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  • Open Access

    ARTICLE

    Enhanced Deep Reinforcement Learning Strategy for Energy Management in Plug-in Hybrid Electric Vehicles with Entropy Regularization and Prioritized Experience Replay

    Li Wang1,*, Xiaoyong Wang2

    Energy Engineering, Vol.121, No.12, pp. 3953-3979, 2024, DOI:10.32604/ee.2024.056705 - 22 November 2024

    Abstract Plug-in Hybrid Electric Vehicles (PHEVs) represent an innovative breed of transportation, harnessing diverse power sources for enhanced performance. Energy management strategies (EMSs) that coordinate and control different energy sources is a critical component of PHEV control technology, directly impacting overall vehicle performance. This study proposes an improved deep reinforcement learning (DRL)-based EMS that optimizes real-time energy allocation and coordinates the operation of multiple power sources. Conventional DRL algorithms struggle to effectively explore all possible state-action combinations within high-dimensional state and action spaces. They often fail to strike an optimal balance between exploration and exploitation, and… More >

  • Open Access

    ARTICLE

    Research on Robustness of Charging Station Networks under Multiple Recommended Charging Methods for Electric Vehicles

    Lei Feng1, Miao Liu1, Yexun Yuan1, Chi Zhang2, Peng Geng1,*

    Journal on Internet of Things, Vol.6, pp. 1-16, 2024, DOI:10.32604/jiot.2024.053584 - 24 July 2024

    Abstract With the rapid development of electric vehicles, the requirements for charging stations are getting higher and higher. In this study, we constructed a charging station topology network in Nanjing through the Space-L method, mapping charging stations as network nodes and constructing edges through road relationships. The experiment introduced five EV charging recommendation strategies (based on distance, number of fast charging piles, user preference, price, and overall rating) used to simulate disordered charging caused by different user preferences, and the impact of the network dynamic robustness in case of node failure is explored by simulating the… More >

  • Open Access

    ARTICLE

    Drive Train Cooling Options for Electric Vehicles

    Randeep Singh1,*, Tomoki Oridate2, Tien Nguyen2

    Frontiers in Heat and Mass Transfer, Vol.22, No.3, pp. 703-717, 2024, DOI:10.32604/fhmt.2024.050744 - 11 July 2024

    Abstract Electrification of vehicles intensifies their cooling demands due to the requirements of maintaining electronics/electrical systems below their maximum temperature threshold. In this paper, passive cooling approaches based on heat pipes have been considered for the thermal management of electric vehicle (EV) traction systems including battery, inverter, and motor. For the battery, a heat pipe base plate is used to provide high heat removal (180 W per module) and better thermal uniformity (<5°C) for the battery modules in a pack while downsizing the liquid cold plate system. In the case of Inverter, two phase cooling system… More > Graphic Abstract

    Drive Train Cooling Options for Electric Vehicles

  • 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 - 25 January 2024

    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… 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 - 28 December 2023

    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 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 - 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

    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

    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 >

  • Open Access

    ARTICLE

    Fuzzy Based Interleaved Step-up Converter for Electric Vehicle

    T. Saravanakumar, R. Saravana kumar*

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1103-1118, 2023, DOI:10.32604/iasc.2023.025511 - 06 June 2022

    Abstract This work focuses on the fuzzy controller for the proposed three-phase interleaved Step-up converter (ISC). The fuzzy controller for the proposed ISC converters for electric vehicles has been discussed in detail. The proposed ISC direct current (DC-DC) converter could also be used in automobiles, satellites, industries, and propulsion. To enhance voltage gain, the proposed ISC Converter combines boost converter and interleaved converter (IC). This design also reduces the number of switches. As a result, ISC converter switching losses are reduced. The proposed ISC Converter topology can produce a 143 V output voltage and 1 kW… 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 More >

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