Charging Network Research Articles

Towards Sustainable Decarbonization: Addressing Challenges in Electric Vehicle Adoption and Infrastructure Development

The transition to electric vehicles (EVs) plays a pivotal role in achieving decarbonization within the transportation sector. However, the widespread adoption of EVs faces multifaceted challenges, particularly concerning infrastructure development. This paper investigates the intersection of sustainability, decarbonization, and EV adoption, with a focus on identifying and analyzing the challenges associated with infrastructure deployment. Strictly adhering to the methodological principles and process of systematic literature reviews, this paper analyzes research spanning the fields of engineering, energy, computer science, environmental science, social sciences, and others to elucidate the barriers hindering EV adoption, ranging from technological limitations to regulatory complexities and market dynamics. Furthermore, it examines the critical role of infrastructure, encompassing charging networks, grid integration, and supportive policies, in facilitating EV uptake and maximizing environmental benefits. The findings are finally used to present the implications for theory, practice, and policies and to highlight the avenues for future research.

The Art of Balancing Price and Plug: Developing a Theoretical Model for Dynamic Pricing in the Electric Vehicle Market

This study presents a novel approach to understanding the complex dynamics of the electric vehicle (EV) market through the lens of differential game theory. We developed a comprehensive model that captures the strategic interactions between EV manufacturers and charging network operators, while incorporating the effects of consumer behavior, market uncertainties, and reference price effects. Using differential game theory, we examined the impact of reference price effects and the charging network’s influence on pricing strategies, focusing on three distinct approaches: basic pricing, static pricing considering reference price effects, and dynamic pricing strategies. Our model offers new insights into consumer behavior and price expectations in the rapidly evolving EV market. The key findings reveal that under static or dynamic pricing strategies, the optimal pricing for EV manufacturers is positively correlated with the initial reference price. When the initial reference price is high (low), the optimal pricing strategy resembles skimming pricing (penetration pricing). As the effort level of charging network operators increases and their influence on consumers’ purchase decisions grows stronger, EV manufacturers tend to set higher prices. Notably, while dynamic pricing strategies can optimize EV manufacturers’ profits, the profits of charging network operators may decrease compared with static pricing strategies. This integrated approach significantly contributes to the field by bridging gaps among market dynamics, pricing strategies, and the infrastructure’s development in the context of electric mobility, providing a comprehensive framework for understanding and optimizing the EV ecosystem. Ultimately, this study advances sustainable business models that balance profitability, consumer behavior, and the infrastructure’s growth in the rapidly evolving EV market.

Optimized demand-based charging networks for long-haul trucking in Europe

Abstract Battery electric trucks (BETs) are the most promising option for fast and large-scale CO2 emission reduction in road freight transport. Yet, the limited range and longer charging times compared to diesel trucks make long-haul BET applications challenging, so a comprehensive fast charging network for BETs is required. However, little is known about optimal truck charging locations for long-haul trucking in Europe. Here we derive optimized truck charging networks consisting of publicly accessible locations across the continent. Based on European truck traffic flow estimates for 2030 and actual truck stop locations we construct a long-term charging network that minimizes the total number of required locations. Our approach introduces an origin-destination pair sampling method and includes local capacity constraints to compute an optimized stepwise network expansion along the highest demand routes in Europe. For an electrification target of 15% BET share in long-haul and without depot charging, our results suggest that about 91% of electric long-haul truck traffic across Europe can be enabled already with a network of 1,000 locations, while 500 locations would suffice for about 50%. We furthermore show how the coverage of origin-destination flows scales with the number of locations and the size of the stations. Ideal locations to cover many truck trips are at highway intersections and along major European road freight corridors (TEN-T core network).

Adaptive Multi-Agent Reinforcement Learning for Optimizing Dynamic Electric Vehicle Charging Networks in Thailand

The rapid growth of electric vehicles (EVs) necessitates efficient management of dynamic EV charging networks to optimize resource utilization and enhance service reliability. This paper explores the application of adaptive multi-agent reinforcement learning (MARL) to address the complexities of EV charging infrastructure in Thailand. By employing MARL, multiple autonomous agents learn to optimize charging strategies based on real-time data by adapting to fluctuating demand and varying electricity prices. Building upon previous research that applied MARL to static network configurations, this study extends the application to dynamic and real-world scenarios, integrating real-time data to refine agent learning processes and also evaluating the effectiveness of adaptive MARL in maximizing rewards and improving operational efficiency compared to traditional methods. Experimental results indicate that MARL-based strategies increased efficiency by 20% and reduced energy costs by 15% relative to conventional algorithms. Key findings demonstrate the potential of extending MARL in transforming EV charging network management, highlighting its benefits for stakeholders, including EV owners, operators, and utility providers. This research contributes insights into advancing electric mobility and energy management in Thailand through innovative AI-driven approaches. The implications of this study include significant improvements in the reliability and cost-effectiveness of EV charging networks, fostering greater adoption of electric vehicles and supporting sustainable energy initiatives. Future research directions include enhancing MARL adaptability and scalability as well as integrating predictive analytics for proactive network optimization and sustainability. These advancements promise to further refine the efficacy of EV charging networks, ensuring that they meet the growing demands of Thailand’s evolving electric mobility landscape.

