Charging Service Research Articles

E-Fuel: An EV-Friendly Urgent Electrical Charge-Sharing Model with Preference-Based Off-Grid Services

Electric-powered vehicles (EVs) allow for an environmentally friendly and economic alternative to fuel-running ones. However, such an alternative is expected to impose further usage hikes and periods of instability on cities’ power systems. From their perspective, cities need to scale their infrastructure grids to allow for adequate power resources to feed such new power-hungry consumers. Indeed, for such a green alternative to proceed, our power grids need to be ready to cope with any unexpected hikes in the power consumption rates without compromising the stability of the services provided to our homes and workplaces. Operators’ steps in this path are still modest, and the coverage of EV charging stations is still insufficient as they are trying to avoid any further costs for upgrading their infrastructures. The lack of price consideration for the charging services offered at charging stations may result in EV drivers paying higher costs compared to traditional fuel vehicles to charge their EVs’ batteries, hindering the economic incentive of owning such sorts of vehicles. Hence, it may take a while for sufficient coverage to exist. Although for drivers the adoption of EVs represents a city-friendly alternative with affordable expenses, it usually comes with range anxiety and battery charging concerns. In this work, we are presenting e-Fuel, a charge-sharing model that allows for preference-based mobile EV charging services. In e-Fuel, we are proposing a stable weight-based vehicle-to-vehicle matching algorithm, through which drivers of EVs will be capable of requesting instant mobile charge-sharing service for their EVs. In addition to being mobile, such charging services are customized, as they are chosen based on the drivers’ preferences of price-per-unit, charging speed, and time of delivery. The developed e-Fuel matching algorithm has been tested in various environments and settings. Compared to the benchmark price-based matching algorithm, the resulting matching decisions of e-Fuel come with balanced matching attributes that mostly allow for 6- to 7-fold shorter service delivery times for a minimal increase in service charges that vary between 9% and 65%.

User Sentiment Analysis of the Shared Charging Service for China’s G318 Route

Shared charging services have gained popularity for their contribution to green travel. Accurately identifying the core factors that influence user experience (UX) not only enhances service quality and optimizes user satisfaction, but also promotes the dissemination of green travel concepts. However, the influencing factors and their mechanisms vary significantly across regions, particularly along the Chengdu–Lhasa (G318) route, which features large elevation changes, diverse climatic conditions, rugged terrain, and frequent geological disasters, making the influencing factors particularly complex. This study analyzes comment texts from 38 shared charging stations along the G318 route in the e-Charging APP, totaling 15,214 comments. A comprehensive approach is employed, including high-frequency word analysis, term frequency–inverse document frequency (TF-IDF) comparison, co-occurrence semantic network and co-word matrix feature correlation analysis, Latent Dirichlet Allocation (LDA) topic modeling, and sentiment analysis. This multifaceted analysis explores core themes, user viewpoints, and sentiments in the comments, focusing on users’ perspectives on service quality, usage experience, and environmental impact of the charging stations. The findings indicate that charging speed, service attitude, environment, operational status of hardware and software, and pricing are key factors influencing user sentiment. Users have a high demand for the perfection of supporting facilities of shared charging stations, directly affecting user satisfaction and indirectly influencing the brand image and market competitiveness of enterprises.

Hierarchical Optimal Dispatching of Electric Vehicles Based on Photovoltaic-Storage Charging Stations

Electric vehicles, known for their eco-friendliness and rechargeable–dischargeable capabilities, can serve as energy storage batteries to support the operation of the microgrid in certain scenarios. Therefore, photovoltaic-storage electric vehicle charging stations have emerged as an important solution to address the challenges posed by energy interconnection networks. However, electric vehicle charging loads exhibit notable randomness, potentially altering load characteristics during certain periods and posing challenges to the stable operation of microgrids. To address this challenge, this paper proposes a hierarchical optimal dispatching strategy based on photovoltaic-storage charging stations. The strategy utilizes a dynamic electricity pricing model and the adaptive particle swarm optimization algorithm to effectively manage electric vehicle charging loads. By decomposing the dispatching task into multiple layers, the strategy effectively solves the problems of the “curse of dimensionality” and slow convergence associated with large numbers of electric vehicles. Simulation results demonstrate that the strategy can effectively achieve peak shaving and valley filling, reducing the load variance of the microgrid by 24.93%, and significantly reduce electric vehicle charging costs and distribution network losses, with a reduction of 92.29% in electric vehicle charging costs and 32.28% in microgrid losses compared to unorganized charging. Additionally, this strategy can meet the travel demands of electric vehicle owners while providing convenient charging services.

