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Electric Vehicle Charging

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Energy Science and Technology".

Deadline for manuscript submissions: closed (31 October 2018) | Viewed by 47821

Special Issue Editor

Special Issue Information

Dear Colleagues,

The number of electric vehicles (EVs) is expected to increase significantly in the near future, due to their advantageous characteristics. To support this kind of mass deployment of EVs, the development of charging technologies for EVs is crucial, as well as their demonstration and deployment. In addition, support from governments, in terms of policy, as well as understanding and willingness from the community, are also strongly needed.

This Special Issue focuses on several aspects related to the charging of EVs, including technology, regulation, standards, demonstration, and social influences. The following topics are welcomed, but are not limited to:

  • Charging technologies, including regular and fast charging, wired and non-wired charging,
  • Battery management
  • Charging control and management
  • System demonstration
  • Charging standards, including charger, connector, information transmission
  • Social influences
  • Policy
  • Correlation to vehicle-to-grid services
  • Integration of REs for EVs charging

Accordingly, this Special Issue is open for the following types of manuscripts, covering the whole breadth of electric vehicle charging and discharging issues and concerns:

  • Original research articles;
  • review articles;
  • technical report;
Dr. Muhammad Aziz
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • electric vehicle
  • battery management
  • charging technology
  • charger
  • standard and regulation

Published Papers (10 papers)

