Special Issue "Advanced Technologies for Electric Vehicles in Sustainable and Reliable Power Grids"

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "Electric Vehicles".

Deadline for manuscript submissions: 31 August 2022.

Special Issue Editors

Prof. Dr. Stefano Bracco
E-Mail Website
Guest Editor
Electrical, Electronics and Telecommunication Engineering and Naval Architecture Department (DITEN), University of Genoa, Via Opera Pia 11a, 16145 Genoa, Italy
Interests: optimization and simulation of microgrids and nanogrids; smart charging of electric vehicles and V2G technologies; power systems management
Special Issues and Collections in MDPI journals
Dr. Ruixin Yang
E-Mail Website
Co-Guest Editor
Department of Vehicle Engineering, School of Mechanical Engineering, Beijing Institute of Technology, No.5 Zhongguancun Street, Beijing 100081, China
Interests: electric/hybrid vehicles; energy storage system; intelligent electrified vehicles; battery management system; battery safety management; battery thermal management; fault diagnosis

Special Issue Information

Dear Colleagues,

The energy sector is more and more characterized by the spread of distributed generation, energy storage systems, and smart electric mobility. In many countries, renewable energy sources (mainly solar, hydro, and wind) represent a significant share of the national energy mix, and the power system architecture has deeply changed, moving from centralized energy production to decentralized production. Innovative smart grid and microgrid projects have been developed and implemented in different sectors, such as industrial areas or sustainable urban districts. Moreover, the electric mobility sector has recorded fast growth in terms of full-electric and hybrid vehicle sales and installation of chargers. Challenging initiatives related to safe and efficient applications of electric vehicles, as well as to the implementation of smart charging and V2G (vehicle-to-grid) and V2B (vehicle-to-building) technologies have been conducted too. Both renewable power plants and electric mobility infrastructures interact with power networks. The impact of the aforementioned technologies on the power system has to be investigated taking into account technical and economic aspects as well as standards and the current legislative framework. In addition, technical merits in energy storage systems, such as batteries and super/ultra-capacitors are critical for the success of transportation electrification and to foster the utilization of renewable energy sources.

This Special Issue will present the research activities focused on the analysis of the impact of electric mobility on power grids, with a particular focus on the interaction of electric vehicles and charging infrastructures with distribution networks and smart grids and microgrids. Moreover, special emphases are given to the design, modeling, management, control, and safety enhancement of energy storage systems, such as batteries, super/ultra-capacitors and fuel cells applied in transportation systems. In particular, we invite the submission of papers addressing issues related to the analysis, simulation, and optimization of both energy storage systems in electric vehicles and electric mobility systems in sustainable grids and microgrids characterized by the presence of renewable power plants and V2G and V2B technologies.

Prof. Dr. Stefano Bracco
Guest Editor

Dr. Ruixin Yang
co-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 papers will be 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. Energies 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 2000 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 vehicles
  • Energy storage systems
  • Sustainable and reliable power grids
  • Smart grids and microgrids
  • Battery management systems
  • Battery safety and thermal management
  • Fault diagnosis
  • Energy management systems
  • Optimal power flow
  • Integration of renewable energy sources in distribution power networks
  • Smart charging of electric vehicles
  • V2G and V2B technologies
  • Simulation
  • Optimization

Published Papers (3 papers)

