Charging Infrastructure Research Articles

Enhancing sustainability in electric mobility: Exploring blockchain applications for secure EV charging and energy management

The global shift towards reducing carbon emissions has spurred a growing interest in electric vehicles (EVs) over traditional fossil fuel-based internal combustion engines. Concurrently, blockchain technology has emerged as a transformative solution across various sectors, characterized by its decentralized database and distributed ledger. Its notable attributes, including transparency, immutability, traceability, security, auditability, and authenticity, have led major companies to recognize its potential integration into the EV sector. As a result, there has been a steady increase in case studies and research initiatives exploring blockchain applications in EVs. This article provides a detailed overview of the use of blockchain in the EV domain, focusing on the challenges and applications in four key areas: EV charging infrastructure, energy trading, supply chain management, and energy management. Initially, the basic concepts of blockchain technology are briefly explained, followed by its applications in different fields. The study presents the opportunities and crucial requirements for implementing blockchain technology for secure energy trading, charging, energy management, and supply chain operations. While blockchain can improve security and efficiency in the EV domain, it remains vulnerable to various attacks. This article explores these attacks and other potential challenges in integrating blockchain technology in the EV sector. The main findings of this rEView provide insights into the importance of blockchain in the EV sector and underscore the need to overcome existing challenges for the widespread adoption of this technology in the near future.

Analyzing the Reasons on Decreasing in Sales for Tesla

Since the end of the epidemic, people's travel demand has gradually recovered, and the demand for transportation has greatly increased; however, in this context, Tesla Motors has experienced a decline in sales. The aim of this study was to examine the reasons that contributed to the decrease in Tesla's sales in the first quarter of 2024. This article examines the variables that have contributed to the decline in Tesla's sales by reviewing sales statistics from previous years in Europe, the United States, and China. This study subsequently outlines the three main variables that are responsible for the decrease in sales for Tesla. The reasons include several variables, such as production challenges, increased competition, and a negative shift in client preferences. This article proposes three ideas to tackle the problem of decreasing sales: diversifying the product range, establishing strategic alliances, and enhancing the charging infrastructure. Moreover, this post has greatly advanced the electric vehicle market by clarifying the reasons for its decline and providing helpful suggestions.

Design and Implementation of Photovoltaic Electric Vehicle Charging Stations: A Case Study at Universidad Tecnológica de Pereira

As the global transportation sector transitions towards sustainability, the need for renewable energy- powered electric vehicle (EV) charging infrastructure becomes increasingly evident. This paper presents a case study on the design and implementation of a photovoltaic electric vehicle charging stations at the Universidad Tecnológica de Pereira (Colombia). The study outlines the design process, technical specifications, and implementation strategies for a photovoltaic (PV) charging station, emphasizing key considerations such as location selection, solar panel configuration, and necessary equipment. Additionally, the paper evaluates the performance and effectiveness of the PV charging station in supplying the demand for EV charging services on campus. This case study provides valuable insights into the feasibility and scalability of PV EV charging infrastructure in educational institutions.

Optimal planning for electric vehicle fast charging stations placements in a city scale using an advantage actor-critic deep reinforcement learning and geospatial analysis

The transition to Electric Vehicles (EVs) for reducing urban greenhouse gas emissions is hindered by the lack of public charging infrastructure, particularly fast-charging stations. Given that electric vehicle fast charging stations (EVFCS) can burden the electricity grid, it is crucial for EVFCS to adopt sustainable energy supply methods while accommodating the growing demands of EVs. Despite recent research efforts to optimize the placement of renewable-powered EV charging stations, current planning methods face challenges when applied to a complex city scale and integrating with renewable energy resources. This study thus introduces a robust decision-making model for optimal EVFCS placement planning integrated with solar power supply in a large and complex urban environment (e.g., Chicago), utilizing an advantage actor-critic (A2C) deep reinforcement learning (DRL) approach. The model balances traffic demand with energy supply, strategically placing charging stations in areas with high traffic density and solar potential. As a result, the model is used to optimally place 1,000 charging stations with a random starting search approach, achieving total reward values of 74.30 %, and estimated the capacities of potential EVFCS. This study can inform the identification of suitable locations to advance the microgrid-based charging infrastructure systems in large urban environments.

