Approximate dynamic programming solutions for lean burn engine aftertreatment

Abstract

The competition to deliver fuel efficient and environmentally friendly vehicles is driving the automotive industry to consider ever more complex powertrain systems. Adequate performance of these new highly interactive systems can no longer be obtained through traditional approaches, which are intensive in hardware use and final control software calibration. The paper explores the use of dynamic programming to make model-based design decisions for a lean burn, direct injection spark ignition engine, in combination with a three way catalyst and lean NOx trap aftertreatment system. The primary contribution is the development of a very rapid method to evaluate the tradeoffs in fuel economy and emissions for this novel powertrain system, as a function of design parameters and controller structure, over a standard emission test cycle.