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  • Open Access

    ARTICLE

    Coordinated Voltage Control of Distribution Network Considering Multiple Types of Electric Vehicles

    Liang Liu, Guangda Xu*, Yuan Zhao, Yi Lu, Yu Li, Jing Gao

    Energy Engineering, Vol.121, No.2, pp. 377-404, 2024, DOI:10.32604/ee.2023.041311

    Abstract The couple between the power network and the transportation network (TN) is deepening gradually with the increasing penetration rate of electric vehicles (EV), which also poses a great challenge to the traditional voltage control scheme. In this paper, we propose a coordinated voltage control strategy for the active distribution networks considering multiple types of EV. In the first stage, the action of on-load tap changer and capacitor banks, etc., are determined by optimal power flow calculation, and the node electricity price is also determined based on dynamic time-of-use tariff mechanism. In the second stage, multiple operating scenarios of multiple types… More >

  • Open Access

    ARTICLE

    Study on Two-Tier EV Charging Station Recommendation Strategy under Multi-Factor Influence

    Miao Liu, Lei Feng, Yexun Yuan, Ye Liu, Peng Geng*

    Journal on Artificial Intelligence, Vol.5, pp. 181-193, 2023, DOI:10.32604/jai.2023.046066

    Abstract This article aims to address the clustering effect caused by unorganized charging of electric vehicles by adopting a two-tier recommendation method. The electric vehicles (EVs) are classified into high-level alerts and general alerts based on their state of charge (SOC). EVs with high-level alerts have the most urgent charging needs, so the distance to charging stations is set as the highest priority for recommendations. For users with general alerts, a comprehensive EV charging station recommendation model is proposed, taking into account factors such as charging price, charging time, charging station preference, and distance to the charging station. Using real data… More >

  • Open Access

    ARTICLE

    Sparsity-Enhanced Model-Based Method for Intelligent Fault Detection of Mechanical Transmission Chain in Electrical Vehicle

    Wangpeng He1,*, Yue Zhou1, Xiaoya Guo2, Deshun Hu1, Junjie Ye3

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2495-2511, 2023, DOI:10.32604/cmes.2023.027896

    Abstract In today’s world, smart electric vehicles are deeply integrated with smart energy, smart transportation and smart cities. In electric vehicles (EVs), owing to the harsh working conditions, mechanical parts are prone to fatigue damages, which endanger the driving safety of EVs. The practice has proved that the identification of periodic impact characteristics (PICs) can effectively indicate mechanical faults. This paper proposes a novel model-based approach for intelligent fault diagnosis of mechanical transmission train in EVs. The essential idea of this approach lies in the fusion of statistical information and model information from a dynamic process. In the algorithm, a novel… More >

  • Open Access

    ARTICLE

    BATTERY COOLING OPTIONS IN ELECTRIC VEHICLES WITH HEAT PIPES

    Randeep Singha,*,†, Gero Lappa, Jason Velardob, Phan Thanh Longa, Masataka Mochizukic, Aliakbar Akbarzadehd, Abhijit Dated, Karsten Mausolfe, Kristin Bussee

    Frontiers in Heat and Mass Transfer, Vol.16, pp. 1-8, 2021, DOI:10.5098/hmt.16.2

    Abstract In this paper, different options, based on heat pipes, for thermal management of electric vehicle (EV) battery system, at cell, module and pack level, for 40 to 400 W output heat, has been explored, analysed and compared. Cooling architecture based on embedded heat pipe (EHP) with single phase pumped cold plate (CP), as most adaptable design for low to medium range EVs, while EHP with loop heat pipe (LHP) as high performance design for high-end carlines, has been classified as potential cooling systems. Experimentally, it was shown that EHPs will provide best performance for heat acquisition at cell/module level, while… More >

  • Open Access

    ARTICLE

    VISUALIZATION OF INDUCED COUNTER-ROTATING VORTICES FOR ELECTRIC VEHICLES BATTERY MODULE THERMAL MANAGEMENT

    A.C. Budimana,*, S. M. Hasheminejadb, Sudirjaa, A. Mitayanic, S. H. Winotod

    Frontiers in Heat and Mass Transfer, Vol.19, pp. 1-6, 2022, DOI:10.5098/hmt.19.9

    Abstract Streamwise development of counter-rotating vortices induced by three different types of chevron Vortex Generators (VGs) placed upstream an Electric Vehicles (EV) dummy battery module is experimentally visualized using a smoke-wire method. From the single chevron reference case, the mushroom-like vortices do not collapse until passing the module. When more chevrons are used in line, the vortices become more prominent. It can also be observed that the vortex sizes and shapes are significantly influenced by the spanwise base length of the chevron. The induced vortices from all three VGs suggest a potential heat transfer augmentation for the EV battery module application. More >

