Abstract

The load factor (LF) of a tractor represents the ratio of actual engine power and rated engine power, and is an important indicator directly used in calculating national air pollutant emissions. Currently, in the Republic of Korea, a fixed value of 0.48 is used for the LF regardless of the working conditions, making it difficult to establish a reliable national air pollutant inventory. Since tractors perform work under soil conditions, soil physical properties directly affect the tractor LF. Therefore, it is expected that more accurate LF estimation will be possible by utilizing soil physical properties. This study was conducted to assess the impact of soil physical properties on the LF. Experimental data were collected in ten different soil conditions. Correlation analysis revealed that the LF exhibited strong correlations with SMC, soil texture, and CI, in that order. The coefficient of determination for the regression model developed using soil variables ranged from 0.678 to 0.926. The developed regression models generally showed higher accuracy when utilizing multiple soil variables, as compared to using a single soil variable. Therefore, an effective estimation of the LF through non-experimental methods can be achieved by measuring various soil properties.

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