Today, the demand for higher output efficiencies, lower fuel consumption, and ever reduced emissions has been rising. Due to its availability, one promising alternative is the applying of hydrogen in internal combustion engines. In this study, the initial efforts concentrated on combine relationships of input and output parameters of hydrogen compressed natural gas spark-ignition engine. The quadratic regression models were conducted for all six responses: torque, carbon monoxide, brake-specific fuel consumption, methane, nitrogen oxides, and total hydrocarbon through response surface methodology and tested for adequacy by analysis of variance. The multi-objective desirability approach employed for the optimization of input variables, namely, the hydrogen compressed natural gas ratio, excess air ratio ( λ), and ignition timing ( θi). Also, two factors, that is, manifold absolute pressure and engine speed, were fixed at 105 kPa and 1600 r/min, respectively. Results indicate that the optimal independent input factors are equal to λ of 1.178, hydrogen compressed natural gas ratio of 25.98%, and θi of 18 °CA before top dead center. Also, the optimal combination of responses is as follows: brake-specific fuel consumption of 219.334 g/kWh, the torque of 395 N m, 30.189 g/kWh for nitrogen oxides, carbon monoxide equal to 5.093 g/kWh, total hydrocarbon of 0.633 g/kWh, and 0.572 g/kWh for methane. This study provided the significance of response surface methodology as an attractive technique for investigators for modeling. In this regard, the response surface methodology modeling and multi-objective desirability approach can be utilized to predict the emission and performance characteristics of the hydrogen compressed natural gas engines minutely.