A Review of Modular Electrical Sub-Systems of Electric Vehicles

Climate change risks have triggered the international community to find efficient solutions to reduce greenhouse gas (GHG) emissions mainly produced by the energy, industrial, and transportation sectors. The problem can be significantly tackled by promoting electric vehicles (EVs) to be the dominant technology in the transportation sector. Accordingly, there is a pressing need to increase the scale of EV penetration, which requires simplifying the manufacturing process, increasing the training level of maintenance personnel, securing the necessary supply chains, and, importantly, developing the charging infrastructure. A new modular trend in EV manufacturing is being explored and tested by several large automotive companies, mainly in the USA, the European Union, and China. This modular manufacturing platform paves the way for standardised manufacturing and assembly of EVs when standard scalable units are used to build EVs at different power scales, ranging from small light-duty vehicles to large electric buses and trucks. In this context, modularising EV electric systems needs to be considered to prepare for the next EV generation. This paper reviews the main modular topologies presented in the literature in the context of EV systems. This paper summarises the most promising topologies in terms of modularised battery connections, propulsion systems focusing on inverters and rectifiers, modular cascaded EV machines, and modular charging systems.

A decision framework for improving the service quality of charging stations based on online reviews and evolutionary game theory

With “charging anxiety” gradually replacing “range anxiety” as the major obstacle for consumers to purchase electric vehicles (EVs), the quantity-driven rather than quality-driven charging station development model barely meets the development of the EV market. It is of great practical significance that a comprehensive and in-depth insight into charging stations’ customer requirements (CRs) to uncover their pain points and improvement measures. Therefore, this study develops a decision framework for improving EV charging service quality based on quality function deployment (QFD). First, CRs are extracted based on charging station online reviews and classified by the revised importance performance analysis (IPA) method to identify the charging service’s main highlights and pain points. Then, the process of achieving consensus among experts on evaluating the correlation between CRs and service design requirements (DRs) is considered as an evolutionary game of coalition, with a meritocratic Fermi rule considering affinities (MFA) being introduced. Finally, the importance of DRs is determined by combining the Shapley value and risk aversion theory. The results indicate that regulation and convenience are the main highlights of charging stations to satisfy EV users, while reliability and assurance are primary pain points. The charging station operators should prioritize their limited resources on providing efficient customer and maintenance services, installing charging stations with international standards, and regularly inspecting and updating charging infrastructures. This study is beneficial for charging station operators to understand what customers want and how to satisfy them.

Electric vehicle industry and sustainable economic growth: A measurement, coupling and causal analysis

This study examines the electric vehicle (EV) industry's impact on sustainable economic growth (SEG). Using the entropy weight method, it evaluates the EV industry's development and SEG levels. A coupling coordination degree model measures their interaction. Results show a positive trend in both areas, with charging infrastructure expansion and foreign investments being key drivers. The study finds a progressive shift from imbalance to high-quality coordination between the EV industry and SEG, highlighting their increasingly synergistic relationship. This growth in the EV industry fosters technological innovation and drives green advancements throughout the industry chain, thereby enhancing SEG.

Detecting Distributed Denial-of-Service (DDoS) attacks that generate false authentications on Electric Vehicle (EV) charging infrastructure

In recent years, smart grid-based Electric Vehicle (EV) charging systems have increasingly faced vulnerabilities to Distributed Denial of Service (DDoS) attacks, especially through malicious authentication failures. These attacks typically involve monopolizing the Grid Server (GS), thereby hindering the authentication process for legitimate EVs. Despite the severity of this issue, no research (to the best of our knowledge) has focused on detecting DDoS attacks exploiting weaknesses in EV authentication. This study introduces a DDoS attack detection model specifically designed for EV authentication. The approach involves developing a machine learning model involving unique feature selection and combination. The proposed approach has been evaluated using a new DDOS attack dataset. The model is engineered to optimize feature combination, aiming for high sampling resolution, minimal information loss, and robust performance under 16 distinct attack scenarios. The feature combination used in this study shows improved accuracy over traditional DDoS detection methods based on access time variation while minimizing information loss.