Nitrogen doped TIO2/g-C3N4 nanocatalyst for photodegradation of methylene blue dye

In this study, the ethanol dispersion procedure was implemented to prepare the g-C3N4/N–TiO2 nanocatalyst structure. Sol-gel synthesis is utilized for synthesizing N–TiO2 and g-C3N4 via urea thermal decomposition. Physicochemical properties of produced photocatalysts were revealed using PL imaging, UV–vis DRS, XRD, FTIR, SEM, BET, and TEM. Evaluation of photocatalytic activity of synthetic photocatalysts by exposure to sunlight and degradation of methylene blue (MB) dye. g-C3N4/N–TiO2 NCs showed excellent photocatalytic activity, reaching 96 % MB degradation efficiency in 80 min. g-C3N4 and N–TiO2 doped form a nanocomposite structure that increases photocatalytic activity, affecting charge separation performance and service life. The system also exhibits the ability to collect visible and ultraviolet light. Even after four consecutive cycles, the efficiency of the MB is still above 85 %. Capture experiments showed that the decomposition of MB was mainly caused by h+ and O22− radicals. The results of kinetic investigations indicate that the degradation rate of g-C3N4/N–TiO2 nanocomposites surpasses that of N–TiO2 nanoparticles.

Empirical Research on the Impact of Technological Innovation on New Energy Vehicle Sales

In the context of global carbon peak and carbon neutrality goals, researching the driving forces and influencing factors behind the growth in sales of new energy vehicles (NEVs) is particularly urgent and crucial. Although the academic community has extensively explored various factors affecting NEV sales, technological innovation, as the core engine driving industry progress, is yet to receive sufficient and in-depth exploration regarding its potential profound impact on sales. Therefore, this study thoroughly analyzes the mechanism by which technological innovation influences sales, supplementing the existing literature, exploring sustainable industry development, and guiding the optimization of business strategies and precise government policies. This research employs the quality of NEV technology patents as a proxy variable for technological innovation, and conducts an empirical analysis using China’s NEV sales data from 2015 to 2022. The results of the study show the following: (1) the quality of technological innovation significantly contributes to the growth of new energy vehicle sales. This conclusion still holds when the administrative protection of intellectual property rights and the government’s public innovation environment indicators are used as instrumental variables of technological innovation quality. (2) Technological innovations in different links of the new energy vehicle industry chain have a positive impact on sales, especially those in the midstream battery, motor, and downstream charging services. This shows that in the critical period of new energy vehicle development, not only is the breakthrough of key technologies crucial, but also, non-critical technologies can promote sales growth by improving user experience and product performance. (3) Compared with plug-in hybrid electric vehicles (PHEVs), the overall technological innovation of new energy vehicles (NEVs) has a more significant effect on the sales of battery electric vehicles (BEVs). (4) In addition, the study finds that there is no significant difference between high-quality and low-quality technological innovations on the promotion of new energy vehicle sales, which indicates that the market values the overall effect of technological innovations more than the mere level of quality. The study of the impact of technological innovation on sales in different branches of the new energy industry chain can help to clarify the direction of technological innovation, optimize resource allocation, promote the synergistic development of the industry chain, enhance market competitiveness, and provide a scientific basis for policy formulation.

Wi-Fi station & Solar Powered Smart-phone Chargers with a Money Multi Coin Selector

The main aim of this study is to present a Wi-Fi station and smart-phone chargers with a money multi coin selector operated through solar energy. Specifically, this study aimed to achieve the following objectives: 1) Determine a solar panel that is appropriate for providing power for a phone charging station. 2) Determine a suitable timing system for providing mobile phone charging services. 3) Determine the acceptability of the device based on the following: a) Physical features; b) Cost; c) Durability; d) Operation. This device is mainly aimed for commercial use since it can require a certain fee for a specified period to charge a mobile phone. It makes possible to highlight two principles of environmental conservation and green economy (using the solar PV) as well as the opening of the workstation.

