Integrated Model Predictive Control of High-Speed Railway Running Gears with Driven Independently Rotating Wheels

TL;DR

This work tackles the problem of integrated lateral and longitudinal control for high-speed railway running gears equipped with driven independently rotating wheels (IRW). It introduces an integrated controller that combines a nonlinear model predictive control (NMPC) lateral guidance scheme with an adhesion-based longitudinal controller, augmented by a track-geometry preview mechanism and a flexible integration rule to balance objectives. The key contributions are: (i) first application of MPC to lateral guidance for IRW running gears, (ii) a novel adhesion-based longitudinal controller capable of regular operation and maximum-seeking adhesion without detailed wheel–rail contact models, and (iii) a variable-structure integration approach enabling smooth shifting between lateral and longitudinal emphasis. Validation via a detailed multi-body simulation shows improved lateral tracking and braking performance over a state-of-the-art ndi controller, with a linear time-variant MPC variant offering substantial computation-time reductions for real-time feasibility. The results support the potential of MPC-based integrated control to enhance safety, ride comfort, and wear characteristics in future high-speed rail concepts, while highlighting directions for real-world experimentation and centralized control architectures.

Abstract

Railway running gears with independently rotating wheels (IRW) can significantly improve wear figures, comfort, and safety in railway transportation, but certain measures for wheelset stabilization are required. This is one reason why the application of traditional wheelsets is still common practice in industry. Apart from lateral guidance, the longitudinal control is of crucial importance for railway safety. In the current contribution, an integrated controller for joined lateral and longitudinal control of a high-speed railway running gear with driven IRW is designed. To this end, a novel adhesion-based traction control law is combined with linear time-variant and nonlinear model predictive control (MPC) schemes for lateral guidance. The MPC schemes are able to use tabulated track geometry data and preview information about set points to minimize the lateral displacement error. Co-simulation results with a detailed multi-body simulation show the effectiveness of the approach compared with state-of-the-art techniques in various scenarios, including curving, varying velocities up to 400 km/h and abruptly changing wheel-rail adhesion conditions.

Figures (9)

• Figure 1: System overview of a railway running gear with irw.
• Figure 2: Schematic adhesion-slip characteristics with good (a) and poor (b) adhesion conditions.
• Figure 3: Simplified model of a railway running gear with irw for use in mpc.
• Figure 4: Schematic of the mpc-based integrated control system for railway running gears.
• Figure 5: Operational segments of adhesion control scheme for two scenarios: desired adhesion $f_{x_j}^{*}<f_{x_{\mathrm{max}}}$ (left) or $f_{x_j}^{*}>f_{x_{\mathrm{max}}}$ (right). Operation in segment (I): torque to be increased. Operation in segment (II): no torque change. Operation in segment (III): torque to be decreased.