2002Unpublished venueRequires access

Study of Truck Tire Pressure in Texas

Feng Wang, Randy B. Machemehl

Open publisher page 3 citations

Abstract

To characterize in-service truck tire pressure and truck configurations on Texas highways, a survey on major Texas trucking routes was conducted. Analysis of the collected tire pressure data showed that factors such as axle weight, tire temperature, geographic area, highway class, traveled distance, and axle type, contributed to in-service tire pressure values. In this study, a factorial experiment design and stratified sampling method were employed. Analysis of variance, analysis of covariance, and t tests were used for the comparison of truck tire pressure data; laboratory experiments and linear regression were used to identify relationship between tire pressure and tire temperature. Comparisons and analyses of factors differentiating truck tire pressure are presented.

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What this paper is about

To characterize in-service truck tire pressure and truck configurations on Texas highways, a survey on major Texas trucking routes was conducted. Analysis of the collected tire pressure data showed that factors such as axle weight, tire temperature, geographic area, highway class, traveled distance, and axle type, contributed to in-service tire pressure values. In this study, a factorial experiment design and stratified sampling method were employed. Analysis of variance, analysis of covariance, and t tests were used for the comparison of truck tire pressure data; laboratory experiments and linear regression were used to identify relationship between tire pressure and tire temperature. Comparisons and analyses of factors differentiating truck tire pressure are presented.

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Available abstract

To characterize in-service truck tire pressure and truck configurations on Texas highways, a survey on major Texas trucking routes was conducted. Analysis of the collected tire pressure data showed that factors such as axle weight, tire temperature, geographic area, highway class, traveled distance, and axle type, contributed to in-service tire pressure values. In this study, a factorial experiment design and stratified sampling method were employed. Analysis of variance, analysis of covariance, and t tests were used for the comparison of truck tire pressure data; laboratory experiments and linear regression were used to identify relationship between tire pressure and tire temperature. Comparisons and analyses of factors differentiating truck tire pressure are presented.

Key concepts: Truck, Axle, Automotive engineering, Axle load, Environmental science, Factorial experiment, Pressure measurement, Regression analysis

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