Effect of self-steering locomotive trucks in improving adhesion on curved tracks

The primary purpose of this study is to provide a qualitative analysis of the effects of the self-steering trucks that are commonly used by the US Railroads-namely, EMD's radial truck and GE's steerable truck-on increasing adhesion in curves. Although there exists a number of anecdotal statements about the ability of steerable trucks in general, and self-steering trucks in particular, in increasing adhesion on curves, to the best of the authors' knowledge, there exists no study that provides a qualitative or quantitative analysis of this aspect of steerable trucks. Two aspects of locomotive trucks are essential for their ability to deliver high adhesion in curves. First, the ability to allow the axles to yaw sufficiently relative to the truck frames, such that they can hold a small angle of attack with the rail. Second, providing sufficiently large longitudinal stiffness between the axles and the truck frame, to accommodate the high adhesions. An equivalent stiffness analysis is used to show that the two steerable trucks that are considered for this study are far superior to the conventional, three-axle, straight trucks in providing both a smaller angle of attack and a higher longitudinal stiffness for better adhesion characteristics. The qualitative analysis of this study agrees with the experience of the US Railroads with the adhesion performance of their self-steering trucks. Although not aware of any adhesion data published in the open literature, the authors are familiar with several attempts by the original equipment manufacturers and railroads to collect adhesion data for self-steering trucks. Similar to the findings of this study, the results of such experiments have often indicated the ability to deliver higher adhesion by self-steering trucks as compared to straight trucks. Further, the railroads have experienced that in their operation they can get higher adhesion in curves from steerable trucks than conventional straight trucks.