Dynamics observer for the longitudinal behavior of a wheelset on a roller rig

Abstract

The presented work illustrates the synthesis of a nonlinear model-based observer for the longitudinal dynamics estimation of a wheelset. This approach offers some significant improvements, such as an enhanced adherence to prescribed brake distances and an advanced usability of the condition-based maintenance of brake systems. The investigation of a single wheelset in a test rig environment enables, for example, the usage of an extended set of sensors to reliably validate the observers. The presented observer design process covers three main steps: identification of the characteristic system disturbances, implementation of the nonlinear observer dynamics, and parametrization of the observer via multicase optimization. With regard to the longitudinal dynamics, the variations of the friction conditions in the wheel–rail interface and in the interface between brake pads and brake disc have a crucial influence. Therefore, a parameter estimator and a disturbance observer are implemented, since these methods allow for a specific consideration of these disturbances. The obtained results prove that the observers accurately estimate the system behavior and provide reliable information on the longitudinal dynamics.

Nonlinear Observer Design for Guidance and Traction of Railway Vehicles

“…Fig. 2 presents corresponding results in the sequel to the DynORail project [2], where the adhesion conditions were measured on a true scale roller rig. The observer, an Extended Kalman Filter [4, Sec.…”

“…State observer design is a task that turned out to be crucial in several recent railway vehicles projects on active control and condition monitoring at DLR such as the Next Generation Train (NGT) [1] and the DynORail [2] project. Moreover, there are a number of existent or emerging vehicle technologies that rely on the capability to gain, process and communicate sensor data: (i) Active control of railway vehicles offers safety and comfort enhancements and allows for reducing energy consumption and wear.…”

“…In the simplest case related to the linear Luenberger Observer [4, Sec. 7.2], L L L may denote a constant feedback matrix whose entries are determined by offline numerical optimization using available measurements, see [2].…”

“…A survey on the parameter variations in operation revealed that the wheel radius r W , the brake radius r B,j and even the wheel load F j,z vary only little in comparison to the friction or adhesion coefficients, so that they may be assumed to be constant [2]. The assumptions µ WR,l ≈ µ WR , µ WR,r ≈ µ WR and µ DC,i ≈ µ DC enable a further simplification of the description.…”

Overview on the DLR RailwayDynamics Library

“…Already initiated and future applications of the library concern the synthesis of advanced observer and control lay-outs, (Schwarz et al, 2018), (Heckmann et al, 2016), and multidisciplinary simulation tasks such as the interaction of running dynamics and drive train, the systems engineering of pneumatic brake systems (Ehret, 2018) and research on advanced system design and assessment scenarios in order to ensure the crosswind stability of railway vehicles, cf. (Heckmann et al, 2014b).…”