An Energy Storage System for Recycling Regenerative Braking Energy in High-Speed Railway

Chen, Junyu; Hu, Haitao; Ge, Yinbo; Wang, Ke; Huang, Wenlong; He, Zhengyou

doi:10.1109/tpwrd.2020.2980018

Cited by 67 publications

(19 citation statements)

References 30 publications

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“…Moreover, large-capacity energy storage systems occupy space and increase train weight. Recently, because balancing the power of the two power arms in the same TS can be realized by a railway power conditioner (RPC) [27], an energy storage system integrated with a RPC was proposed to reduce the capacity of the energy storage device and fully utilize regenerative braking energy (such as a RPC with energy storage systems [28][29][30] or a RPC with super-capacitor [31]). In addition, in [32], a photovoltaic energy storage system for railway traction is proposed.…”

Section: Introductionmentioning

confidence: 99%

An effective utilization scheme for regenerative braking energy based on power regulation with a genetic algorithm

Cheng

Wang

et al. 2022

IET Power Electronics

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To ensure that regenerative braking energy is fully utilized by traction trains in the whole railway power supply systems, an effective utilization scheme of the regenerative braking energy based on power regulation with a genetic algorithm (GA) is proposed in this paper. This scheme consists of railway power conditioners (RPCs), energy transfer converters (ETCs) and a central controller. A RPC connects the two power arms of each TS, and an ETC connects the two power arms of each section post (SP). The RPCs and ETCs are controlled to transfer the regenerative braking power distributed by the central controller, which is calculated by the GA. The detailed calculation steps are described. Moreover, the principle and control strategies of the negative sequence current compensation by the RPCs are given based on the optimization results of the GA. Finally, optimization calculations and hardware in loop (HIL) experiments were performed. The results show that the utilization rate of regenerative braking energy is about 93.3% and the three-phase current imbalance is reduced by about 98.6% in the case system with the proposed scheme. This result verifies the effectiveness and feasibility of the proposed scheme.

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Section: Introductionmentioning

confidence: 99%

An effective utilization scheme for regenerative braking energy based on power regulation with a genetic algorithm

Cheng

Wang

et al. 2022

IET Power Electronics

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“…Arikan and Yamur et al adopted a combined strategy that includes reducing electrification loss, using regenerative braking, and improving comfort and driving technology to solve the problem of the high energy consumption of the train [ 6 ]. An optimization method for improving the energy efficiency of regenerative braking based on the master-slave mode is proposed [ 7 ]. On the basis of describing the switching model of urban rail train dynamics, an online optimization method of a train for energy-saving based on model predictive control is proposed [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

Energy-Saving Optimization Method of Urban Rail Transit Based on Improved Differential Evolution Algorithm

Zhang

2022

Sensors

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The transformation of railway infrastructure and traction equipment is an ideal way to realize energy savings of urban rail transit trains. However, upgrading railway infrastructure and traction equipment is a high investment and difficult process. To produce energy-savings in the urban rail transit system without changing the existing infrastructure, we propose an energy-saving optimization method by optimizing the traction curve of the train. Firstly, after analyzing the relationship between the idle distance and running energy-savings, an optimization method of traction energy-savings based on the combination of the inertia motion and energy optimization is established by taking the maximum idle distance as the objective; and the maximum allowable running speed, passenger comfort, train timetable, maximum allowable acceleration and kinematics equation as constraints. Secondly, a solution method based on the combination of the adaptive dynamic multimodal differential evolution algorithm and the Q learning algorithm is applied to solve the optimization model of energy-savings. Finally, numeric experiments are conducted to verify the proposed method. Extensive experiments demonstrate the effectiveness of the proposed method. The results show that the method has significant energy-saving properties, saving energy by about 11.2%.

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“…Also, braking energy's recovery efficiency is closely related to the vehicle RBS control strategy. 9,10 There is a major difference between RBS and the traditional friction braking system. The traditional friction braking system comprises four main parts: energy supply device, control device, transmission device, and braking device.…”

Section: Introductionmentioning

confidence: 99%

An adaptive fuzzy sliding‐mode control for regenerative braking system of electric vehicles

Mei

Karimi

Yang

et al. 2021

Adaptive Control & Signal

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This article proposes a novel fuzzy sliding-mode control scheme under an adaptive control strategy for energy management mechanism in electric vehicles that are subject to a regenerative braking system. The effectiveness of the fuzzy logic controller is to adjust the sliding mode parameters according to the slip ratio tracking error between the optimal slip ratio and the actual slip ratio. Specifically, the proposed torque distribution strategy can integrate the best battery condition and energy recovery efficiency under the practical constraints through this control method by fixing the pneumatic braking torque and motor torque.

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An Energy Storage System for Recycling Regenerative Braking Energy in High-Speed Railway

Cited by 67 publications

References 30 publications

An effective utilization scheme for regenerative braking energy based on power regulation with a genetic algorithm

An effective utilization scheme for regenerative braking energy based on power regulation with a genetic algorithm

Energy-Saving Optimization Method of Urban Rail Transit Based on Improved Differential Evolution Algorithm

An adaptive fuzzy sliding‐mode control for regenerative braking system of electric vehicles

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