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Energy-Efficient Driving Strategy for High-Speed Trains with Considering the Checkpoints

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Chinese Journal of Electronics 2024年第3期33卷 847-858页

作者： Zixuan ZHANG Yuan CAO Shuai SU State Key Laboratory of rail Traffic control and Safety Beijing Jiaotong University School of Electronic and Information engineering Beijing Jiaotong University national engineering research center of rail transportation operation and control system Beijing Jiaotong University Frontiers Science center for Smart High-speed railway system Beijing Jiaotong University

With rising energy prices and concerns about environmental issues,energy-efficient driving strategies(EEDS) for high-speed trains have received a substantial amount of attention.In particular,energy-saving schemes play a huge role in reducing the energy and operating costs of trains.This article studies the EEDS of high-speed trains at a given time.A well-posed model is formulated,in which the constraints of the checkpoints,in addition to the speed limits,vehicle dynamics,and discrete control throttle,are first considered.For a given control sequence,the Karush-Kuhn-Tucker(KKT) conditions are used to obtain the necessary conditions for an EEDS.According to several key equations of the necessary conditions,the checkpoint constraints are satisfied.Some case studies are conducted based on the data of the Beijing-Shanghai high-speed line to illustrate the effectiveness of the proposed approach.

关键词： Energy consumption Costs Simulation Mathematical models Energy efficiency Vehicle dynamics Optimization

Vibration-Based Fault Diagnosis for railway Point Machines Using VMD and Multiscale Fluctuation-Based Dispersion Entropy

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Chinese Journal of Electronics 2024年第3期33卷 803-813页

作者： Yongkui SUN Yuan CAO Peng LI Guo XIE Tao WEN Shuai SU national engineering research center of rail transportation operation and control system Beijing Jiaotong University School of Electronic and Information engineering Beijing Jiaotong University Shaanxi Key Laboratory of Complex system control and Intelligent Information Processing Xi'an University of Technology Frontiers Science center for Smart High-speed railway system Beijing Jiaotong University

As one of the most important railway signaling equipment,railway point machines undertake the major task of ensuring train operation safety.Thus fault diagnosis for railway point machines becomes a hot topic.Considering the advantage of the anti-interference characteristics of vibration signals,this paper proposes an novel intelligent fault diagnosis method for railway point machines based on vibration signals.A feature extraction method combining variational mode decomposition(VMD) and multiscale fluctuation-based dispersion entropy is developed,which is verified a more effective tool for feature selection.Then,a two-stage feature selection method based on Fisher discrimination and ReliefF is proposed,which is validated more powerful than single feature selection methods.Finally,support vector machine is utilized for fault diagnosis.Experiment comparisons show that the proposed method performs best.The diagnosis accuracies of normal-reverse and reverse-normal switching processes reach 100% and 96.57% respectively.Especially,it is a try to use new means for fault diagnosis on railway point machines,which can also provide references for similar fields.

关键词： Fault diagnosis Vibrations Support vector machines Diversity reception Switches Feature extraction rail transportation

Fault Diagnosis for railway Point Machines Using VMD Multi-scale Permutation Entropy and ReliefF Based on Vibration Signals

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Chinese Journal of Electronics 2024年

作者： Yongkui SUN Yuan CAO Peng LI Shuai SU national engineering research center of rail transportation operation and control system Beijing Jiaotong University School of Automation and Intelligence Beijing Jiaotong University Frontiers Science center for Smart High-speed railway system Beijing Jiaotong University

The railway point machine plays an important part in railway systems. It is closely related to the safe operation of trains. Considering the advantages of vibration signals on anti-interference, this paper develops a novel vibration signal-based diagnosis approach for railway point machines. First, variational mode decomposition(VMD)is adopted for data preprocessing, which is verified more effective than empirical mode decomposition. Next, multiscale permutation entropy is extracted to characterize the fault features from multiple scales. Then ReliefF is utilized for feature selection, which can greatly decrease the feature dimension and improve the diagnosis accuracy. By experiment comparisons, the proposed approach performs best on diagnosis for railway point machines. The diagnosis accuracies on reverse-normal and normal-reverse processes are respectively 100% and 98.29%.

