Improving the combustion process by determining the optimum percentage of liquefied petroleum gas (LPG) via response surface methodology (RSM) in a spark ignition (SI) engine running on gasoline-LPG blends

In the current research, it is aimed to determine the optimum ratio of liquefied petroleum gas (LPG) to be used efficiently in terms of performance and emissions in a spark-ignition (SI) engine running on gasoline-LPG blends with response surface methodology (RSM). To create the RSM model, LPG and engine load were selected as input variables, while performance and emission responses affected by input variables were selected as brake specific fuel consumption (BSFC), brake thermal efficiency (BTE), carbon monoxide (CO), carbon dioxide (CO2), and hydrocarbon (HC). Analysis of variance (ANOVA) supported RSM analysis was performed according to the selected factors and responses, it was found that LPG had a significant effect on all responses. Moreover, it was concluded that BSFC and BTE are the most affected responses to LPG ratio change. Also, according to the optimization results, the optimum factor levels were determined as 35% and 2400 W for LPG and engine load, respectively. According to the verification study, the maximum error between the experimental results and the optimization results was found as 3.75%. As a result, it is concluded that the SI engine fueled with LPG can be successfully modeled with low error rates by using RSM.

Automated summary

The study aimed to optimize the use of liquefied petroleum gas (LPG) in gasoline-LPG blends for an SI engine, focusing on performance and emissions. Response surface methodology (RSM) was utilized to determine the optimal LPG ratio, with findings showing significant effects on various responses, particularly BSFC and BTE. Verification study revealed low error rates in modeling the SI engine with RSM.