A speed trajectory optimization model for rail vehicles using mixed integer linear programming

Tan, Zhaoxiang; Lu, Shaofeng; Xue, Fei; Bao, Kai

doi:10.1109/itsc.2017.8317807

Cited by 4 publications

(4 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Much effort so far has been put into developing energysaving operating schemes for trains. In earlier work, the optimization of the train speed trajectory is usually formulated as a mixed-integer linear programming (MILP) problem for minimum energy consumption [14]- [17], while some approximations using linearization are required. With later advances in computer performance, more studies were focused on developing meta-heuristic algorithm based optimization models [18]- [25].…”

Section: Romentioning

confidence: 99%

Robust Optimization of Energy-Saving Train Trajectories Under Passenger Load Uncertainty Based on p-NSGA-II

Xing

Zhang

et al. 2023

IEEE Trans. Transp. Electrific.

View full text Add to dashboard Cite

show abstract

Section: Romentioning

confidence: 99%

Robust Optimization of Energy-Saving Train Trajectories Under Passenger Load Uncertainty Based on p-NSGA-II

Xing

Zhang

et al. 2023

IEEE Trans. Transp. Electrific.

View full text Add to dashboard Cite

show abstract

“…e choice of space as the independent variable simplifies the consideration of track-related data, e.g., the speed limits and the line condition, including the curves, grades, and tunnels. Moreover, the discrete-space method has been used in many previous studies to study the train control problem (e.g., Lu et al [14], Tan et al [15], and Wu et al [16]).…”

Section: Discrete-space Train Movement Modelmentioning

confidence: 99%

“…Finally, to linearize the nonlinear speed-related constraints (8), ( 9), and ( 13), the following mixed-integer constraints determined by using a similar piecewise linear approach as in Tan et al [15] and Wu et al [16] should be imposed on the model:…”

Section: Cur I − 30mentioning

confidence: 99%

A Discrete-Space Train Movement Model for a High-Speed Train under Temporary Speed Restriction

Long

Meng

Wang

et al. 2020

Mathematical Problems in Engineering

View full text Add to dashboard Cite

This paper constructs a discrete-space train movement model to evaluate the impact of a temporary speed restriction (TSR) for a high-speed railway train. The established model can demonstrate train movement under different TSR conditions. The proposed model can reveal whether a train is affected by the block section influenced by the TSR within a time duration. Moreover, the model can output detailed train trajectories and the minimal train running time between two adjacent stations to analyse the impact of the TSR. Based on the experimental results, we carry out a comprehensive analysis of the impact of several factors on the running time and train trajectories, including the length of the affected area (i.e., number of affected block sections), the location of the TSR, the limited speed value, and the stopping patterns of the train at two adjacent stations. The experiments show that the proposed discrete-space train movement model can be used to analyse the impact of the TSR on a high-speed railway train under various considered TSR conditions.

show abstract

“…The authors in [6] applied MILP to address non-linear constraints arising from varying gradients along the braking route for partial speed trajectory optimization problems. By formulating the speed trajectory optimization as an MILP model, the authors in [48] tried to optimize the speed trajectory to achieve the minimum net energy. Further to this work, this paper develops and proposes an MILP model for adaptive partial speed trajectory optimization with considerations of motor efficiency during regenerative braking and traction.…”

Section: Publication Algorithms/theory Multiple/single Train(s)mentioning

confidence: 99%

Adaptive Partial Train Speed Trajectory Optimization

Tan

Bao

et al. 2018

Energies

Self Cite

View full text Add to dashboard Cite

Train speed trajectory optimization has been proposed as an efficient and feasible method for energy-efficient train operation without many further requirements to upgrade the current railway system. This paper focuses on an adaptive partial train speed trajectory optimization problem between two arbitrary speed points with a given traveling time and distance, in comparison with full speed trajectory with zero initial and end speeds between two stations. This optimization problem is of interest in dynamic applications where scenarios keep changing due to signaling and multi-train interactions. We present a detailed optimality analysis based on Pontryagin’s maximum principle (PMP) which is later used to design the optimization methods. We propose two optimization methods, one based on the PMP and another based on mixed-integer linear programming (MILP), to solve the problem. Both methods are designed using heuristics obtained from the developed optimality analysis based on the PMP. We develop an intuitive numerical algorithm to achieve the optimal speed trajectory in four typical case scenarios; meanwhile, we propose a new distance-based MILP approach to optimize the partial speed trajectory in the same scenarios with high modeling precision and computation efficiency. The MILP method is later used in a real engineering speed trajectory optimization to demonstrate its high computational efficiency, robustness, and adaptivity. This paper concludes with a comparison of both methods in addition to the widely applied pseudospectral method and propose the future work of this paper.

show abstract

A speed trajectory optimization model for rail vehicles using mixed integer linear programming

Cited by 4 publications

References 12 publications

Robust Optimization of Energy-Saving Train Trajectories Under Passenger Load Uncertainty Based on p-NSGA-II

Robust Optimization of Energy-Saving Train Trajectories Under Passenger Load Uncertainty Based on p-NSGA-II

A Discrete-Space Train Movement Model for a High-Speed Train under Temporary Speed Restriction

Adaptive Partial Train Speed Trajectory Optimization

Contact Info

Product

Resources

About