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.

在目前的研究，旨在确定液化石油气（LPG）的最佳比例可以在火花点火式的性能方面和排放有效地使用（SI）发动机上的响应面法汽油LPG混合物运行（ RSM）。为了创建RSM模型，LPG和发动机负荷被选为输入变量，而受到输入变量的性能和排放的响应被选定为制动燃料消耗率（BSFC），制动热效率（BTE），一氧化碳（CO），碳二氧化碳（CO ₂) 和碳氢化合物 (HC)。方差分析根据选定因素和反应进行（ANOVA）支持RSM分析，发现LPG对所有反应的显著效果。此外，得出的结论是燃油消耗率和BTE是LPG比变化影响最严重的反应。此外，根据该优化结果，最佳因子水平确定为35％和2400 W代表分别LPG和发动机负载，。根据核查研究，实验结果和优化结果之间的最大误差被发现为3.75％。结果表明，使用 RSM 可以成功地以低错误率对以 LPG 为燃料的 SI 发动机进行建模。