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Research

21 pages, 5639 KiB  
Article
An Evaluation of Turbocharging and Supercharging Options for High-Efficiency Fuel Cell Electric Vehicles
by Arthur Kerviel, Apostolos Pesyridis, Ahmed Mohammed and David Chalet
Appl. Sci. 2018, 8(12), 2474; https://doi.org/10.3390/app8122474 - 3 Dec 2018
Cited by 37 | Viewed by 7611
Abstract
Mass-produced, off-the-shelf automotive air compressors cannot be directly used for boosting a fuel cell vehicle (FCV) application in the same way that they are used in internal combustion engines, since the requirements are different. These include a high pressure ratio, a low mass [...] Read more.
Mass-produced, off-the-shelf automotive air compressors cannot be directly used for boosting a fuel cell vehicle (FCV) application in the same way that they are used in internal combustion engines, since the requirements are different. These include a high pressure ratio, a low mass flow rate, a high efficiency requirement, and a compact size. From the established fuel cell types, the most promising for application in passenger cars or light commercial vehicle applications is the proton exchange membrane fuel cell (PEMFC), operating at around 80 °C. In this case, an electric-assisted turbocharger (E-turbocharger) and electric supercharger (single or two-stage) are more suitable than screw and scroll compressors. In order to determine which type of these boosting options is the most suitable for FCV application and assess their individual merits, a co-simulation of FCV powertrains between GT-SUITE and MATLAB/SIMULINK is realised to compare vehicle performance on the Worldwide Harmonised Light Vehicle Test Procedure (WLTP) driving cycle. The results showed that the vehicle equipped with an E-turbocharger had higher performance than the vehicle equipped with a two-stage compressor in the aspects of electric system efficiency (+1.6%) and driving range (+3.7%); however, for the same maximal output power, the vehicle’s stack was 12.5% heavier and larger. Then, due to the existence of the turbine, the E-turbocharger led to higher performance than the single-stage compressor for the same stack size. The solid oxide fuel cell is also promising for transportation application, especially for a use as range extender. The results show that a 24-kWh electric vehicle can increase its driving range by 252% due to a 5 kW solid oxide fuel cell (SOFC) stack and a gas turbine recovery system. The WLTP driving range depends on the charge cycle, but with a pure hydrogen tank of 6.2 kg, the vehicle can reach more than 600 km. Full article
(This article belongs to the Special Issue Electric Vehicle Charging)
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16 pages, 3693 KiB  
Article
Optimal Energy Management of V2B with RES and ESS for Peak Load Minimization
by Nandinkhuu Odkhuu, Ki-Beom Lee, Mohamed A. Ahmed and Young-Chon Kim
Appl. Sci. 2018, 8(11), 2125; https://doi.org/10.3390/app8112125 - 1 Nov 2018
Cited by 18 | Viewed by 4895
Abstract
In order to decrease fuel consumption and greenhouse gas emissions, electric vehicles (EVs) are being widely adopted as a future transportation system. Accordingly, increasing the number of EVs will mean battery charging will have a significant impact on the power grid. In order [...] Read more.
In order to decrease fuel consumption and greenhouse gas emissions, electric vehicles (EVs) are being widely adopted as a future transportation system. Accordingly, increasing the number of EVs will mean battery charging will have a significant impact on the power grid. In order to manage EV charging, an intelligent charging strategy is required to prevent the power grid from overloading. Therefore, we propose an optimal energy management algorithm (OEMA) to minimize peak load on a university campus consisting of an educational building with laboratories, a smart parking lot, EVs, photovoltaic (PV) panels and an energy storage system (ESS). Communication networks are used to connect all the system components to a university energy management system (UEMS). The proposed OEMA algorithm coordinates EV charging/discharging so as to reduce the peak load of the building’s power consumption by considering the real-time price (RTP). We also develop a priority determination method for the time allocation of the optimal charging algorithm. Priority is determined by arrival time, departure time, state-of-charge (SOC), battery capacity and trip distance. The performance of the proposed algorithm is evaluated in terms of charging cost and peak load under the real environment of the university engineering building. Full article
(This article belongs to the Special Issue Electric Vehicle Charging)
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19 pages, 5031 KiB  
Article
A Fuzzy State-of-Charge Estimation Algorithm Combining Ampere-Hour and an Extended Kalman Filter for Li-Ion Batteries Based on Multi-Model Global Identification
by Xin Lai, Dongdong Qiao, Yuejiu Zheng and Long Zhou
Appl. Sci. 2018, 8(11), 2028; https://doi.org/10.3390/app8112028 - 23 Oct 2018
Cited by 36 | Viewed by 3005
Abstract