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Low-Carbon Dispatching for Virtual Power Plant with Aggregated Distributed Energy Storage Considering Spatiotemporal Distribution of Cleanness Value

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Journal of Modern Power systems and Clean Energy 2024年第2期12卷 346-358页

作者： Hongchao Gao Tai Jin Guanxiong Wang Qixin Chen Chongqing Kang Jingkai Zhu State Key Laboratory of Power system operation and control Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Sichuan Energy Internet research Institute Tsinghua University Chengdu 200016China Power Dispatching and control center of Shanghai Municipal Electric Power Company Shanghai 200122China IEEE

The scale of distributed energy resources is increasing,but imperfect business models and value transmission mechanisms lead to low utilization ratio and poor responsiveness.To address this issue,the concept of cleanness value of distributed energy storage(DES)is proposed,and the spatiotemporal distribution mechanism is discussed from the perspectives of electrical energy and cleanness.Based on this,an evaluation system for the environmental benefits of DES is constructed to balance the interests between the aggregator and the power system operator.Then,an optimal low-carbon dispatching for a virtual power plant(VPP)with aggregated DES is constructed,where-in energy value and cleanness value are both considered.To achieve the goal,a green attribute labeling method is used to establish a correlation constraint between the nodal carbon potential of the distribution network(DN)and DES behavior,but as a cost,it brings multiple nonlinear relationships.Subsequently,a solution method based on the convex envelope(CE)linear re-construction method is proposed for the multivariate nonlinear programming problem,thereby improving solution efficiency and feasibility.Finally,the simulation verification based on the IEEE 33-bus DN is conducted.The simulation results show that the multidimensional value recognition of DES motivates the willingness of resource users to respond.Meanwhile,resolving the impact of DES on the nodal carbon potential can effectively alleviate overcompensation of the cleanness value.

关键词： Distributed energy storage virtual power plant(VPP) spatiotemporal distribution low-carbon dispatching

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A method for establishing a bearing residual life prediction model for process enhancement equipment based on rotor imbalance response analysis

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Chinese Journal of Chemical engineering 2024年第2期66卷 203-215页

作者： Feng Wang Haoran Li Zhenghui Zhang Yan Bai Hong Yin Jing Bian national Foundation research Laboratory of Fault Prevention and control in Hazardous Chemicals Production system Engineering Research Center of Chemical Technology SafetyBeijing University of Chemical TechnologyBeijing 100029China China Nuclear Power engineering Co. LtdBeijing 100840China CNOOC Tianjin Chemical research and Design Institute Co. LtdTianjin Key Laboratory of Energy and Chemical Explosion SafetyAcademician Expert Collaborative Innovation CenterTianjin 300131China

A rotating packed bed is a typical chemical process enhancement equipment that can strengthen micromixing and mass transfer.During the operation of the rotating packed bed,the nonreactants and products irregularly adhere to the wire mesh packing in the rotor,thus resulting in an imbalance in the vibration of the rotor,which may cause serious damage to the bearing and material leakage.This study proposes a model prediction for estimating the bearing residual life of a rotating packed bed based on rotor imbalance response analysis.This method is used to determine the influence of the mass on the imbalance in the vibration of the rotor on bearing damage.The major influence on rotor vibration was found to be exerted by the imbalanced mass and its distribution radius,as revealed by the results of orthogonal experiments.Through implementing finite element analysis,the imbalance response curve for the rotating packed bed rotor was obtained,and a correlation among rotor imbalance mass,distribution radius of imbalance mass,and bearing residue life was established via data fitting.The predicted value of the bearing life can be used as the reference basis for an early safety warning of a rotating packed bed to effectively avoid accidents.

关键词： Rotating packed bed Mass imbalance Harmonic response analysis Residual life Prediction model

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A VNS-NPGA Approach to Multi-Objective Optimization of Hub-and-spoke Logistics Network

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Journal of Traffic and transportation engineering(English Edition) 2024年

作者： Changxi Ma Chuwei Shi Yun Yang Yongpeng Zhao Zhuye Xu Bo Du School of Traffic and transportation Lanzhou Jiaotong University Key Laboratory of railway lndustry on Plateau railway transportation Intelligent Management and control Lanzhou Jiaotong University School of Tourism and Management Yangling Vocational and Technical College School of New Energy and Power engineering Lanzhou Jiaotong University national engineering research center of Highway Maintenance Technology Changsha University of Science & Technology SMART Infrastructure Facility University of Wollongong

To realize low-cost freight transport in the logistics network and improve the network operation efficiency， a multi-objective optimization model and the corresponding algorithm for a hub-and-spoke logistics network are proposed based on the multi-level location of hub points and channels layout. By considering the structure of the multi-level hub-and-spoke logistics network and the features of the connectivity between the hub and spoke points， the multi-objective optimization model is constructed with two objectives of minimizing the total network operation costs and the total network service time. By considering the characteristics of decision variables and models， a Variable Neighborhood Search (VNS)-Niched Pareto Genetic Algorithm (NPGA) approach with a three-stage encoding structure chromosome is proposed， where the VNS algorithm nested in NPGA is used for individual variable neighborhood search to optimize individual channel level genes， and NPGA is adopted to solve the multi-objective optimization model. To evaluate the performance of the proposed VNS-NPGA approach， a real-life case study based on a small-scale Australia Post data set was conducted， and 25 nodes of the Australia Post and 14 nodes of the Gansu Province 3-level hub-and-spoke logistics networks were established， respectively. The analysis results indicated that the network structure of multi-level hub points could avoid the detour problem existing in the traditional hub-and-spoke network， and showed better applicability in the narrow geographical structure. Compared to the traditional multi-objective evolutionary algorithms， VNS-NPGA can obtain better solutions through the distributed optimization of channel levels， avoiding the problem that a single algorithm cannot effectively deal with coupling relationships in genes.