Sunfuel Electric: charting a differentiated go-to-market-strategy in the EV charging space

Learning outcomes After completion of the case study, students will be able to understand the service offerings within the nascent electric vehicle (EV) sector and end-consumer needs of EV charging services, understand the reasoning behind Sunfuel Electrics (SFEs) prioritisation of destination charging for their first go-to-market (GTM) strategy and appreciate SFE’s use of community marketing and alliance partners to execute its various strategies. Connect game-theory with the proposed strategies. Case overview/synopsis SFE was an early start-up in EV charging space. The co-founders believed that any success would hinge on their ability to play a differentiated game and carve a distinct yet profitable niche in the EV charging arena. SFE deliberately focussed on “destination charging” and identified a segment that they were confident of making a difference: the discerning high-end consumer. Soon, SFE’s success caught the eye of its deep-pocketed competitors who also entered the same space. As a single service company, the co-founders set in motion a back-up plan and identified three new strategic thrust areas to maintain SFE’s competitive edge. The first involved entering the city charging segment, and the second was a pioneering concept branded “E-Trails” targeted at a community of EV owners who were motor enthusiasts. Thirdly, SFE conceptualised an EV-Roadhouse concept, promising a full-bouquet of select premium services at a pit-stops along the highway. The co-founders needed to test which and to what extent would these initiatives would translate into real gains and if returns were commensurate with investments and SFE’s ability to deliver a scalable consistent experience. Specifically, if these proposed asset-light avenues added the required heft to their GTM strategy. Complexity academic level This case study is suitable for post-graduate students in marketing, strategy, entrepreneurship and sustainability courses. Supplementary materials Teaching notes are available for educators only. Subject code CSS 8: Marketing.

Dynamic in‐motion wireless charging systems: Modelling and coordinated hierarchical operation in distribution systems

AbstractThe high adoption of electric vehicles (EVs) and the rising need for charging power in recent years calls for advancing charging service infrastructures and assessing the readiness of the power system to cope with such infrastructures. This paper proposes a novel model for the integrated operation of dynamic wireless charging (DWC) and power distribution systems offering charging service to in‐motion EVs. The proposed model benefits from a hierarchical design, where DWC controllers capture the traffic flows of in‐motion EVs on different routes and translate them into estimations of charging power requests on power distribution system nodes. The charging power requests are then communicated with a central controller that monitors the distribution system operation by enforcing an optimal power flow model. This controller coordinates the operation of distributed energy resources to leverage charging power delivery to in‐motion EVs and mitigate stress on the distribution system operation. The proposed model is tested on a test distribution system connected to multiple DWC systems in Salt Lake City, and the findings demonstrate its efficiency in quantifying the traffic flow of in‐motion EVs and its translation to charging power requests while highlighting the role of distributed energy resources in alleviating stress on the distribution system operation.

When Climate Mitigation Meets the Needs of Adaptation: Closing the Resilience Gap for EV Charging Services in Hurricane-Prone Areas

When Climate Mitigation Meets the Needs of Adaptation: Closing the Resilience Gap for EV Charging Services in Hurricane-Prone Areas

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.

How do supply- and demand-side dynamics and subsidies affect the prospects for electric vehicle battery swapping services? Evidence from an evolutionary analysis

The growing adoption of electric vehicles has highlighted the challenges associated with charging services. Slow charging has proven insufficient to address users’ concerns about range anxiety, and the constraints within the power grid have impeded the expansion of fast charging infrastructure. Battery-swapping services have emerged as a potential resolution to this predicament. Despite government efforts to promote the advancement of battery-swapping services, the market’s future remains to be determined. This study develops a network-based three-decision evolutionary game model to analyze the diffusion of battery-swapping services, considering subsidies along with supply- and demand-side dynamics. The result shows that: (1) Battery-swapping services win out in performance, and Charging Station (CS) only providing charging service will be gradually squeezed out by Battery Swapping Station (BSS) and Battery Charging-Swapping Station (BCSS). (2) It is more effective to subsidize station builders than users. Besides, avoiding over-subsidizing to prevent wastage and providing long-term subsidies for station builders are recommended, while user subsidies can be gradually phased out. (3) The charging/battery-swapping service price in the early stage exhibits a U-shaped effect on the decline of CS market share. (4) Proactively promoting the benefits of battery-swapping services can be a nudge.