The popular and widely reported lithium-ion battery model is the equivalent circuit model (ECM). The suitable ECM structure and matched model parameters are equally important for the state-of-charge (SOC) estimation algorithm. This paper focuses on high-accuracy models and the estimation algorithm with high [...] Read more.
The popular and widely reported lithium-ion battery model is the equivalent circuit model (ECM). The suitable ECM structure and matched model parameters are equally important for the state-of-charge (SOC) estimation algorithm. This paper focuses on high-accuracy models and the estimation algorithm with high robustness and accuracy in practical application. Firstly, five ECMs and five parameter identification approaches are compared under the New European Driving Cycle (NEDC) working condition in the whole SOC area, and the most appropriate model structure and its parameters are determined to improve model accuracy. Based on this, a multi-model and multi-algorithm (MM-MA) method, considering the SOC distribution area, is proposed. The experimental results show that this method can effectively improve the model accuracy. Secondly, a fuzzy fusion SOC estimation algorithm, based on the extended Kalman filter (EKF) and ampere-hour counting (AH) method, is proposed. The fuzzy fusion algorithm takes advantage of the advantages of EKF, and AH avoids the weaknesses. Six case studies show that the SOC estimation result can hold the satisfactory accuracy even when large sensor and model errors exist. Full article
(This article belongs to the Special Issue Electric Vehicle Charging)
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17 pages, 3809 KiB  
Article
Energy Trading with Electric Vehicles in Smart Campus Parking Lots
by Mohamed A. Ahmed and Young-Chon Kim
Appl. Sci. 2018, 8(10), 1749; https://doi.org/10.3390/app8101749 - 27 Sep 2018
Cited by 17 | Viewed by 5368
Abstract
Energy trading with electric vehicles provides opportunities to eliminate the high peak demand for electric vehicle charging while providing cost saving and profits for all participants. This work aims to design a framework for local energy trading with electric vehicles in smart parking [...] Read more.
Energy trading with electric vehicles provides opportunities to eliminate the high peak demand for electric vehicle charging while providing cost saving and profits for all participants. This work aims to design a framework for local energy trading with electric vehicles in smart parking lots where electric vehicles are able to exchange energy through buying and selling prices. The proposed architecture consists of four layers: the parking energy layer, data acquisition layer, communication network layer, and market layer. Electric vehicles are classified into three different types: seller electric vehicles (SEVs) with an excess of energy in the battery, buyer electric vehicles (BEVs) with lack of energy in the battery, and idle electric vehicles (IEVs). The parking lot control center (PLCC) plays a major role in collecting all available offer/demand information among parked electric vehicles. We propose a market mechanism based on the Knapsack Algorithm (KPA) to maximize the PLCC profit. Two cases are considered: electric vehicles as energy sellers and the PLCC as an energy buyer, and electric vehicles as energy buyers and the PLCC as an energy seller. A realistic parking pattern of a parking lot on a university campus is considered as a case study. Different scenarios are investigated with respect to the number of electric vehicles and amount of energy trading. The proposed market mechanism outperforms the conventional scheme in view of costs and profits. Full article
(This article belongs to the Special Issue Electric Vehicle Charging)
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21 pages, 5936 KiB  
Article
A Modular Cell Balancer Based on Multi-Winding Transformer and Switched-Capacitor Circuits for a Series-Connected Battery String in Electric Vehicles
by Thuc Minh Bui, Chang-Hwan Kim, Kyu-Ho Kim and Sang Bong Rhee
Appl. Sci. 2018, 8(8), 1278; https://doi.org/10.3390/app8081278 - 1 Aug 2018
Cited by 26 | Viewed by 6457
Abstract
In this paper, a cell balancing topology for a series-connected Lithium-Ion battery string (SCBS) in electric vehicles is proposed and experimentally verified. In particular, this balancing topology based on the modular balancer consists of an intra-module balancer based on a multi-winding transformer circuit [...] Read more.
In this paper, a cell balancing topology for a series-connected Lithium-Ion battery string (SCBS) in electric vehicles is proposed and experimentally verified. In particular, this balancing topology based on the modular balancer consists of an intra-module balancer based on a multi-winding transformer circuit and an outer-module balancer based on a switched capacitor converter, both offering the potential advantages and over conventional balancing methods, including short equalization time, simple control scheme, elimination of voltage sensors. In addition, a number of cells in the SCBS can be easily extended in this circuit. Furthermore, a system structure and an operating principle of the proposed topology are analyzed and experimentally verified for three different cases. The voltages of all cells in the SCBS reached the balanced state regardless of the various arrangement of the initial voltage, where the energy efficiency of the circuit reached 83.31%. Our experimental realization of the proposed balancing topology shows that such a technique could be employed in electric vehicles. Full article
