Electric Vehicles Smart Charging: Strategies, Technologies, and Challenges

Topic Information

Dear Colleagues,

This topic is related to the very academically popular but also practical subject of Electric Vehicles Smart Charging: Strategies, Technologies, and Challenges. In the last two decades, rapid development in both electric vehicle technology and successful commercialized applications has made the electrification of transportation become a reality. Our research community could dive deeper into the most recent smart charging solutions, studying improved charging efficiency and associated environmental benefits. The topic will also discuss EV-dedicated demand response programs, time-of-use pricing, vehicle-to-grid (V2G) technology, and other innovative approaches aimed at optimizing EV charging patterns to reduce grid congestion and overall energy consumption. The challenges of emerging EV technologies cannot be ignored when we consider the barriers and obstacles hindering the widespread adoption of smart charging solutions, including issues related to infrastructure deployment, interoperability, regulatory frameworks, cybersecurity concerns, and consumer acceptance. We can only speculate boldly on the further potential growth of smart charging technologies and their role in the future of smart transportation, energy systems and smart cities. Therefore, this kind of topic may help highlight areas for further research and development, helping to overcome existing challenges and accelerate the transition to electric mobility in the next decade. We have initialized this topic because we can see that mature commercialized development for electric vehicles is expanding rapidly. The next decade will be an even more important period in terms of making the transition from fossil fuel vehicles to electric vehicles. This period is critical to electric vehicle development, and we now invite you to submit a paper to report, discuss and predict upcoming research and innovations within our publication on the subject Electric Vehicles Smart Charging: Strategies, Technologies, and Challenges.

Dr. Tao Chen
Dr. Hongxun Hui
Dr. Qianzhi Zhang
Dr. Zhao Yuan
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Batteries batteries	4.6	6.6	2015	19.7 Days	CHF 2700	Submit
Electronics electronics	2.6	6.1	2012	16.4 Days	CHF 2400	Submit
Energies energies	3.0	7.3	2008	16.8 Days	CHF 2600	Submit
Eng eng	-	3.2	2020	21.5 Days	CHF 1200	Submit
Smart Cities smartcities	7.0	14.7	2018	28.4 Days	CHF 2000	Submit
Vehicles vehicles	2.4	5.3	2019	19.9 Days	CHF 1600	Submit

Preprints.org is a multidisciplinary platform offering a preprint service designed to facilitate the early sharing of your research. It supports and empowers your research journey from the very beginning.

MDPI Topics is collaborating with Preprints.org and has established a direct connection between MDPI journals and the platform. Authors are encouraged to take advantage of this opportunity by posting their preprints at Preprints.org prior to publication:

1. Share your research immediately: disseminate your ideas prior to publication and establish priority for your work.
2. Safeguard your intellectual contribution: Protect your ideas with a time-stamped preprint that serves as proof of your research timeline.
3. Boost visibility and impact: Increase the reach and influence of your research by making it accessible to a global audience.
4. Gain early feedback: Receive valuable input and insights from peers before submitting to a journal.
5. Ensure broad indexing: Web of Science (Preprint Citation Index), Google Scholar, Crossref, SHARE, PrePubMed, Scilit and Europe PMC.

Published Papers (3 papers)

Order results

Content type Publication Date

Result details

Normal Extended Compact

Journals

All Batteries Electronics Energies Eng Smart Cities Vehicles

Show export options expand_more Show export options expand_less

Select all

Export citation of selected articles as:

Plain Text BibTeX BibTeX (without abstracts) Endnote Endnote (without abstracts) Tab-delimited RIS

Error

Oops... you haven't selected anything for export.

Ok

clear

17 pages, 3748 KiB  

Open AccessArticle

Research on Lithium-Ion Battery State of Health Prediction Based on XGBoost–ARIMA Joint Optimization

by Chen Fei, Zhuo Lu, Weiwei Jiang, Liang Zhao and Fan Zhang

Batteries 2025, 11(6), 207; https://doi.org/10.3390/batteries11060207 - 23 May 2025

Viewed by 516

Abstract

Due to the complex electrochemical reactions within lithium-ion batteries and the uncertainties with respect to external environmental factors, accurately assessing their State of Health (SOH) remains a significant challenge. To improve the precision of SOH estimation, we propose an intelligent estimation approach that [...] Read more.

Due to the complex electrochemical reactions within lithium-ion batteries and the uncertainties with respect to external environmental factors, accurately assessing their State of Health (SOH) remains a significant challenge. To improve the precision of SOH estimation, we propose an intelligent estimation approach that integrates data visualization and advanced machine learning techniques. Initially, the battery data are visualized using matplotlib to extract key features such as temperature difference, voltage difference, and average voltage. Subsequently, an XGBoost-based model is constructed to perform the initial SOH estimation. To further enhance the estimation accuracy, we introduce the Autoregressive Integrated Moving Average Model (ARIMA) model for post-estimation correction, effectively refining the preliminary results. Experimental results demonstrate that the proposed XGBoost–ARIMA model outperforms traditional algorithms, including Linear Regression (LR), Random Forest (RF), Support Vector Machine (SVM), and K-Nearest Neighbor (KNN), not only in estimation accuracy but also in generalization capability, showing significant improvements over five other regression models. Full article

