Real time eco-driving of high speed trains by simulation-based dynamic multi-objective optimization

Fernández-Rodríguez, Adrián; Fernández-Cardador, Antonio; Cucala, Asunción P.

doi:10.1016/j.simpat.2018.01.006

Cited by 41 publications

(11 citation statements)

References 62 publications

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“…In recent studies [53], [54], [55], GA PTO methods were applied to both conventional and electric vehicles with results showing favorable fuel economy improvement for both types of vehicles. PSO was used in various studies to optimize energy consumption for individual vehicles [52], [56], [57], [58] and to streamline vehicle platoon behavior at intersections [59]. A comparison of PSO-based PTO method with DP [58] found that PSO significantly underperformed DP in terms of efficiency but executed in significantly less time.…”

Section: Polynomial Trajectory Optimizationmentioning

confidence: 99%

Real-Time Implementation Comparison of Urban Eco-Driving Controls

Rabinowitz,

Ang,

Mahmoud

et al. 2024

IEEE Trans. Contr. Syst. Technol.

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Connected autonomous vehicle (CAV) technology has the potential to enable significant gains in energy economy (EE). Much research attention has been focused on autonomous eco-driving control enabled by various methods. In this study, the state of the literature on autonomous eco-driving control is reviewed, an overall systems' description of eco-driving control for a CAV is provided, and representative methods are evaluated comparatively against each other in simulation. Simulations are conducted using real-world traffic signal data and a validated future automotive systems technology simulator (FASTSim) model. Results indicate that an EE improvement in the range of 5%-15% is attainable depending on the method and cost function used. In this article it is shown that dynamic programming (DP) methods are most effective in improving EE but are significantly more computationally expensive than other methods. The genetic algorithm (GA) methods are shown to present the most potential in terms of EE improvement and run-time. Results also indicate that velocity-sensitive cost functions allow all the methods to perform better than pure acceleration minimization.

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Section: Polynomial Trajectory Optimizationmentioning

confidence: 99%

Real-Time Implementation Comparison of Urban Eco-Driving Controls

Rabinowitz,

Ang,

Mahmoud

et al. 2024

IEEE Trans. Contr. Syst. Technol.

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“…Sun et al [14] proposed a multi-objective optimization model for train routing on a high-speed railway network, thereby providing an important reference for train planning to provide better services. Fernández-Rodríguez et al [31] described the train scheduling problem as a dynamic multi-objective optimization model that utilizes accurate results provided by detailed real-time train simulations. Mateus et al [32] described a multi-criteria decision analysis approach that identified the best alternative from a given set of possible alternatives.…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-Objective Optimization for High-Speed Railway Network Based on “Demand–Supply–Management” Model

Hu,

Bian,

Lin

et al. 2023

Applied Sciences

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This paper develops a multi-objective optimization model for national high-speed railway network planning. Three objectives are proposed from the macro, meso, and micro perspectives, and these three objectives are considered simultaneously. Using real data, case studies are conducted to optimize China’s “four east–west and four north–south railway lines” network, which includes Beijing, Shanghai, Wuhan, Guangzhou, and Zhengzhou as main hubs. The results show that, on the one hand, the optimization model reduces the overlap between long-distance passengers and short-distance passengers on the high-speed railway line, facilitates the travel of passengers, and improves the line service capability; on the other hand, optimization of the network shortens the travel time of the passengers, reduces the cost of the railway, and improves the operation efficiency of the high-speed railway line network. The results show that the total travel time of all high-speed railway passengers in the optimization model is reduced by 18.4%, while the benefit rate of the operator increased by 21.99%.

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“…Also, the impact of rotational inertia caused by the rotating parts of a train, for example, wheels and motors, should be considered in its linear motion. This rotational effect can be modelled by increasing the tare mass of the train (between 5% and 15%) for the number of motored axles [32]. Thus,

λ^{R M F}

, which expressed the rotating mass factor of the train is employed.…”

Section: The Integrated Energy Hub Systemsmentioning

confidence: 99%

Optimal coordinated operation of integrated energy hubs, considering regenerative braking utilization

Akbari

Fazel

Jadid

2021

IET Electrical Syst in Trans

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This article presents a coordinated operation model for energy management of a multiintegrated energy system based on Mixed-Integer Linear Programing (MILP). The power derived by trains from regenerative braking energy (RBE), during deceleration, is utilised to meet the interconnected energy hubs' (IEHs) demand. The recovered energy is calculated by simulating the motion of the trains in MATLAB software. The electricity and heat demand response (DR) programs are integrated into the proposed model to study their impacts on the operating cost and the carbon emission of the IEH, considering several case studies. Furthermore, the uncertainties of the RBE, photovoltaic power generation, and loads of the IEH are considered by formulating the optimisation problem stochastically through a scenario-based approach. Therefore, a scenario generation and reduction decision-making technique is employed. Finally, the GAMS optimisation software is used to assess the efficiency of the presented MILP model. The simulation results indicate that the total operating cost of the IEH reduced 2.0% and 1.4% in the case studies. Also, the CO 2 emission is decreased by about 0.3% by applying the coordination scheme besides the DR programs.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Real time eco-driving of high speed trains by simulation-based dynamic multi-objective optimization

Cited by 41 publications

References 62 publications

Real-Time Implementation Comparison of Urban Eco-Driving Controls

Real-Time Implementation Comparison of Urban Eco-Driving Controls

Multi-Objective Optimization for High-Speed Railway Network Based on “Demand–Supply–Management” Model

Optimal coordinated operation of integrated energy hubs, considering regenerative braking utilization

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