Application of machine learning tools for constrained multi-objective optimization of an HCCI engine

Because of strict emission regulations, significant efforts are made by researchers to reduce the pollut-ants from internal combustion engines. Homogeneous mixture of fuel and air in Homogeneous Charge Compression Ignition (HCCI) engine results in lower amounts of thermal NOx while CO and HC emissions would be higher in this process. Besides, performance instability due to knock and misfire is another problem that HCCI engines are facing. In this paper, machine learning tools have been implemented to learn the behavior of a single-cylinder engine using three different fuels with the HCCI strategy. Changes in six objective functions with engine Inlet Valve Closing (IVC) temperature and air-fuel equivalence ratio are studied with the help of an Artificial Neural Network (ANN). Those objective functions are thermal efficiency, combustion efficiency, IMEP, together with NOx, CO, and HC emissions. A multi-objective optimization algorithm based on a decomposition method and genetic algorithm is used to identify the best operating condition of studied fuels. Results show that HCCI engine fueled with Ethanol and Methanol could produce significantly lower HC and CO emissions at their optimum point. However, the produced NOx would be higher in these cases comparing to the engine fueled with CNG. The genetic algorithm indicates that the optimum point of operation for CNG-fueled engine is T-IVC approximate to 445 K while lambda approximate to 2.25. In contrast, for the Ethanol-fueled case, this optimum point is located in the IVC temperature of approximate to 450 K and lambda approximate to 2.75. The TOPSIS point is located in minimum air-fuel equivalence ratio and lower IVC temperatures (T-IVC approximate to 420 K) when the engine is being operated with Methanol as fuel. (C) 2021 Elsevier Ltd. All rights reserved.

Automated summary

This study focuses on using machine learning tools to learn the behavior of a single-cylinder engine with HCCI strategy using different fuels. It analyzes the impact of engine Inlet Valve Closing (IVC) temperature and air-fuel equivalence ratio on six objective functions, including thermal efficiency, combustion efficiency, IMEP, NOx, CO, and HC emissions. The results show that HCCI engine fueled with Ethanol and Methanol could produce lower HC and CO emissions, but higher NOx emissions compared to CNG-fueled engine.