Why is Tesla’s Business model so effective and what can they adapt to improve it?

The electric vehicle (EV) revolution is gaining momentum and Tesla is playing a key role in promoting environmentally friendly transport. However, Tesla faces challenges in expanding its charging infrastructure, which lags behind its competitors. Currently, Tesla has about 16.8 thousand to 17.7 thousand chargers in the US, while competitors such as Chargepoint offer about 34 thousand chargers. As the increase in the use of electric vehicles is estimated to reach 28.3 million vehicles by 2030, the charging network urgently needs to be improved. S\&P Global Mobility recommends a fourfold increase in charging points, especially Level 2 and Level 3 chargers, between 2022 and 2025 to meet growing demand. Tesla has two main options: collaborate with other companies to create a more interconnected network or continue to build its stations. The development of Tesla's Magic Dock technology, which allows other electric vehicles to use Tesla's chargers, marks progress, but also brings challenges, such as compatibility issues due to cable length. Tesla must address these concerns to ensure that its charging network keeps pace with rapid EV growth and supports a wider range of EVs.

Towards full electrification of local public transport: A tool to guide strategies for implementing the electric charging network

This paper describes a methodology and a Decision Support Tool (DST) for the assessment of the impacts of future scenarios of public electric mobility on the electric Distribution Network (DN) of a city, aimed to support the implementation strategies of the electric charging network for the Local Public Transport (LPT).The objective of the proposed tool is supporting the decision makers in estimating the effect of the future development of electromobility on the urban electric grid considering the evolution of both electric buses and their charging infrastructure.Some scenarios for the development of electric charging infrastructure for LPT were identified together with the local public transport operator and the energy provider. The results, which are of interest to both the local Public Transport Operator (PTO) and the local Distribution System Operator (DSO), have been quantified for the city of Turin (Italy), but the methodology can be adopted in any urban context: DSOs and PTOs of each city can use the proposed tool as a support to define their public transport electrification strategies.Some results from the case study examined in this paper (Turin, Italy) show that the energy demand related to the electrification of LPT on a typical weekday is about 45 MWh in 2030 (corresponding to 40 % e-bus), and about 90 MWh when the entire bus fleet is electric. It is also shown how more distributed recharging during the day (with intermediate recharging at the terminus) can dampen the energy/power peaks required at the depot compared to overnight recharging alone: a reduction of up to 27 % of energy demand at the depot is observed due to opportunity charging.

ADDRESSING INFRASTRUCTURE GAPS IN MUMBAI’S 2-WHEELER EV CHARGING NETWORK: A FOCUS ON ACCESSIBILITY, USABILITY, AND USER FEEDBACK

Electric vehicles (EVs) are transforming transportation in Mumbai, with 2-wheeler EVs gaining significant traction among commuters. However, the insufficient availability and accessibility of charging infrastructure remain critical challenges. This study investigates the experiences of 2- wheeler EV users in Mumbai, focusing on the barriers they encounter when charging their vehicles. Given Mumbai’s dense traffic and urban complexities, limited charging points, long waiting times, and infrastructural constraints can hinder the user experience and discourage further adoption of EVs. The findings provide key insights into optimal charging station locations based on a comprehensive analysis of population density, traffic flow, and urban planning frameworks. Additionally, the study addresses the need for standardized charging protocols, advanced technologies, and user-friendly interfaces to enhance the usability of charging stations. The study emphasizes that addressing these challenges is crucial not only for the user experience but also for policymakers, urban planners, and stakeholders aiming to expand Mumbai’s EV infrastructure. Moreover, the environmental benefits of 2-wheeler EV adoption are examined, including reductions in energy consumption, carbon emissions, and overall environmental impact. By analyzing these factors, the research highlights the positive environmental outcomes of investing in robust charging infrastructure. Key challenges, such as high costs, feasibility concerns, and policy limitations, are also explored, offering a holistic understanding of the practical barriers to improving the EV charging network. The study concludes with actionable recommendations aimed at overcoming these challenges, fostering sustainable growth, and ensuring the efficient deployment of 2-wheeler EV charging infrastructure across Mumbai.

