designs will utilize an array of control and performance sensors. Under a NSF and OSTP Clean Car sponsored program, NeuroDyne, the University of South Carolina, West Virginia University, and MIT Artificial Intelligence Laboratory are collaborating as an interdisciplinary research team in the development of advanced lean-burn engine control for reducing pollution and enhancing fuel economy in existing automobiles. NeuroDyne, Inc., proposes to leverage this program to investigate the integration of advanced sensor technology with intelligent sensor processing and control methods to enhance the performance and efficiency of next generation vehicle engines.