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Research

Article
Electrification of LPT in Algeciras Bay: A New Methodology to Assess the Consumption of an Equivalent E-Bus
Energies 2021, 14(16), 5117; https://doi.org/10.3390/en14165117 - 19 Aug 2021
Viewed by 399
Abstract
The present paper proposes a new methodology to aid the electrification process of local public transport (LPT). In more detail, real drive cycles of traditional buses currently in use are evaluated together with other data to simulate the consumption of equivalent e-buses (electric [...] Read more.
The present paper proposes a new methodology to aid the electrification process of local public transport (LPT). In more detail, real drive cycles of traditional buses currently in use are evaluated together with other data to simulate the consumption of equivalent e-buses (electric buses) with similar characteristics. The results are then used in order to design the best charging infrastructure. The proposed methodology is applied to the case study of Algeciras Bay, where a specific line of LPT is considered. Real measurements are used as data for the simulation model, and the average consumption of an equivalent e-bus is obtained for different operating conditions. Based on these results, different sizes and locations for fast-charging infrastructure are proposed, and the size of the depot charging system is defined trying to maintain the current buses timetable. Finally, some future developments of the present work are presented by considering other bus lines that may benefit from the introduction of the defined charging systems. Full article
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Article
A Multi-Model Probability Based Two-Layer Fusion Modeling Approach of Supercapacitor for Electric Vehicles
Energies 2021, 14(15), 4644; https://doi.org/10.3390/en14154644 - 30 Jul 2021
Viewed by 356
Abstract
The improvement of the supercapacitor model redundancy is a significant method to guarantee the reliability of the power system in electric vehicle application. In order to enhance the accuracy of the supercapacitor model, eight conventional supercapacitor models were selected for parameter identification by [...] Read more.
The improvement of the supercapacitor model redundancy is a significant method to guarantee the reliability of the power system in electric vehicle application. In order to enhance the accuracy of the supercapacitor model, eight conventional supercapacitor models were selected for parameter identification by genetic algorithm, and the model accuracies based on standard diving cycle are further discussed. Then, three fusion modeling approaches including Bayesian fusion, residual normalization fusion, and state of charge (SOC) fragment fusion are presented and compared. In order to further improve the accuracy of these models, a two-layer fusion model based on SOC fragments is proposed in this paper. Compared with other fusion models, the root mean square error (RMSE), maximum error, and mean error of the two-layer fusion model can be reduced by at least 23.04%, 8.70%, and 30.13%, respectively. Moreover, the two-layer fusion model is further verified at 10, 25, and 40 °C, and the RMSE can be correspondingly reduced by 60.41%, 47.26%, 23.04%. The results indicate that the two-layer fusion model proposed in this paper achieves better robustness and accuracy. Full article
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Article
An Open Circuit Voltage Model Fusion Method for State of Charge Estimation of Lithium-Ion Batteries
Energies 2021, 14(7), 1797; https://doi.org/10.3390/en14071797 - 24 Mar 2021
Cited by 1 | Viewed by 603
Abstract
The mapping between open circuit voltage (OCV) and state of charge (SOC) is critical to the lithium-ion battery management system (BMS) for electric vehicles. In order to solve the poor accuracy in the local SOC range of most OCV models, an OCV model [...] Read more.
The mapping between open circuit voltage (OCV) and state of charge (SOC) is critical to the lithium-ion battery management system (BMS) for electric vehicles. In order to solve the poor accuracy in the local SOC range of most OCV models, an OCV model fusion method for SOC estimation is proposed. According to the characteristics of the experimental OCV–SOC curve, the method divides SOC interval (0, 100%) into several sub-intervals, and respectively fits the OCV curve segments in each sub-interval to obtain a corresponding number of OCV sub-models with local high precision. After that, the OCV sub-models are fused through the continuous weight function to obtain fusional OCV model. Regarding the OCV curve obtained from low-current OCV test as the criterion, the fusional OCV models of LiNiMnCoO2 (NMC) and LiFePO4 (LFP) are compared separately with the conventional OCV models. The comparison shows great fitting accuracy of the fusional OCV model. Furthermore, the adaptive cubature Kalman filter (ACKF) is utilized to estimate SOC and capacity under a dynamic stress test (DST) at different temperatures. The experimental results show that the fusional OCV model can effectively track the performance of the OCV–SOC curve model. Full article
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

1. Impact of electric mobility on the design of renewable energy collective self-consumers. Stefano Bracco, Giorgio Piazza
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