A mechatronic two-axle rail vehicle with only one suspension step is introduced in the Shift2Rail project Pivot2. This vehicle design reduces the vehicle weight in comparison to standard bogie vehicles. However, having only one suspension step drastically decreases passenger comfort. Thus, hydraulic actuators are introduced instead of passive dampers and active modal sky-hook control is applied. Due to the strong interaction between the running gear frame and the carbody, a blended modal solution is applied where a percentage of the acceleration of the frame is used in the feedback loop in addition to the acceleration of the carbody. To assess the performance of the controllers, simulations are carried out with the vehicle running at constant speeds from 10 km/h to 120 km/h on tangent track with high level of track irregularities. First, multiplicative dimensional reduction method (M-DRM) sensitivity analysis is applied to determine the importance of the control variables and subsequently a genetic algorithm (GA) optimization is performed to identify the control gains for each speed. The blended control proposed here can improve passenger comfort with respect to a standard modal control while maintaining similar energy and force usage.

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Innovative Two-Axle Vehicle with Improved Ride Comfort via Blended Active Vibration Control

  • Rocco Libero Giossi,
  • Rickard Persson,
  • Sebastian Stichel

摘要

A mechatronic two-axle rail vehicle with only one suspension step is introduced in the Shift2Rail project Pivot2. This vehicle design reduces the vehicle weight in comparison to standard bogie vehicles. However, having only one suspension step drastically decreases passenger comfort. Thus, hydraulic actuators are introduced instead of passive dampers and active modal sky-hook control is applied. Due to the strong interaction between the running gear frame and the carbody, a blended modal solution is applied where a percentage of the acceleration of the frame is used in the feedback loop in addition to the acceleration of the carbody. To assess the performance of the controllers, simulations are carried out with the vehicle running at constant speeds from 10 km/h to 120 km/h on tangent track with high level of track irregularities. First, multiplicative dimensional reduction method (M-DRM) sensitivity analysis is applied to determine the importance of the control variables and subsequently a genetic algorithm (GA) optimization is performed to identify the control gains for each speed. The blended control proposed here can improve passenger comfort with respect to a standard modal control while maintaining similar energy and force usage.