Modelling and iterative learning control of internal pressure for high-speed trains under excitation of varying-amplitude tunnel pressure waves

Abstract

Traditional control algorithm of shutting down the air ducts for a fixed period is not applicable to take both the riding comfort and the air quality inside high-speed train carriages into account in long tunnels. Inspired by the morphological similarity of the tunnel pressure waves generated by the same train passes through the same tunnel, an upgraded iterative learning control algorithm for suppressing the air pressure variation excited by the quasi-periodic varying-amplitude tunnel pressure wave is developed. Firstly, the mathematical model of the control system is established, in which the air ducts, gaps and random interferences are considered. Then, the methodology of determining the goal in each iteration is formed, and the implementation of the iterative learning control algorithm is discussed. Finally, simulations of the algorithm are carried out. The simulation results show that in the upgraded iterative learning control algorithm, both the goal and the output of the air pressure inside the carriage will converge into a range determined by the amplitude and random interferences. By comparing with the traditional control algorithm, the upgraded iterative learning control algorithm is more adaptable to meet the needs of riding comfort.

Internal pressure iterative learning control for high-speed trains based on condition and performance matching under morphologically similar tunnel pressure waves

“…To suppress the pressure variation inside the carriage, on the one hand, it is helpful to enhance the airtightness and strength of the car body; on the other hand, it is necessary to improve the performance of the ventilation system and adopt the advanced internal pressure fluctuation control strategy 3 . However, the enhancement of train airtightness will increase the cost of train manufacturing 4 . And the traditional passive control of closing the air ducts for a fixed time may cause greater internal pressure fluctuation when the air ducts are reopened, and closing the air ducts for a long time will affect the air quality inside the carriage 4 .…”

“…However, the enhancement of train airtightness will increase the cost of train manufacturing 4 . And the traditional passive control of closing the air ducts for a fixed time may cause greater internal pressure fluctuation when the air ducts are reopened, and closing the air ducts for a long time will affect the air quality inside the carriage 4 . Therefore, it is of great significance to study the control strategy of matching the opening and closing time of the air ducts with the characteristics of tunnel pressure waves.…”

Internal pressure control for high-speed trains based on condition matching and performance iteration

“…In the field of railway transportation, Yu et al (2017) proposed an ILC scheme to solve the speed tracking problem, making utilising the repetitive characteristics in system control possible. He et al (2021aHe et al ( , 2021b tried to apply the morphological similarities in controlling the internal pressure for highspeed trains. But, the researches by He et al (2021aHe et al ( , 2021b did not take the varying-amplitude and varying-scale characteristics into consideration, by which a general rather than an adaptive opening degree for the air ducts can be generated.…”

“…He et al (2021aHe et al ( , 2021b tried to apply the morphological similarities in controlling the internal pressure for highspeed trains. But, the researches by He et al (2021aHe et al ( , 2021b did not take the varying-amplitude and varying-scale characteristics into consideration, by which a general rather than an adaptive opening degree for the air ducts can be generated.…”

“…Therefore, in this paper, the morphological similarities of the tunnel pressure wave will be applied to generate a proper opening degree for air ducts and further control the internal pressure of the high-speed trains. Different from He et al (2021aHe et al ( , 2021b, an ILC scheme of condition matching and performance iteration is proposed in this paper to control the internal pressure. In this scheme, the opening degree will be matched with that in the nearest condition before the train passes through the tunnel.…”