Electric vehicle charging technologies, infrastructure expansion, grid integration strategies, and their role in promoting sustainable e-mobility

The transport sector is experiencing a notable transition towards sustainability, propelled by technological progress, innovative materials, and a dedication to environmental preservation. This study explicitly examines the incorporation of electric vehicles (EVs) into the power grid, with a particular emphasis on passenger automobiles. Our analysis emphasises the vital importance of updated transport infrastructure in decreasing greenhouse gas emissions and aiding carbon reduction efforts in electricity networks. The analysis uncovers that adopting electric vehicles offers significant advantages, including enhanced grid efficiency and decreased emissions. However, it also brings issues concerning the design and operation of power systems at both the transmission and distribution levels. Key players are crucial in tackling these difficulties to improve electric vehicle integration into the grid. The study determines the most effective ways for distributing and providing electric vehicle charging infrastructure, and investigates the efforts made to establish common standards in order to solve current challenges. This research contributes to the advancement of sustainable mobility and energy systems by conducting a thorough examination of the impact of electric vehicles on power systems and offering appropriate integration solutions.

Electrification of marinas in Stockholm: Optimizing charging infrastructure for electric boats

The adoption of electric boats faces challenges due to range anxiety. This study addresses this challenge by optimizing the allocation of slow and fast chargers for public electric boat charging stations. A mixed-integer linear programming model was developed to minimize charging infrastructure and electricity costs while meeting the demand of each participating marina in Stockholm, Sweden. The model identified three distinct categories of stations based on the optimal charger allocation: stations prioritizing fast chargers (e.g., Sickla station with 13 fast and 8 slow chargers for 208 boats), stations prioritizing slow chargers (e.g., Kungsholmen station with 2 slow and 3 fast chargers for 50 boats), and stations with an equal number of both charger types (Äppelviken station with 2 each for 25 boats). This study found out that all stations will achieve financial viability within seven years, indicating a promising return on investment. This study also proposes a novel way for optimizing charger allocation in electric boat charging infrastructure, promoting wider electric boat adoption.

Strategies and models for optimal EV charging station site selection

Abstract In numerous countries worldwide, adopting electric vehicles (EVs) is gaining momentum as a proactive measure to mitigate the detrimental environmental impacts of traditional fuel-powered automobiles. This shift drives exponential growth in the adoption of EVs, prompting the need for comprehensive analysis to optimize charging infrastructure requirements. Developing reliable and sustainable charging infrastructure depends on practical and strategic site selection of EV charging stations. The main challenge is finding a charging solution that maximizes efficiency within limited financial resources. The present review critically assesses methodologies for selecting optimal EV charging station sites, considering technical, environmental, social, and economic factors. Special emphasis is given to social factors such as population density and service accessibility, as well as technical factors like vehicle battery life, charging time, and grid capacity. Environmental impact and feasibility are also vital criteria under evaluation. Through a synthesis of insights from various studies, this review provides a comprehensive overview of the existing models used in EV charging infrastructure site selection. The findings contribute valuable insights for decision-makers, city planners, and other stakeholders in creating sustainable EV charging networks amidst the dynamic landscape of electric mobility.

Introducing a Three‐Layer Model Taxonomy to Facilitate System‐of‐Systems Co‐Simulation

AbstractThe growing demand for efficient, resilient, and sustainable electricity infrastructure has led to the emergence of smart grids as cyber‐physical systems of systems. Co‐simulation has proven an effective tool for their analysis and validation by coordinating independent subsystem simulations. However, the reuse and integration of diverse models in co‐simulation poses challenges, requiring compatibility and integration efforts. In response, this paper proposes a model taxonomy with the purpose of facilitating co‐simulation; it comprises three layers: concrete‐instance models, abstract‐instance models, and type models. The taxonomy contributes to the creation of independently developed models that can be seamlessly integrated into a coupled co‐simulation. Furthermore, it reflects the emergence of digital twins in smart grid engineering by the explicit distinction of abstract and concrete instances. The three‐layer taxonomy was derived and validated through a case study on co‐simulation of electric‐vehicle charging infrastructure. The research further analyzes and formalizes three modeling‐and‐simulation challenges framed through the lens of the taxonomy: the integration of models across all three layers, the merging of layers, and the consolidation of instance models to craft joint co‐simulation scenarios. Finally, three concrete recommendations for research and industrial practice are given. Thereby, the study contributes to the efficient and effective model‐based validation of cyber‐physical systems of systems using co‐simulation.