(This article belongs to the Special Issue Electric Vehicle Charging)
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18 pages, 1656 KiB  
Article
Research on Power Demand Suppression Based on Charging Optimization and BESS Configuration for Fast-Charging Stations in Beijing
by Yian Yan, Jiuchun Jiang, Weige Zhang, Mei Huang, Qiang Chen and Huang Wang
Appl. Sci. 2018, 8(8), 1212; https://doi.org/10.3390/app8081212 - 24 Jul 2018
Cited by 18 | Viewed by 3415
Abstract
In order to reduce the recharging time of electric vehicles, the charging power and voltage are becoming higher, which has led to a huge distribution capacity demand and load fluctuation, especially in pure electric buses (PEBs) with large onboard batteries. Based on one [...] Read more.
In order to reduce the recharging time of electric vehicles, the charging power and voltage are becoming higher, which has led to a huge distribution capacity demand and load fluctuation, especially in pure electric buses (PEBs) with large onboard batteries. Based on one actual direct current (DC) fast-charging station, a two-step strategy for the suppression of the peak charging power was developed in this paper, which combined charging optimization and a battery energy storage system (BESS) configuration. A novel charging strategy was proposed, with the PEBs fast-charging during operating hours and normal charging at night, based on a new charging topology. Then, a charging sequence optimization model was established, according to the operation characteristics analysis of the DC fast-charging station. The particle swarm optimization (PSO) algorithm is applied to optimize the charging sequence, which is disordered at present. Linear programming is used to configure the battery energy storage system in order to further decrease the peak charging power and satisfy the distribution capacity constraint. The two-step strategy was simulated by the dataset from the real station. The results show that the distribution capacity demand, charging load fluctuation, electricity cost, and size of the BESS were significantly decreased. Full article
(This article belongs to the Special Issue Electric Vehicle Charging)
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25 pages, 4578 KiB  
Article
Bi-Level Planning Model of Charging Stations Considering the Coupling Relationship between Charging Stations and Travel Route
by Haixiang Zang, Yuting Fu, Ming Chen, Haiping Shen, Liheng Miao, Side Zhang, Zhinong Wei and Guoqiang Sun
Appl. Sci. 2018, 8(7), 1130; https://doi.org/10.3390/app8071130 - 12 Jul 2018
Cited by 8 | Viewed by 3188
Abstract
The major factors affecting the popularization of electric vehicles (EV) are the limited travel range and the lack of charging infrastructure. Therefore, to further promote the penetration of EVs, it is of great importance to plan and construct more fast charging stations rationally. [...] Read more.
The major factors affecting the popularization of electric vehicles (EV) are the limited travel range and the lack of charging infrastructure. Therefore, to further promote the penetration of EVs, it is of great importance to plan and construct more fast charging stations rationally. In this study, first we establish a travel pattern model based on the Monte Carlo simulation (MCS). Then, with the traveling data of EVs, we build a bi-level planning model of charging stations. For the upper model, with an aim to maximize the travel success ratio, we consider the influence of the placement of charging stations on the user’s travel route. We adopt a hybrid method based on queuing theory and the greedy algorithm to determine the capacity of charging stations, and we utilize the total social cost and satisfaction index as two indicators to evaluate the optimal solutions obtained from the upper model. Additionally, the impact of the increase of EV ownership and slow charger coverage in the public parking lot on the fast charging demands and travel pattern of EV users are also studied. The example verifies the feasibility of the proposed method. Full article
(This article belongs to the Special Issue Electric Vehicle Charging)
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16 pages, 4944 KiB  
Article
Modeling and Solving Method for Supporting ‘Vehicle-to-Anything’ EV Charging Mode
by Tian Mao, Xin Zhang and Baorong Zhou
Appl. Sci. 2018, 8(7), 1048; https://doi.org/10.3390/app8071048 - 27 Jun 2018
Cited by 22 | Viewed by 4056
Abstract
Electric vehicles (EVs) are an attractive solution to make traditional transportation energy-efficient and environmentally friendly. EVs are also considered an important element to bring new opportunities for power grids. In addition to the role of a pure load, along with the development of [...] Read more.