A DQN based approach for large-scale EVs charging scheduling

This paper addresses the challenge of large-scale electric vehicle (EV) charging scheduling during peak demand periods, such as holidays or rush hours. The growing EV industry has highlighted the shortcomings of current scheduling plans, which struggle to manage surge large-scale charging demands effectively, thus posing challenges to the EV charging management system. Deep reinforcement learning, known for its effectiveness in solving complex decision-making problems, holds promise for addressing this issue. To this end, we formulate the problem as a Markov decision process (MDP). We propose a deep Q-learning (DQN) based algorithm to improve EV charging service quality as well as minimizing average queueing times for EVs and average idling times for charging devices (CDs). In our proposed methodology, we design two types of states to encompass global scheduling information, and two types of rewards to reflect scheduling performance. Based on this designing, we developed three modules: a fine-grained feature extraction module for effectively extracting state features, an improved noise-based exploration module for thorough exploration of the solution space, and a dueling block for enhancing Q value evaluation. To assess the effectiveness of our proposal, we conduct three case studies within a complex urban scenario featuring 34 charging stations and 899 scheduled EVs. The results of these experiments demonstrate the advantages of our proposal, showcasing its superiority in effectively locating superior solutions compared to current methods in the literature, as well as its efficiency in generating feasible charging scheduling plans for large-scale EVs. The code and data are available by accessing the hyperlink: https://github.com/paperscodeyouneed/A-Noisy-Dueling-Architecture-for-Large-Scale-EV-ChargingScheduling/tree/main/EV%20Charging%20Scheduling.

Dynamic Operations of a Mobile Charging Crowdsourcing Platform

This paper investigates the operation of a novel electric vehicles (EVs) charging service mode, that is, crowdsourced mobile charging service for EVs, whereby a crowdsourcing platform is established to arrange suppliers (crowdsourced chargers) to deliver charging service to customers’ electric vehicles (parked EVs) at low-battery levels. From the platform operator’s perspective, we aim to determine the optimal operation strategies for mobile charging crowdsourcing platforms to achieve specific objectives. A mathematical modeling framework is developed to capture the interactions among supply, demand, and service operations in the crowdsourced mobile charging market. To design an efficient solution method to solve the formulated model, we first analyze the model properties by rigorously proving that a crucial variable set for operating the mobile charging crowdsourcing system includes charging price, commission control, and period-specific aggregate demand control. Besides, we provide both an equivalent condition and a necessary condition for checking the feasibility of these crucial variables. On top of this, we construct a search tree according to the operation periods in a day to solve the optimal operation strategies, wherein a nondominated principle is adopted as an accelerating technique in the searching process. The solution obtained from the proposed solution algorithm is proved to be sufficiently close to the actual global optimal solutions of the formulated model up to the resolution of the discretization scheme adopted. Numerical examples provide evidence verifying the model’s validity and the solution method’s efficiency. Overall, the research outcome of this work can offer service operators structured and valuable guidelines for operating mobile charging crowdsourcing platforms. Funding: This work was supported by the Singapore Ministry of Education [Grant RG124/21]. Supplemental Material: The online appendices are available at https://doi.org/10.1287/trsc.2023.0126 .

A two-sided equilibrium model of Vehicle-to-Vehicle charging platform

A novel mobile charging service utilizing vehicle-to-vehicle (V2V) charging technology has been proposed as a complement to fixed charging infrastructure (CI), enabling electric vehicles (EVs) to exchange electricity. This study develops a two-sided equilibrium model for a V2V charging platform, where the demand-side charging vehicles (CVs) choose between charging piles and the V2V platform, and the supple-side discharging vehicles (DVs) decide whether to provide discharging services. The V2V platform matches CVs with DVs, receiving compensation from CV owners and reimbursing DV owners. To explore the strategic interactions between the V2V platform and fixed CI operators, we construct an analytical bi-level model that examines different operation regimes, including competitive and cooperative scenarios, i.e., non-cooperative game and Nash Bargaining game. The lower-level model is a two-sided equilibrium model that quantifies charging and discharging choices of EV owners, while the upper-level model optimizes the pricing decisions of the V2V platform and fixed CI operator. Numerical results indicate that the introduction of the V2V platform can reduce the overall charging costs, thus encourage the use of public charging services. Furthermore, it is suggested that the V2V platform be managed by independent enterprises, rather than existing fixed CI operators, to promote the EVs at relatively low charging costs.