The accessibility of public electric vehicle (EV) charging infrastructure: Evidence from the cities of Nottingham and Frankfurt

AbstractThe distribution of public electric vehicle (EV) charging infrastructure is a widespread approach for promoting EV adoption and decarbonising transportation. A significant amount of literature explores the distribution of EV charging points at a country scale, but there is a lack of studies focusing on a district scale. This study aims to contribute to this gap by gaining insights into the distribution of EV charging points per district within cities, such as Nottingham and Frankfurt. The study investigates the current distribution of EV charging points across 38 postcode districts in Frankfurt and 9 postcode districts in Nottingham, using geographical data analysis and a linear regression approach. The following factors in response to the number of EV charging points per postcode district (ZIP code) are examined: the percentage of apartment buildings/floor area ratio, the availability of amenities, population, charging capacity (kW), area size, strategic approaches, including policy goals and principles. The results reveal disparities in access to EV charging infrastructure across districts and underscore the importance of expanding EV charging networks not only in districts located near urban centres or those with high availability of amenities but also ensuring that users without home charging options are not left behind.

A Novel Charging Management and Security Framework for the Electric Vehicle (EV) Ecosystem

The EV charging network has witnessed significant growth in the UK in the last few years due to the net zero emission target of the government by 2030. The related literature in EV charging management mainly focuses on road-traffic-parameter-based optimization and lacks detail in terms of charging statistics and cyber–security-enabled charging management frameworks. In this context, this paper proposes a novel EV Charging Management and Security (EVCMS) framework using real-time charging statistics and an Open Charge Point Protocol (OCPP). Specifically, a system model for EVCMS is presented considering charging data management and security protocols. An EVCMS framework design is detailed, focusing on charging pricing, optimization, and charging security. The experimental implementation is described in terms of client–server and charge-box-based simulation. The performance of the proposed EVCMS framework is evaluated by considering different charging scenarios and a range of charging-related metrics. An analysis of results and comparative study attest to the benefits of the proposed EVCMS framework for enabling the EV charging ecosystem.

Measuring the effectiveness of incorporating mobile charging services into urban electric vehicle charging network: An agent-based approach

Mobile charging service (MCS) has emerged as a cost-efficient solution to compensate for the limitations of fixed charging stations (FCSs) in service capacity and coverage. Nevertheless, the impacts of incorporating the MCS into the charging infrastructure network have not been well understood. Therefore, this study introduces an exhaustive framework for devising Agent-based Modeling (ABM) to delineate electric vehicle (EV) drivers' daily travels and charging behaviors within the integrated charging network. Specifically, the developed ABM framework encompasses both internal attributes of individuals and external variables of charging and transport networks that potentially shape EV drivers’ public charging decisions. It generates authentic daily charging demands for FCSs and MCSs and provides a streamlined process to further incorporate more charging modes into the EV charging ecosystem. Subsequently, we opted for the Salt Lake City metropolitan area to implement our framework and showcase the effectiveness of MCS integration on the charging network over various EV adoption levels and network settings. The findings of the designed case study unravel the choice patterns of EV drivers when facing diverse charging options and pinpoint the strengths and weaknesses of MCS incorporating into the urban charging network at different stages.

Assessment of Economic Viability of Direct Current Fast Charging Infrastructure Investments for Electric Vehicles in the United States

As the global transportation sector increasingly adopts electric vehicles, the demand for advanced and accessible charging infrastructure is rising. In addition to at-home electric vehicle (EV) charging, there is a growing need for the swift development of commercial direct current fast charging (DCFC) stations to meet on-the-go EV charging demands. While government funds are available to support the expansion of the EV charging network in the United States, the establishment of a robust nationwide EV charging infrastructure requires significant private sector investment. This study was conducted to assess the economic feasibility of various business models for fast charging stations in the U.S. using two case studies and exploring different operational strategies including sole ownership and collaborative ventures with public and private entities. The results indicate that based on the current adoption and utilization rates in the U.S., the business model involving an owner-operator collaborating with a public partner ensures profitability and protects the investment in DCFC stations from financial losses. The study also highlights that demand charges and electricity retail prices are the factors that affect the profitability of a DCFC station.