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A Temporary Frequency Response Strategy Using a Voltage Source-Based PermanentMagnet Synchronous Generator and Energy Storage systems

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Energy engineering 2024年第2期121卷 541-555页

作者： Baogang Chen Fenglin Miao Jing Yang Chen Qi Wenyan Ji CSIC HaiZhuangWindpower Co. Ltd.Chongqing400000China State Key Laboratory of operation and control of Renewable Energy&Storage systems China Electric Power Research InstituteBeijing100000China

Energy storage systems(ESS)and permanent magnet synchronous generators(PMSG)are speculated to be able to exhibit frequency regulation capabilities by adding differential and proportional control loops with different control objectives.The available PMSG kinetic energy and charging/discharging capacities of the ESS were restricted.To improve the inertia response and frequency control capability,we propose a short-term frequency support strategy for the ESS and PMSG.To this end,the weights were embedded in the control loops to adjust the participation of the differential and proportional controls based on the system frequency excursion.The effectiveness of the proposed control strategy was verified using PSCAD/EMTDC.The simulations revealed that the proposed strategy could improve the maximum rate of change of the frequency nadir and maximum frequency excursion.Therefore,it provides a promising solution of ancillary services for frequency regulation of PMSG and ESS.

关键词： Inertial control PMSG ESS wind power generation frequency support

research on Virtual Coupled Train control Method Based on GPC & VAPF

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Chinese Journal of Electronics 2022年第5期31卷 897-905页

作者： CAO Yuan YANG Yaran MA Lianchuan WEN Jiakun State Key Laboratory of rail Traffic control and Safety Beijing Jiaotong University national engineering research center of rail transportation operation and control system Beijing Jiaotong University School of Electronic and Information engineering Beijing Jiaotong University

Improving transportation efficiency is an eternal research hotspot in rail transit system. In recent years, the train operation control method based on virtual coupling has attracted the attention of many scholars.The method of train coordination and anti-collision control is not only the key to realize the virtual coupling of train, but also the key to ensure the safety of train operation. Therefore, based on the existing research, a virtual coupled train dynamics model with nonlinear dynamics is established. Then, the parameters of the operation process model of the nonlinear virtual coupled train are identified by the recursive least squares method based on realtime data, which is applied to the variable parameter artificial potential field(VAPF) for parameter identification.A fusion controller based on feature-based generalized model prediction(GPC) and VAPF is used to control the virtual coupled train and prevent collision. Finally, the validity of the proposed method is verified by using real high-speed railway data.

关键词： Virtual coupling train control system Generalized model predictive control Nonlinear system Artificial potential field (APF)

Vibration Signal-Based Fault Diagnosis of railway Point Machines via Double-Scale CNN

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Chinese Journal of Electronics 2023年第5期32卷 972-981页

作者： CHEN Xiaohan HU Xiaoxi WEN Tao CAO Yuan The School of Electronic and Information engineering Beijing Jiaotong University The State Key Laboratory of rail Traffic control and Safety Beijing Jiaotong University the national engineering research center of rail transportation operation control system Beijing Jiaotong University

In the railway transportation industry,fault diagnosis of railway point machines(RPMs) is vital.Because operational vibration signals can reflect the condition of various faults in mechanical devices, vibration sensing and monitoring and more importantly, vibration signal-based fault diagnosis for RPMs have attracted the attention of scholars and engineers. Most vibration signalbased fault-diagnosis methods for RPMs rely on data collected using high-sampling-rate sensors and manual feature extraction, hence are costly and insufficiently robust.To overcome these shortcomings, we propose a doublescale wide first-layer kernel convolutional neural network(DS-WCNN) for RPMs fault diagnosis using inexpensive and low-sampling-rate vibration sensors. The proposed wide first-layer kernels, which extract features from vibration observations, are particularly suitable for lowsampling-rate signals. Meanwhile, the proposed doublescale structure improves accuracy and noise suppression by combining two types of timescale features. Sufficient experiments, including noise addition and comparison,were conducted to demonstrate the robustness and accuracy of the proposed algorithm.

关键词： railway point machines Fault diagnosis Condition monitoring Vibration signals Convolutional neural networks