Prediction of waste heat energy recovery performance in a naturally aspirated engine using artificial neural network

Abstract

The waste heat from exhaust gases represents a significant amount of thermal energy, which has conventionally been used for combined heating and power applications. This paper explores the performance of a naturally aspirated spark ignition engine equipped with waste heat recovery mechanism (WHRM). The experimental and simulation test results suggest that the concept is thermodynamically feasible and could significantly enhance the system performance depending on the load applied to the engine. The simulation method is created using an artificial neural network (ANN) which predicts the power produced from the WHRM. © 2014 Safarudin Gazali Herawan et al.