Exhaust Gas Recirculation Control in a Spark-Ignition LPG Engine Using Neural Networks

This paper presents a neural network approach to control exhaust gas recirculation(EGR) in a Liquefied Petroleum Gas(LPG) engine. In order to meet Increasingly stringent automotive exhaust emission regulations, alternative fuels such as LPG engines have been developed in many countries. HC&CO emissions of LPG engines can be easily reduced through air-fuel ratio control, but the control effect on NOx reduction is not good enough. Consequently EGR system is introduced to achieve a significant reduction in NOx emissions. Conventional EGR control uses the mapping method. The calibration time is long and the work is complex when adopting this mapping method. However neural networks are suitable f...