A centralized fleet management system for electrified transportation

Abstract Hybrid Electric Vehicles are a promising alternative to Conventional and Electric Vehicles, as they offer better fuel economy, lower emissions, and long drive range without requiring extensive charging infrastructure. Limited driving range and battery degradation in electric vehicles are the main challenges in electrified fleets working in large metropolitan. For these challenges, the hybrid electric vehicle fleet management system is an effective solution to optimize power consumption and mitigate electric vehicle and conventional vehicle challenges. This paper proposes a hybrid electric vehicle fleet management system for public transportation, to analyze and investigate the performance and energy consumption rate of conventional, electric, and hybrid electric vehicles on different routes using representative driving cycles. The hybrid electric vehicle fleet management system enhances operational efficiency for the fleet management system and reduces power consumption in transportation. The proposed work comprises a hybrid electric vehicle model that is based on object-oriented programming. The proposed work offers the ability to add the input of the initial state of charge, power split ratio, and route data for each bus, and the hybrid electric vehicle model computes the state of charge and fuel consumption rate along the road. Finally, The proposed work shows how a hybrid electric vehicle fleet management system has a significant potential to be a solution for public transportation in Egyptian urban areas at this time compared with conventional vehicle and electric vehicle fleet management systems.

OPTIMIZING MICROMOBILITY INFRASTRUCTURE: A COMPREHENSIVE STUDY OF DOCKING, LOCKING, AND CHARGING SOLUTIONS IN METRO CITIES

The surge in micro-mobility options, such as e-scooters and shared bicycles, has transformed urban transportation, providing a sustainable and efficient means for short-distance travel. Despite their benefits, the rapid expansion of these services has unveiled significant infrastructural challenges, particularly concerning docking, locking, and charging systems. This comprehensive study examines these challenges, evaluates existing practices, and proposes optimized solutions to improve the functionality and user experience of micro-mobility in metro cities. Through a detailed analysis of various technologies, their implementation in different cities, and their impact on urban mobility, this research aims to offer actionable insights. Key areas of focus include standardizing docking mechanisms to enhance interoperability, developing robust and user-friendly locking solutions to prevent theft and vandalism, and creating efficient, sustainable charging infrastructure. By studying successful strategies from cities like Paris, New York, and Singapore, the research identifies best practices and common pitfalls. Recommendations emphasize the importance of standardization, integration with public transportation, sustainability, user education, and supportive policies and regulations. The findings of this study aim to guide city planners and micro-mobility service providers in optimizing infrastructure, thereby enhancing the overall efficiency, security, and sustainability of urban transportation networks.

Shaping the future: Improvements in the EV charging Infrastructure: A comparative analysis of Germany and India

The shift towards sustainable transportation has accelerated the deployment of electric vehicles (EVs), demanding advancements in EV charging infrastructure. [1] This thesis, "Shaping the Future: Improvements in EV Charging Infrastructure," explores the critical role of enhancing charging networks to boost EV adoption and usage. It delves into the status, challenges, technological innovations, regulatory frameworks, and evaluates the collective impact on future mobility. In-depth investigations reveal the challenges facing the existing EV charging infrastructure, such as grid capacity limitations, interoperability issues, and regulatory complexities. [2] It also compares global strategies from countries like Germany and India to evaluate the impact of government policies, subsidies, and incentives on infrastructure deployment. The research identifies emerging trends, including wireless charging, bidirectional capabilities, and smart, connected charging stations, emphasizing their potential to revolutionize the EV charging experience. It assesses the economic and environmental sustainability of integrating renewable energy sources into charging networks, as well as the scalability and adaptability of the infrastructure to evolving demands. [3] By synthesizing these findings, the thesis provides insights into future directions for the development of EV charging infrastructure. It offers recommendations for overcoming current barriers, fostering technological innovation, and harmonizing regulations to create a seamless, sustainable, and universally accessible EV charging environment.