Innovative Solutions, Green Initiatives for Sustainable Economic - The Hungarian Example

Green development has become a major goal for most world powers and is taking an increasingly prominent place in the global economy, with China and Europe being no exception. Both have set green growth as a goal to achieve carbon neutrality in the coming years. As the green economy is now global, cooperation is essential to improve quality of life everywhere. Chinese experts are helping to green Hungary's transition taking part in the Hungarian energy economy. The relationship between the two countries has been dominant for centuries, but until recently it needed to be redefined. The Chinese President in 2024 visited Hungary and met the Prime Minister and the Hungarian Head of State. Within the framework of the One Belt, One Road strategy, the two countries have drawn up an expanding list of projects for joint investment and development. The summit between the two countries delivered results, with the parties signing eighteen important agreements. Hungarian experts collaborate with Chinese partners on clean energy, sustainable energy production and green technology innovation. In a summary, the agreement covers cooperation in nuclear research and development, training, the expansion of the electric car charging network, and the exploration of the possibility of jointly connecting the domestic and Serbian oil pipeline systems. In our research, we explore areas for further cooperation between China and Hungary, identifying key areas of mutual benefit and common interest.

Novel Methodology to Measure the Reliability of Public DC Fast Charging Stations

A network of reliable corridor charging stations is essential to building driver confidence in long-distance battery electric vehicle trips. Here, we propose a detailed methodology to measure station reliability based on charging infrastructure data. By assigning charging events to unique charging visits, our methodology can capture a holistic overview of the driver’s charging experience. We use real world charging data collected between 2019 and 2022 from 54 Direct Current Fast Chargers (DCFCs) in 36 corridor charging stations across California to demonstrate that our overarching reliability framework is close to the experience of users. Our analysis of two different charging networks shows that users of these networks have an average chance of 83% and 77% generally successful outcomes, respectively, after one or more tries at a charging station location. We also find significant variation in station performance within the same network (i.e., 79%–87% and 13%–95%, respectively). Furthermore, we observe that at least 3% of users are facing unexpected charging interruptions. In addition, we demonstrate a practical application of our framework for deep diagnostics of the charging eco-system using error codes to identify common issues such as vehicle/charger communication issues, safety issues, payment issues, and cable/connector issues. We compare how error codes alone are not a good proxy to diagnose charging failures. As more data from DCFCs becomes available, our methodology can become a mainstream tool for evaluating station reliability.

FACTORS AFFECTING THE ADOPTION OF ELECTRIC VEHICLES BY PUBLIC SERVICE VEHICLE OPERATORS IN KENYA

This research investigates the factors influencing the adoption of electric vehicles (EVs) among public service vehicle operators in Kenya. The study employs a descriptive survey design, encompassing 212 public vehicle operators in the country. The primary objectives include assessing the impact of cost, infrastructure development, knowledge, and social-cultural factors on the adoption of EVs by public service vehicle operators in Kenya. The study conducted in-depth interviews and focus group discussions with a selected subset of participants to gain deeper insights into the qualitative aspects of the study. The study reveals that cost, infrastructure development, knowledge, and social-cultural factors collectively influence the adoption landscape. High upfront costs and operational expenses pose significant barriers, emphasizing the need for financial incentives and supportive policies to make EVs more economically viable. Infrastructure development, particularly the establishment of a robust charging network, is crucial to alleviate range anxiety and enhance the practicality of EVs. Knowledge gaps among operators highlight the importance of educational programs and training initiatives to enhance understanding and promote the benefits of electric vehicles. Social-cultural factors, such as attitudes and perceptions, also shape adoption patterns, emphasizing the need for awareness campaigns to address misconceptions. In conclusion, a comprehensive strategy involving financial incentives, infrastructure development, knowledge dissemination, and cultural sensitization is recommended to foster the widespread adoption of electric vehicles in Kenya's public service transportation sector

Decoding tourist perceptions and behavioral intentions to use electric vehicles for sustainable tourism with the lens of technology continuance theory