  • Open Access

    ARTICLE

    Stability Analysis and Control of DC Distribution System with Electric Vehicles

    Zhijie Zheng1, Song Zhang1, Xiaolei Zhang2, Bo Yang1, Fang Yan3, Xiaoning Ge3,*

    Energy Engineering, Vol.120, No.3, pp. 633-647, 2023, DOI:10.32604/ee.2022.024081

    Abstract The DC distribution network system equipped with a large number of power electronic equipment exhibits weak damping characteristics and is prone to low-frequency and high-frequency unstable oscillations. The current interpretation of the oscillation mechanism has not been unified. Firstly, this paper established the complete state-space model of the distribution system consisting of a large number of electric vehicles, characteristic equation of the distribution network system is derived by establishing a state-space model, and simplified reduced-order equations describing the low-frequency oscillation and the high-frequency oscillation are obtained. Secondly, based on eigenvalue analysis, the oscillation modes and the influence of the key… More >

  • Open Access

    ARTICLE

    Optimal Operation of Electric Vehicles and Distributed Generation Resources in Smart Grid Considering Load Management

    Zheng Wang*, Shangke Liu, Yanli Xiao, Ye Wan, Bin Bai

    Energy Engineering, Vol.119, No.6, pp. 2655-2679, 2022, DOI:10.32604/ee.2022.021843

    Abstract Technology advancement and the global tendency to use renewable energy in distributed generation units in the distribution network have been proposed as sources of energy supply. Despite the complexity of their protection, as well as the operation of distributed generation resources in the distribution network, factors such as improving reliability, increasing production capacity of the distribution network, stabilizing the voltage of the distribution network, reducing peak clipping losses, as well as economic and environmental considerations, have expanded the influence of distributed generation (DG) resources in the distribution network. The location of DG sources and their capacity are the key factors… More >

  • Open Access

    ARTICLE

    Optimal Energy Consumption Optimization in a Smart House by Considering Electric Vehicles and Demand Response via a Hybrid Gravitational Search and Particle Swarm Optimization Algorithm

    Rongxin Zhang1,*, Chengying Yang2,3, Xuetao Li1

    Energy Engineering, Vol.119, No.6, pp. 2489-2511, 2022, DOI:10.32604/ee.2022.021517

    Abstract Buildings are the main energy consumers across the world, especially in urban communities. Building smartization, or the smartification of housing, therefore, is a major step towards energy grid smartization too. By controlling the energy consumption of lighting, heating, and cooling systems, energy consumption can be optimized. All or some part of the energy consumed in future smart buildings must be supplied by renewable energy sources (RES), which mitigates environmental impacts and reduces peak demand for electrical energy. In this paper, a new optimization algorithm is applied to solve the optimal energy consumption problem by considering the electric vehicles and demand… More >

  • Open Access

    ARTICLE

    Optimization of Charging/Battery-Swap Station Location of Electric Vehicles with an Improved Genetic Algorithm-Based Model

    Bida Zhang1,*, Qiang Yan1, Hairui Zhang2, Lin Zhang3

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 1177-1194, 2023, DOI:10.32604/cmes.2022.022089

    Abstract The joint location planning of charging/battery-swap facilities for electric vehicles is a complex problem. Considering the differences between these two modes of power replenishment, we constructed a joint location-planning model to minimize construction and operation costs, user costs, and user satisfaction-related penalty costs. We designed an improved genetic algorithm that changes the crossover rate using the fitness value, memorizes, and transfers excellent genes. In addition, the present model addresses the problem of “premature convergence” in conventional genetic algorithms. A simulated example revealed that our proposed model could provide a basis for optimized location planning of charging/battery-swapping facilities at different levels… More >

  • Open Access

    ARTICLE

    State-of-Charge Estimation of Lithium-Ion Battery for Electric Vehicles Using Deep Neural Network

    M. Premkumar1, R. Sowmya2, S. Sridhar3, C. Kumar4, Mohamed Abbas5,6, Malak S. Alqahtani7, Kottakkaran Sooppy Nisar8,*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6289-6306, 2022, DOI:10.32604/cmc.2022.030490

    Abstract It is critical to have precise data about Lithium-ion batteries, such as the State-of-Charge (SoC), to maintain a safe and consistent functioning of battery packs in energy storage systems of electric vehicles. Numerous strategies for estimating battery SoC, such as by including the coulomb counting and Kalman filter, have been established. As a result of the differences in parameter values between each cell, when these methods are applied to high-capacity battery packs, it has difficulties sustaining the prediction accuracy of overall cells. As a result of aging, the variation in the parameters of each cell is higher as more time… More >

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