Mapping the charging demand for electric vehicles in 2050 from mobility habits

This paper proposes a method to spatially model and compare charging needs on the European scale, considering local disparities in population density, distance to city centres, car ownership and mobility habits. Mobility habits are modelled across Europe in terms of distance and time frame to elaborate scenarios of charging behaviour. The first step of the method is to calculate the density of electric vehicles with a resolution of 1km2, according to the progressive electrification of the fleet each year between 2020 and 2050. The second step is to quantify the mobility of commuters using their driving distance to work areas and mobility statistics. The model is then applied in a case study in Switzerland to plan the public charging infrastructure required to satisfy the charging needs of the local population. Despite lower motorization rates and driving distances, the results show a stronger need for charging in cities. With 50% of commuters charging at work and 20% at home during the workday, the demand in the evening can be reduced by 50% in the suburban areas compared to the baseline scenario in which all commuters are charging at home in the evening. This model can be used to quantify the energy needs of commuters, plan the deployment of the charging infrastructure, or simulate the effect of policies.

Optimization of electric charging infrastructure: integrated model for routing and charging coordination with power-aware operations

With the increasing adoption of electric vehicles (EVs), optimizing charging operations has become imperative to ensure efficient and sustainable mobility. This study proposes an optimization model for the charging and routing of electric vehicles between Origin-Destination (OD) demands. The objective is to develop an efficient and reliable charging plan that ensures the successful completion of trips while considering the limited range and charging requirements of electric vehicles. This paper presents an integrated model for optimizing electric vehicle (EV) charging operations, considering additional factors of setup time, charging time, bidding price estimation, and power availability from three sources: the electricity grid, solar energy, and wind energy. One crucial aspect addressed by the model is the estimation of bidding prices for both day-ahead and intra-day electricity markets. The model also considers the total power availability from the electricity grid, solar energy, and wind energy. The alignment of charging operations with the capacity of the grid and prevailing bidding prices is essential.This ensures that the charging process is optimized and can effectively adapt to the available grid capacity and market conditions. The utilization of renewable energies led to a 42% decrease in the electricity storage capacity available in batteries at charging stations. Furthermore, this integration leads to a substantial cost reduction of approximately 69% compared to scenarios where renewable energy is not utilized. Hence, the proposed model can design renewable energy systems based on the required electricity capacity at charging stations. These findings highlight the compelling financial advantages associated with the adoption of sustainable power sources.

Public Perceptions of EV Charging Infrastructure: A Combined Sentiment Analysis and Topic Modeling Approach

Public Perceptions of EV Charging Infrastructure: A Combined Sentiment Analysis and Topic Modeling Approach

Charging infrastructure assessment for shared autonomous electric vehicles in 374 small and medium-sized urban areas: An agent-based simulation approach

This research examines the use of Shared Autonomous Electric Vehicles (SAEVs) in 374 U.S. small and medium-sized urban areas, focusing on fleet and infrastructure needs through agent-based simulations. It assesses metrics such as fleet size, trips per vehicle, and charging station requirements, considering two charger types: Level 2 and Level 3. The findings show significant spatial differences in SAEV operations and infrastructure across these cities. Statistical analysis links these variations to regional road networks and travel patterns. The study finds Level 3 chargers more efficient, requiring fewer stations and enabling more trips per vehicle compared to Level 2 chargers. Furthermore, Level 3 chargers exhibit a greater number of trips per SAEV and a higher ratio of vehicles to charging stations. These findings highlight the significance of considering charging infrastructure characteristics to optimize SAEV fleet performance and promote sustainable transportation systems in urban areas. This study significantly contributes by identifying the spatial variation and correlates of the SAEVs' operational and charging infrastructural performance. Policymakers, urban planners, and transportation service providers can leverage these insights to design and implement effective charging infrastructure for SAEV fleets, thereby advancing the transition to cleaner and more efficient mobility solutions.

Влияние государственных мер поддержки на развитие рынка электрозарядной инфраструктуры в РФ

Currently, there is a growing awareness worldwide among societies and governments regarding pollution resulting from human activities, raising the issue of climate change. All this, together with other factors, puts a priority theme of environmental friendliness in various areas of the economy, and the field of transport was no exception. The use of vehicles running on alternative fuels and electricity emerges as a pressing agenda. The article examines the development of the charging infrastructure market for electric vehicles, taking into account existing measures to stimulate the electric vehicle market in both Russian and foreign practices. The aim of the study is to systematize the accumulated experience of stimulating demand. Since the electric vehicle market and the charging infrastructure of cities are interrelated, an important task is to identify existing barriers hindering the development of the electric vehicle market in Russia and to investigate support measures. The investment potential of projects for the development of electrical charging infrastructure was assessed, taking into account various forms of support.