Energy-Efficient Train Operation Using Nature-Inspired Algorithms

Keskin, Kemal; Karamancioğlu, Abdurrahman

doi:10.1155/2017/6173795

Cited by 30 publications

(21 citation statements)

References 51 publications

(62 reference statements)

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“…In [21] the authors present an algorithm that is a combination between GA and SA, a so-called Genetic Simulated Annealing Algorithm. The objective of joining both algorithms is to eliminate its individual weaknesses and to enhance its advantages.…”

Section: Literature Reviewmentioning

confidence: 99%

A New Approach for Real Time Train Energy Efficiency Optimization

et al. 2018

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Efficient use of energy is currently a very important issue. As conventional energy resources are limited, improving energy efficiency is, nowadays, present in any government policy. Railway systems consume a huge amount of energy, during normal operation, some routes working near maximum energy capacity. Therefore, maximizing energy efficiency in railway systems has, recently, received attention from railway operators, leading to research for new solutions that are able to reduce energy consumption without timetable constraints. In line with these goals, this paper proposes a Simulated Annealing optimization algorithm that minimizes train traction energy, constrained to existing timetable. For computational effort minimization, re-annealing is not used, the maximum number of iterations is one hundred, and generation of cruising and braking velocities is carefully made. A Matlab implementation of the Simulated Annealing optimization algorithm determines the best solution for the optimal speed profile between stations. It uses a dynamic model of the train for energy consumption calculations. Searching for optimal speed profile, as well as scheduling constraints, also uses line shape and velocity limits. As results are obtained in seconds, this new algorithm can be used as a real-time driver advisory system for energy saving and railway capacity increase. For now, a standalone version, with line data previously loaded, was developed. Comparison between algorithm results and real data, acquired in a railway line, proves its success. An implementation of the developed work as a connected driver advisory system, enabling scheduling and speed constraint updates in real time, is currently under development.

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Section: Literature Reviewmentioning

confidence: 99%

A New Approach for Real Time Train Energy Efficiency Optimization

et al. 2018

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“…On the other hand, when no storage devices are available, a timetable optimization, aimed at synchronizing acceleration and deceleration phases of convoys operating in the network, represents a key task for maximizing the receptivity of the line (see, for instance, [11][12][13][14]). Additionally, the role of an energy-efficient timetabling phase lies in a suitable design of all operational times involved, such as running times, buffer times, dwell times and reserve times [15][16][17][18]. Moreover, by means of reversible or active substations, the regenerated energy can also be traced back to the medium voltage distribution network [19,20].…”

Section: Literature Reviewmentioning

confidence: 99%

A Passenger-Oriented Optimization Model for Implementing Energy-Saving Strategies in Railway Contexts

D’Acierno

Botte

2018

Energies

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Rail and metro systems are characterized by high-performing and environmentally friendly features that make them a crucial factor for driving modal split towards public transport modes, thus reducing private car use and related externalities (such as air and noise pollution, traffic congestion and accidents). Within this framework, the implementation of suitable energy-saving policies, allowing to reduce energy consumption, but, at the same time, preserving timetable stability and passengers’ satisfaction, may turn out to be imperative. In particular, this study aims to develop an analytical framework for properly supporting the implementation of eco-driving strategies in a passenger-oriented perspective. An application to a rail line in southern Italy is performed so as to demonstrate the usefulness of the proposed approach in determining the optimal compromise between energy reductions and travel time increases.

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“…Train safety is an important issue in transportation systems [1]. One key feature of train control technologies is traction system control [2][3][4][5]. Previous studies have transformed the traction system into a multi-agent system and identified consensus problem as the basis and core of maintaining a coordinated control of this system [6,7].…”

Section: Introductionmentioning

confidence: 99%

Virtual Line Shafting-Based Total-Amount Coordinated Control of Multi-Motor Traction Power

Chen

Mao

et al. 2020

Journal of Advanced Transportation

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This paper investigates a virtual line shafting-based total-amount coordinated control method of multi-motor traction power to solve the traffic safety problem caused by train traction power loss. This method considers the total amount instead of the synchronous control amongst single motors in a multi-motor control system. Firstly, a block diagram of the proposed method is built. Secondly, on the basis of this diagram, an accurate system model with parameter perturbations is constructed. Thirdly, a virtual controller is designed to quickly adjust the output torque of the virtual motor and to realise a tracking control of the reference torque. A total-amount coordinated control strategy based on the integral sliding mode is also designed to keep the total traction power of the multi-motor system constant under uncertain and unknown disturbances. Lyapunov stability theory is used to prove the system stability. The simulation and experiment results verify the effectiveness of the virtual controller and the total-amount coordinated control strategy in guaranteeing system robustness under disturbances and parameter perturbations.

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Energy-Efficient Train Operation Using Nature-Inspired Algorithms

Cited by 30 publications

References 51 publications

A New Approach for Real Time Train Energy Efficiency Optimization

A New Approach for Real Time Train Energy Efficiency Optimization

A Passenger-Oriented Optimization Model for Implementing Energy-Saving Strategies in Railway Contexts

Virtual Line Shafting-Based Total-Amount Coordinated Control of Multi-Motor Traction Power

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