(This article belongs to the Topic Electric Vehicles Smart Charging: Strategies, Technologies, and Challenges)

►▼ Show Figures

Figure 1

14 pages, 2421 KiB  

Open AccessArticle

Coordinated Optimization Method of Electric Buses and Voltage Source Converters for Improving the Absorption Capacity of New Energy Sources and Loads in Distribution Networks

by Yang Liu, Min Huang, Yujing Zhang, Lu Zhang, Wenbin Liu, Haidong Yu, Feng Wang and Lisheng Li

Energies 2025, 18(4), 832; https://doi.org/10.3390/en18040832 - 11 Feb 2025

Cited by 1 | Viewed by 487

Abstract

The large-scale integration of renewable energy sources and new loads, such as distributed photovoltaics and electric vehicles, has resulted in frequent power quality issues within distribution networks. Traditional AC distribution networks lack the necessary flexibility and have limited capacity to accommodate these new [...] Read more.

The large-scale integration of renewable energy sources and new loads, such as distributed photovoltaics and electric vehicles, has resulted in frequent power quality issues within distribution networks. Traditional AC distribution networks lack the necessary flexibility and have limited capacity to accommodate these new energy sources and loads. Transforming the conventional distribution network into an AC-DC hybrid network using flexible interconnection devices like Voltage Source Converters can enhance the network’s flexibility, mitigating the power quality challenges arising from the integration of renewable energy and new loads. Electric buses, with their substantial capacity, mobility, and centralized management, offer potential as mobile energy storage. They can participate in the dispatching of the distribution network, thereby improving the network’s flexibility in power regulation. This paper proposes a coordinated optimization approach that integrates electric buses and VSCs for distribution network dispatch. This method enables electric buses to assist in power dispatch without interfering with their primary public transport duties, thus enhancing the network’s capacity to absorb new energy sources and loads. Firstly, considering the mobility characteristics of electric buses, a multi-layer stochastic Time–Space Network model is developed for bus dispatching. Secondly, an optimization model is constructed that accounts for the coordination of charging and discharging power between VSCs and electric buses, with the objective of minimizing the network losses in the distribution system. Finally, the proposed model is transformed into a second-order cone programming formulation, facilitating its solution through convex optimization techniques. The effectiveness of the proposed approach is demonstrated through a case study. Full article

(This article belongs to the Topic Electric Vehicles Smart Charging: Strategies, Technologies, and Challenges)

►▼ Show Figures

Figure 1

44 pages, 5949 KiB  

Open AccessReview

Review of Authentication, Blockchain, Driver ID Systems, Economic Aspects, and Communication Technologies in DWC for EVs in Smart Cities Applications

by Narayanamoorthi Rajamanickam, Pradeep Vishnuram, Dominic Savio Abraham, Miroslava Gono, Petr Kacor and Tomas Mlcak

Smart Cities 2024, 7(6), 3121-3164; https://doi.org/10.3390/smartcities7060122 - 24 Oct 2024

Viewed by 1598

Abstract

The rapid advancement and adoption of electric vehicles (EVs) necessitate innovative solutions to address integration challenges in modern charging infrastructure. Dynamic wireless charging (DWC) is an innovative solution for powering electric vehicles (EVs) using multiple magnetic transmitters installed beneath the road and a [...] Read more.

The rapid advancement and adoption of electric vehicles (EVs) necessitate innovative solutions to address integration challenges in modern charging infrastructure. Dynamic wireless charging (DWC) is an innovative solution for powering electric vehicles (EVs) using multiple magnetic transmitters installed beneath the road and a receiver located on the underside of the EV. Dynamic charging offers a solution to the issue of range anxiety by allowing EVs to charge while in motion, thereby reducing the need for frequent stops. This manuscript reviews several pivotal areas critical to the future of EV DWC technology such as authentication techniques, blockchain applications, driver identification systems, economic aspects, and emerging communication technologies. Ensuring secure access to this charging infrastructure requires fast, lightweight authentication systems. Similarly, blockchain technology plays a critical role in enhancing the Internet of Vehicles (IoV) architecture by decentralizing and securing vehicular networks, thus improving privacy, security, and efficiency. Driver identification systems, crucial for EV safety and comfort, are analyzed. Additionally, the economic feasibility and impact of DWC are evaluated, providing essential insights into its potential effects on the EV ecosystem. The paper also emphasizes the need for quick and lightweight authentication systems to ensure secure access to DWC infrastructure and discusses how blockchain technology enhances the efficiency, security, and privacy of IoV networks. The importance of driver identification systems for comfort and safety is evaluated, and an economic study confirms the viability and potential benefits of DWC for the EV ecosystem. Full article

(This article belongs to the Topic Electric Vehicles Smart Charging: Strategies, Technologies, and Challenges)

►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less

Select all

Export citation of selected articles as:

Plain Text BibTeX BibTeX (without abstracts) Endnote Endnote (without abstracts) Tab-delimited RIS

 

Error

Oops... you haven't selected anything for export.

Ok

clear

Displaying articles 1-3