Predictive modelling and optimization of performance and emissions of an auto-ignited heavy naphtha/n-heptane fueled HCCI engine using RSM

In this study, the effects of engine speed and lambda input parameters of a single-cylinder HCCI engine on the performance, combustion and emissions with the use of fuels with different concentrations were investigated. As finding of the best operating point of the engine perfomance is vital, therefore, in this research work the Response Surface Method waas used to model and optimize the process. The processes of determining the experimental sets, creating the model equations of the response parameters and performing the optimization were carried out with the RSM method. The engine speed was determined as 800-1600 rpm, the lambda value was 1.8-2.6 and the naphtha ratio in the mixed fuel was 0-100 %. As a result of the study, ANOVA tables, model equations, contour graphics of response parameters were created and the effects of input parameters were examined in detail. The accuracy of the model equations created by comparing the estimated and actual response parameter values has been strengthened. After the optimization, the optimum input parameters were calculated as 75 % naphtha ratio, 1166.75 rpm engine speed and 2.12 lambda value. The response parameter values ob-tained depending on the optimum input parameters are effective torque 6.26 Nm, indicated thermal efficiency 33.09 %, BSFC 196.79 g/kWh, CA10 0.77 degrees CA, CA50 5.6 degrees CA, combustion duration 28.84 degrees CA, COVimep 1.46 %, MPRR It was determined as 6.24 bar/degrees CA, UHC 375.96 ppm and CO 0.05 %.

Automated summary

This study investigates the effects of engine speed and lambda input parameters on the performance, combustion, and emissions of a single-cylinder HCCI engine using different fuel concentrations. The Response Surface Method is used to model and optimize the process. The study determines the optimum input parameters, including a 75% naphtha ratio, 1166.75 rpm engine speed, and 2.12 lambda value.