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The Road Toward Greener Cars by Using Neuro-Fuzzy Modeling of Spark-Ignition Engines with Variable Valve Overlap

Abstract Greening technology is gaining more attention in different aspects, especially the surface transport. This technology aims to improve performance and reduce global greenhouse gas emissions. In this work, a typical automotive spark ignition engine with four cylinders and 1600 cc displacement was considered. This work introduces a neuro-fuzzy approach that can be used to design an intelligent system for controlling the overlap angle in the spark ignition engine cycle. The simulation results showed that the neuro-fuzzy-based control system for varying the overlap angle achieved increased engine power and reduced fuel consumption in comparison with the conventional engine that used fixed overlap angle. The power was improved by about 2.2–12.6 %, while the BSFC was reduced by about 2%-11%.