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  • 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 - 03 August 2023

    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.… More >

  • Open Access

    ARTICLE

    Deep Learning Based Automatic Charging Identification and Positioning Method for Electric Vehicle

    Hao Zhu1, Chao Sun2,*, Qunfeng Zheng2, Qinghai Zhao1,3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 3265-3283, 2023, DOI:10.32604/cmes.2023.025777 - 09 March 2023

    Abstract Electric vehicle charging identification and positioning is critically important to achieving automatic charging. In terms of the problem of automatic charging for electric vehicles, a dual recognition and positioning method based on deep learning is proposed. The method is divided into two parts: global recognition and localization and local recognition and localization. In the specific implementation process, the collected pictures of electric vehicle charging attitude are classified and labeled. It is trained with the improved YOLOv4 network model and the corresponding detection model is obtained. The contour of the electric vehicle is extracted by the… More > Graphic Abstract

    Deep Learning Based Automatic Charging Identification and Positioning Method for Electric Vehicle

  • Open Access

    ARTICLE

    A Novel Ultra Short-Term Load Forecasting Method for Regional Electric Vehicle Charging Load Using Charging Pile Usage Degree

    Jinrui Tang*, Ganheng Ge, Jianchao Liu, Honghui Yang

    Energy Engineering, Vol.120, No.5, pp. 1107-1132, 2023, DOI:10.32604/ee.2023.025666 - 20 February 2023

    Abstract Electric vehicle (EV) charging load is greatly affected by many traffic factors, such as road congestion. Accurate ultra short-term load forecasting (STLF) results for regional EV charging load are important to the scheduling plan of regional charging load, which can be derived to realize the optimal vehicle to grid benefit. In this paper, a regional-level EV ultra STLF method is proposed and discussed. The usage degree of all charging piles is firstly defined by us based on the usage frequency of charging piles, and then constructed by our collected EV charging transaction data in the… More >

  • Open Access

    ARTICLE

    Electric Vehicle Charging Capacity of Distribution Network Considering Conventional Load Composition

    Pengwei Yang1, Yuqi Cao2, Jie Tan2, Junfa Chen1, Chao Zhang1, Yan Wang1, Haifeng Liang2,*

    Energy Engineering, Vol.120, No.3, pp. 743-762, 2023, DOI:10.32604/ee.2023.024128 - 03 January 2023

    Abstract At present, the large-scale access to electric vehicles (EVs) is exerting considerable pressure on the distribution network. Hence, it is particularly important to analyze the capacity of the distribution network to accommodate EVs. To this end, we propose a method for analyzing the EV capacity of the distribution network by considering the composition of the conventional load. First, the analysis and pretreatment methods for the distribution network architecture and conventional load are proposed. Second, the charging behavior of an EV is simulated by combining the Monte Carlo method and the trip chain theory. After obtaining… 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 - 03 January 2023

    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 More >

  • Open Access

    ARTICLE

    Generating Time-Series Data Using Generative Adversarial Networks for Mobility Demand Prediction

    Subhajit Chatterjee1, Yung-Cheol Byun2,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5507-5525, 2023, DOI:10.32604/cmc.2023.032843 - 28 December 2022

    Abstract The increasing penetration rate of electric kickboard vehicles has been popularized and promoted primarily because of its clean and efficient features. Electric kickboards are gradually growing in popularity in tourist and education-centric localities. In the upcoming arrival of electric kickboard vehicles, deploying a customer rental service is essential. Due to its free-floating nature, the shared electric kickboard is a common and practical means of transportation. Relocation plans for shared electric kickboards are required to increase the quality of service, and forecasting demand for their use in a specific region is crucial. Predicting demand accurately with… More >

  • Open Access

    ARTICLE

    Hybrid Optimized PI Controller Design for Grid Tied PV Based Electric Vehicle

    J. Aran Glenn1,*, Srinivasan Alavandar2

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1523-1545, 2023, DOI:10.32604/iasc.2023.033545 - 05 January 2023

    Abstract Nowadays, researchers are becoming increasingly concerned about developing a highly efficient emission free transportation and energy generation system for addressing the pressing issue of environmental crisis in the form of pollution and climate change. The introduction of Electric Vehicles (EVs) solves the challenge of emission-free transportation while the necessity for decarbonized energy production is fulfilled by the installation and expansion of solar-powered Photovoltaic (PV) systems. Hence, this paper focuses on designing an effective PV based EV charging system that aids in stepping towards the achievement of a pollution free future. For overcoming the inherent intermittency… More >

  • Open Access

    ARTICLE

    Location and Capacity Determination Method of Electric Vehicle Charging Station Based on Simulated Annealing Immune Particle Swarm Optimization

    Jiulong Sun1, Yanbo Che1,*, Ting Yang1, Jian Zhang2, Yibin Cai1

    Energy Engineering, Vol.120, No.2, pp. 367-384, 2023, DOI:10.32604/ee.2023.023661 - 29 November 2022

    Abstract As the number of electric vehicles (EVs) continues to grow and the demand for charging infrastructure is also increasing, how to improve the charging infrastructure has become a bottleneck restricting the development of EVs. In other words, reasonably planning the location and capacity of charging stations is important for development of the EV industry and the safe and stable operation of the power system. Considering the construction and maintenance of the charging station, the distribution network loss of the charging station, and the economic loss on the user side of the EV, this paper takes… More > Graphic Abstract

    Location and Capacity Determination Method of Electric Vehicle Charging Station Based on Simulated Annealing Immune Particle Swarm Optimization

  • Open Access

    ARTICLE

    A Novel Method for Heat Exchange Evaluation in EV

    Mohammad Saraireh*

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 57-70, 2023, DOI:10.32604/iasc.2023.032050 - 29 September 2022

    Abstract With the growing global energy and environmental problems, electric vehicles that are both environmentally friendly and cost effective have seen rapid growth. An electrified vehicle’s effective thermal management must include all of the vehicle’s systems. However, optimizing the thermal behavior of each component is insufficient. A lithium-ion battery’s operating temperature has a significant impact on its performance. When working at low temperatures, the internal resistance of lithium-ion batteries increases, the available energy and power of the system decreases, and lithium precipitation caused by low-temperature charging may cause safety issues; high-temperature operation and temperature inconsistency between… 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 - 31 August 2022

    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 More >

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