Abstract:

Energy-saving metro train control is closely related to the vertical track alignment (VTA) design, and both have a significant impact on operating costs. To further reduce operating costs based on optimized train control, this study proposed a collaborative optimization model for the VTA design phase. This model optimizes the bidirectional train control strategy and VTA of a metro section with the goal of minimizing energy consumption and maintenance costs simultaneously, while adhering to the constraints of scheduled train control and the requirements of the "Metro Design Code." Given the numerous factors affecting the maintenance costs of wheels and rails, a train-track dynamic simulation model was developed to calculate these costs. Based on this, an algorithm combining the pseudospectral method and brute force search was designed to solve the collaborative optimization model. The effectiveness of this optimization method was validated using three sections of the Guangzhou metro line. The results indicate that, compared to the method of optimizing scheduled train control alone on the actual VTA, the collaborative optimization model is more effective in saving operating costs, reducing the average operating costs by 21% across the studied sections. This study can provide novel approaches and theoretical support to further reduce metro operating costs, which contributes to promoting sustainable development of metro.

Key words: underground metro, train trajectory, track alignment design, operating cost, pseudospectral method