Comfort improvement in railway vehicles via optimal control of adaptive pneumatic suspensions

This paper presents an adaptive optimal control strategy focused on improving ride comfort by minimising the root mean square of accelerations measured at seven locations on the carbody floor. It requires preview knowledge of both the train speed and the standard track quality (not the deterministic track disturbances) and differs from other works in considering pointwise constraints (upper and lower secondary suspension travel limits). Adaptive control is achieved by varying the diameter of the restriction orifice which connects the pneumatic spring to the auxiliary air reservoir, which confers different dynamic stiffness and damping to the front and rear secondary suspensions. Decision maps with the front and rear optimal diameters for five track irregularity levels and six different speeds were obtained using a Monte Carlo strategy based on solving the optimal control problem for 240 stochastic realisations of time-varying track irregularities of 300 s. Results show that the adaptive optimal control provides a successful compromise between comfort and safety which overshadows the conventional passive approach: it improves comfort up to 50% with respect to stiff passive configurations and it guarantees constraint fulfilment unlike compliant passive configurations.