Stability enhancement of a high-speed train bogie using active mass inertial actuators |
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Authors: | Yuan Yao Guang Li Yousef Sardahi |
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Institution: | 1. State Key Laboratory of Traction Power, Southwest JiaoTong University, Chengdu, People's Republic of China;2. State Key Laboratory of Heavy Duty AC Drive Electric Locomotive Systems Integration, Changsha, People's Republic of China;3. College of Information Technology &4. Engineering, Marshall University, Huntington, WV, USA |
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Abstract: | In this study, a method regarding frame lateral vibration control based on the state feedback of an additional oscillator is proposed, so as to improve the bogie hunting stability. The multi-objective optimisation method (MOOP), with two objective functions of the stability index and control effort, is solved by the NSGA-II algorithm to obtain the feedback gains. The frame lateral vibration control can effectively improve the bogie hunting stability according to the linear and non-linear analysis of a high-speed train bogie, in which a fault of the yaw damper and time delay in the control system are considered. The effect of the oscillator suspension parameters and time delay on the system stability and robustness are analysed. The results show that the damped vibration frequency of the oscillator should be equal to the bogie hunting frequency, but a harder oscillator suspension can be used to improve the hunting critical speed margin of the bogie control system. However, just as how the feeding the frame states back directly, a hard oscillator suspension will lead to instability in the control system at a certain time delay. Therefore, the improvement of bogie hunting stability and reduction of control system stability must be considered when optimising the oscillator parameters. For the 350?km/h train bogie covered in this study, the optimal mass, natural frequency and damping ratio of the additional oscillator are acquired. |
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Keywords: | High-speed train bogie hunting stability active control time delay multi-objective optimisation finite dimensional state space approximation |
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