Improving the energy efficiency and riding comfort of high-speed trains across slopes by the optimized suspension control

Duo Zhang, Zi-Yu Tao, Kai Zhou, Fang-Ru Zhou, Qi-Yuan Peng and Yin-Ying Tang

Energy, 2024, vol. 307, issue C

Abstract: As the link between cities, the high-speed train (HST) not only effectively enhances national and regional accessibility, but also induces much energy consumption. On the other hand, passengers have a higher requirement for riding comfort of HST than before. Considering the impacts of slope gradient on energy consumption and vertical carbody acceleration, this paper optimizes the scale factor of the damper controller depending on the running condition to juggle the energy efficiency and riding comfort when HST is across slopes. Firstly, the multibody dynamics simulation model of HST is established to evaluate the energy consumed by motion resistances and carbody vibrations. Then the Skyhook control strategy is applied to the secondary vertical damper of the vehicle model. The effects of vehicle speed, slope gradient, and scale factor of the Skyhook controller on energy saving and vertical carbody acceleration of HST are investigated. Based on the simulation results, the Gaussian process regression model is established to predict the vehicle performance and describe the bi-objective optimization problem. It is demonstrated that the optimized Skyhook control system can at most save energy consumed by motion resistances by 8.52 % or reduce vertical carbody acceleration by 37.14 % without sacrificing the other target. Finally, a comprehensive feasibility and economic analysis of the proposed control system is carried out to promote its practical implementation.

Keywords: High-speed train; Energy efficiency; Riding comfort; Multibody dynamics simulation; Gaussian process regression; Bi-objective optimization (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:307:y:2024:i:c:s0360544224024344

DOI: 10.1016/j.energy.2024.132660

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