An artificial neural network developed for predicting of performance and emissions of a spark ignition engine fueled with butanol–gasoline blends

Zhiqiang Liu,Yuelin Li,Gang Wu,Qingsong Zuo

doi:10.1177/1687814017748438

Abstract

The engine experiments require multiple tests that are hard, time-consuming, and high cost. Therefore, an artificial neural network model was developed in this study to successfully predict the engine performance and exhaust emissions when a port fuel injection spark ignition engine fueled with n-butanol–gasoline blends (0–60 vol.% n-butanol blended with gasoline referred as G100-B60) under various equivalence ratio. In the artificial neural network model, compression ratio, equivalence ratio, blend percentage, and engine load were used as the input parameters, while engine performance and emissions like brake thermal efficiency, brake-specific fuel consumption, carbon monoxide, unburned hydrocarbons, and nitrogen oxides were used as the output parameters. In comparison between experimental data and predicted results, a correlation coefficient ranging from 0.9929 to 0.9996 and a mean relative error ranging from 0.1943% to 9.9528% were obtained. It is indicated that the developed artificial neural network model was capable of predicting the combustion of n-butanol–gasoline blends due to a commendable accuracy.

Highlights

With the climbing threat of energy depletion and air pollutions,[1,2] there has been growing interest in the use of renewable fuels in recent years
This could be explained by the fact that the combustion phasing of fuels was retarded at lean conditions, but the engine was still running at gasoline’s maximum brake torque (MBT) at stoichiometric condition, and the advanced combustion phasing of butanol–gasoline blends was more suited, negating the impacts of improper combustion phasing on engine power
The engine performance and exhaust emissions of the engine fueled with butanol– gasoline blends were predicted using Artificial neural network (ANN) method

Summary

Introduction

With the climbing threat of energy depletion and air pollutions,[1,2] there has been growing interest in the use of renewable fuels in recent years. Biofuels, being one possible renewable fuel, are biodegradable and have potential to reduce air pollution.[3,4,5] The most common biofuel includes alcohols, vegetable oils, biodiesel, and so on. Alcohols have been extensively utilized in internal combustion engines due to its potential to reduce emission of greenhouse gas and toxic exhaust components, enhance overall energy efficiency, and reduce fuel costs.[6,7,8]. In comparison with methanol and ethanol, butanol being a viable alternative provides several advantages over them.

Methods

Results

Conclusion