Exergy based model predictive control of an integrated dual fuel engine and a waste heat recovery system

Abstract

This study showcases a new exergy based model predictive control (XMPC) framework designed to maximize the fuel conversion efficiency of an internal combustion engine (ICE); when the ICE is integrated with a waste heat recovery (WHR) system. Consequently, mathematical models are developed for the integrated ICE and WHR system; which are control oriented. The control oriented models developed are based on applying the First and Second Laws of thermodynamics to the system. In particular, based on the of Thermodynamics. The designed XMPC framework maximizes the fuel conversion efficiency of the ICE by maximizing the second law efficiency of the ICE, turbocharger, heat exchanger, and organic Rankine cycle sub-systems in the integrated ICE and WHR system. In addition, the designed XMPC framework meets the exhaust gas temperature required by the exhaust aftertreatment systems. The results show that the application of designed XMPC framework to the integrated ICE and WHR system can reduce the fuel consumed by the ICE by 3.2%; compared to the application of a fully calibrated energy based rule based controller.