Analysis on new semi-active control strategies to reduce lateral vibrations of high-speed trains by simulation and hardware-in-the-loop testing

Abstract

In order to further reduce the vibration of vehicles and simultaneously increase ride comfort, a class of new control strategies, namely, the extension of Rakheja-Sankar (RS) control, is proposed for semi-active suspension systems with magnetorheological (MR) dampers of high-speed trains. At first, the design and analysis of semi-active control strategies are conducted in a quarter railway lateral model considering the node stiffness. Secondly, a whole vehicle model of a high-speed train is constructed by using Universal Mechanism (UM) software to be applied in evaluating semi-active control strategies. Finally, a hardware-in-the-loop (HIL) test system is carried out to verify the performance of the new control strategies. During these processes, the transmission characteristics are calculated and compared, which helps to test the performance of the semi-active control strategy on train vibration suppression. Then, the effect of the control strategies on the dynamic performance of the whole vehicle is studied. The ride comfort under different control strategies is compared, and the effects of different semi-active control strategies on the lateral stability and safety of trains are also analyzed. Through simulations and experiments, it is confirmed that the new control strategies can effectively reduce the lateral vibration of trains and therefore contribute to the improvement of ride comfort while they do not significantly reduce the train running stability and safety. Therefore, the new control strategies possess future application value.

Modelling and Dynamic Analysis of Adaptive Neuro-Fuzzy Inference System-Based Intelligent Control Suspension System for Passenger Rail Vehicles Using Magnetorheological Damper for Improving Ride Index

“…To develop the ANFIS setup, data for training and checking are obtained from the mathematical model of the MR damper proposed by Spencer et al [4]. A 2-input type-3 ANFIS with 9 if-then rules is used to construct the fuzzy inference system (FIS).…”

“…Semi-active suspension systems, in particular, garnered attention due to their potential to adapt to changing conditions while avoiding the complexity and energy consumption associated with fully active systems. Researchers like Cebon and Wong focused on semi-active control methods, investigating how controlled dampers can improve ride quality and safety [3,4].…”