Abstract

In this work, we have developed a serial-chain multibody model of a rail vehicle, using the Decoupled Natural Orthogonal Complement matrices. The governing equations of the system were linearized, and the start of hunting was identified by finding the Smallest Bifurcation Point (SBP) of the trivial solution. Uneven wear creates differences in the properties of similar components in a rail vehicle. It was found that such variations are neglected in the hunting analysis. Hence, we introduce these differences by independently changing 32 parameters. The study found that these variations lead to unique trends. Then, these trends were used to recommend design changes for a rail vehicle, which could be thought of, in order to improve the hunting characteristics. For this purpose, an interactive software tool was created to easily visualize, and manipulate the hunting behavior of a rail vehicle.

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