Purpose This study aims to explore tourist perceptions and behaviors toward electric vehicles (EVs) in the Delhi National Capital Region using the technology continuance theory. Design/methodology/approach An online survey involving 226 respondents uses structural equation modeling to analyze correlations among factors, including perceived enjoyment, facilitating conditions, ease of use, satisfaction, cost, image and performance. Findings This study reveals that enhancing perceived enjoyment and facilitating conditions can improve the user-friendliness of EVs. Additionally, reducing perceived cost, enhancing image and improving perceived performance can increase the perceived usefulness of EVs. Perceived ease of use strongly influences user satisfaction, while perceived usefulness and satisfaction positively impact users’ attitudes and intentions to use EVs. Although factors such as experience, environmental consciousness, age and gender influence perceptions, focusing on enjoyment, facilitating conditions, cost, image and performance can significantly enhance user satisfaction and intention to use EVs. Research limitations/implications The findings underscore several actionable recommendations for businesses and policymakers to boost EV adoption at tourist destinations. The potential benefits of EV adoption, such as improved environmental sustainability, enhanced technological image and increased tourist satisfaction, can serve as a source of inspiration and motivation. Enhancing user experience by prioritizing comfort and convenience in EV design is crucial. Addressing cost concerns through incentives and cost-effective pricing strategies can make EVs more appealing. Marketing campaigns highlighting environmental benefits and technological advancements can improve EV image and performance perception. Prioritizing tourists’ satisfaction and support services is essential, along with educational campaigns to increase awareness. Infrastructure development, including expanding charging networks, and supportive policies like tax incentives, can further encourage EVs adoption, accelerating the transition to sustainable transportation. Originality/value This research contributes to understanding tourist perspectives on EV adoption within the context of sustainable tourism and technology 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.

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.

Meeting the charging demand of Electric Vehicles in Greece: Enabling intercity trips

The increasing need for sustainable transportation has underscored the pivotal role of electric mobility in shaping the future of mobility. Electric Vehicles (EVs) have emerged as a promising solution, but their widespread adoption is contingent upon the availability of a reliable charging network. This challenge extends even to EV adoption pioneers like Norway and China. This study delves into the context of EV adoption in Greece, providing insights into the EV market, existing incentives, and the state of charging infrastructure. Reports indicate that Greece is at a critical juncture, with fast EV adoption but sluggish development of Charging Stations (CSs). To address this issue, a Monte Carlo simulation is employed to evaluate the feasibility of long-distance EV trips in Greece and propose an infrastructure development plan. For EVs, the study reveals a linear relationship between battery size and autonomy, with some exceptions emphasizing the importance of data acquisition and individual EV assessment. The study also provides insights into the relationship between trip length and energy consumption, indicating that longer trips exhibit greater fluctuation in energy consumption due to varying conditions, while energy usage patterns of shorter trips are more predictable. Additionally, the analysis presents average energy consumption values for each EV model in different temperature conditions, highlighting the impact of environmental factors on EV performance.

Green Wheels, Greener Wallets: Economic Viability of Last-Mile Delivery Fleet Electrification in Case of Latvia

The analysis of internal combustion engine vehicle (ICEV) usage habits in the DPD Latvija company and the study of the specifics of its last-mile delivery transport business will allow to understand whether electromobility solutions can make the company more efficient. The question addressed in the research is whether the electrification of the delivery vehicle fleet can reduce transport expenses for the company and under what conditions. For estimation of direct and indirect costs of transport acquisition and usage Total Cost of Ownership (TCO) is used. The company’s daily operation parameters and technical data of the used vehicles VW e-Crafter and VW Crafter 35 Kasten/long base are considered in the study. Net Present Value (NPV) and Internal Rate of Return (IRR) calculation methods are used for analyzing the investment project. The expense of the creation of electrical vehicle charging infrastructure is not considered, because the company’s daily routine allows to cover all charging processes overnight by using domestic sockets together with Mode 2 chargers. All technical data and calculations were made for deliveries in a city cycle. In financial terms of owning delivery transport, the company is using a 5-year operational lease with 0% first payment. The obtained results in terms of TCO comparison showed a slight advantage by using EV after 5 years of last-mile delivery service per 1 vehicle – 706.98 Euro at 31200km a year or 100km in the working day of 6-day working week (156000km in 5-year is under 160000 warranty condition). The calculation is performed for DPD Latvija 213 ICE vans of a total 240-vehicle fleet. Results of NPV, NPVI, and IRR with a comparison rate of 10.6% for EV case clearly show a sufficiently good return. The Net Present Value of the solution is 89271.92 Euro and the Internal rate of return is 48.05%. The study proves that the electrification of the last-mile delivery company's fleet is economically justified and within 5 years. In the process of electrification, the company will reduce its expenses – by 1.45%, which increases the net annual profit by 0.13%. The main conclusion is that the company will not incur losses by switching to an environmentally friendly vehicle, the capital investment in a realistic scenario pays off already from the 3rd year. Nevertheless, the authors of the study recommend evaluating delivery vehicles with higher driving range parameters, because during peak delivery and seasons with cold weather, the company may experience unplanned downtime and expenses due to the need for additional charging time at public charging networks on the road, that could lead to financial losses and need for TCO calculation corrections.

Joint Path Selection, Energy Trading, and Task Offloading in Electric Vehicle Charging and Computing Network

Joint Path Selection, Energy Trading, and Task Offloading in Electric Vehicle Charging and Computing Network