Electric vehicles (EVs) are an attractive solution to make traditional transportation energy-efficient and environmentally friendly. EVs are also considered an important element to bring new opportunities for power grids. In addition to the role of a pure load, along with the development of discharging technology for batteries, EVs can deliver energy back to power grids or another power consumption entity or community, performing various discharging activities such as vehicle-to-home (V2H), vehicle-to-building (V2B), vehicle-to-vehicle (V2V), vehicle-to-grid (V2G), etc. These charging scenarios can be uniformly named the ‘Vehicle-to-anything’ (V2A) charging mode. The paradigm of this charging mode has already been given; however, the modeling and solving approaches are still insufficient. Therefore, the analysis and modeling of V2A are investigated herein. The aim is to propose a generic model suitable for different applications of V2A in different places. The characteristics of the V2A charging mode are given and analyzed first. Then a model that can adapt to the V2A scenario is illustrated. The optimization problem is transformed and solved as an INLP (integer nonlinear programming) problem. The effectiveness of the approach is verified with simulation results. The outcome also indicates that V2A applications have great potential for lowering power consumption costs; for instance, a reduction of 4.37% in energy expense can be achieved in a case study with EV discharging enabled for a household. Full article
(This article belongs to the Special Issue Electric Vehicle Charging)
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14 pages, 5105 KiB  
Article
Virtual Synchronous Motor Based-Control of a Three-Phase Electric Vehicle Off-Board Charger for Providing Fast-Charging Service
by Xiangwu Yan, Jiajia Li, Bo Zhang, Zhonghao Jia, Yang Tian, Hui Zeng and Zhipeng Lv
Appl. Sci. 2018, 8(6), 856; https://doi.org/10.3390/app8060856 - 23 May 2018
Cited by 17 | Viewed by 4489
Abstract
This study introduces a three-phase virtual synchronous motor (VSM) control and its possible application for providing fast-charging service from off-board chargers of electric vehicles (EVs). The main circuit of the off-board charger consists of a three-phase voltage source PWM rectifier (VSR) and a [...] Read more.
This study introduces a three-phase virtual synchronous motor (VSM) control and its possible application for providing fast-charging service from off-board chargers of electric vehicles (EVs). The main circuit of the off-board charger consists of a three-phase voltage source PWM rectifier (VSR) and a resonant LLC zero-voltage-switching converter. In the proposed control approach, VSM-controlled pre-stage VSR emulates the external characteristics of a synchronous motor (SM), simultaneously, droop control based on charging mode in the VSM can satisfy the demand of the EVs constant-current fast-charging; The post-stage DC–DC converter is responsible for stabilizing the DC bus voltage. The feature of this control strategy is that VSM and fast charging control are implemented by the pre-stage converter, which has better coordination. In the MATLAB, the equivalent synchronous grid of the distribution network supplies to the power battery through the off-board charger, and the effectiveness of the presented control is demonstrated by typical working conditions. Full article
(This article belongs to the Special Issue Electric Vehicle Charging)
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17 pages, 2819 KiB  
Article
An Optimal Domestic Electric Vehicle Charging Strategy for Reducing Network Transmission Loss While Taking Seasonal Factors into Consideration
by Yuancheng Zhao, Yanbo Che, Dianmeng Wang, Huanan Liu, Kun Shi and Dongmin Yu
Appl. Sci. 2018, 8(2), 191; https://doi.org/10.3390/app8020191 - 26 Jan 2018
Cited by 11 | Viewed by 4223
Abstract
With the rapid growth of domestic electric vehicle charging loads, the peak-valley gap and power fluctuation rate of power systems increase sharply, which can lead to the increase of network losses and energy efficiency reduction. This paper tries to regulate network loads and [...] Read more.
With the rapid growth of domestic electric vehicle charging loads, the peak-valley gap and power fluctuation rate of power systems increase sharply, which can lead to the increase of network losses and energy efficiency reduction. This paper tries to regulate network loads and reduce power system transmission loss by optimizing domestic electric vehicle charging loads. In this paper, a domestic electric vehicle charging loads model is first developed by analyzing the key factors that can affect users’ charging behavior. Subsequently, the Monte Carlo method is proposed to simulate the power consumption of a cluster of domestic electric vehicles. After that, an optimal electric vehicle charging strategy based on the 0-1 integer programming is presented to regulate network daily loads. Finally, by taking the IEEE33 distributed power system as an example, this paper tries to verify the efficacy of the proposed optimal charging strategy and the necessity for considering seasonal factors when scheduling electric vehicle charging loads. Simulation results show that the proposed 0-1 integer programming method does have good performance in reducing the network peak-valley gap, voltage fluctuation rate, and transmission loss. Moreover, it has some potential to further reduce power system transmission loss when seasonal factors are considered. Full article
(This article belongs to the Special Issue Electric Vehicle Charging)
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