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.

An Analytical Framework for Assessing Equity of Access to Public Electric Vehicle Charging Stations: The Case of Shanghai

With the unprecedented growth of electric vehicles usage, the equitable population-based provision of public charging services has become an important concern in high-density urban centers. To address sustainability concerns, this study explores an analytical framework for assessing the equity of access to public charging services. By comprehensively analyzing factors such as accessibility, the Gini coefficient, the correlation coefficient, and supply–demand matching, we investigated the unequal access to public charging stations within 24 types of sites in central Shanghai. The spatial distribution and accessibility were visualized to illustrate differences in service access. Subsequently, social equity was assessed by considering the population distribution and identifying areas of supply–demand imbalance. The results show that 81% of households share only 10% of public charging services, suggesting a generalized inequality within areas and facilities. Residents of large-scale, low-density, low-grade neighborhoods have difficulties accessing services. Nearly 66.96% of subdistricts have supply and demand conflicts. In addition, priority types of improvement were identified and directions for improvement were suggested, as well as recommendations for the integration of PCSs with exterior built places. We also found significant differences in accessibility and equity at both the district and subdistrict level. The findings of this study will help urban planners assess and locate unequal areas and provide insights and the basis for further expansion into the analysis methods adopted at different stages to achieve sustainable development.

Service pricing and charging strategy for video platforms considering consumer preferences

AbstractHeterogeneity of consumer preferences is a crucial feature of the platform economy, and service price and charging strategies crucially influence customer choice behavior. To enhance consumer experience and boost product value, video platforms offer value‐added services, also known as premium membership features. For instance, Youku's benefits of value‐added service include seamless video playback, high‐definition picture quality, and exclusive episodes. This study constructs a two‐stage Hotelling model from monopoly to duopoly competition. Considering the heterogeneity of consumer preferences for product quality and platform usage costs, we analyze the impact mechanism of the customer preferences heterogeneity and the service pricing of video platform enterprises. In addition, we analyze the Nash equilibrium strategies of competing enterprises in the competition scenario, and we consider two charging strategies: freemium and bundled sales. The results indicate that the consumer sensitivity factors significantly impact the optimal pricing of services and the profits of enterprises and that this impact varies with the heterogeneity of customer composition and the type of charging strategies. For the optimal solutions in a competition scenario, the proportion of quality‐sensitive customers is positive for the freemium model, whereas it is negative for the bundled sales model. Furthermore, we analyze the impact of heterogeneous customer composition on the choice of charging strategy utilizing numerical analysis. This study provides a theoretical basis and decision support for product development and value‐added service pricing that can be applied to video platform enterprises and other media platforms.

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.

Online optimal scheduling for battery swapping charging systems with partial delivery

Battery swapping–charging system (BSCS) is a promising operating paradigm to provide centering charging and battery swapping service for electric vehicles in transportation electrification. Facing real-time information on battery demand under the limited transporting trucks, flexible online optimization of battery delivery and transportation routing is essential for meeting practical requirements. This paper investigates the real-time scheduling problem in BSCS, considering the battery partial delivery, energy demand, delivery deadline, and vehicle routing. Considering the non-deterministic polynomia hardness of battery transportation, the offline BSCS is a time-consuming task and is unsuitable for the online setting. A Lagrangian relaxation-based Benders decomposition is proposed for parallel and real-time implementation, improving the scheduling efficiency. To tackle future information such as battery demands and delivery deadlines, by introducing the dummy copy, the offline algorithm is embedded within a rolling horizon framework to solve in real-time repeatedly. Finally, case studies using real road maps in Shanghai and Belgium have verified the validity of the proposed online framework and confirmed the necessity of considering partial delivery in enhancing the operation flexibility of BSCS. The computational efficiency of the proposed algorithm is studied under different scales of the road network, and the profit from partial delivery and online implementation are highlighted.

Electrical Vehicle Smart Charging Using the Open Charge Point Interface (OCPI) Protocol

This paper proposes a new approach to the design of smart charging systems. It aims to separate the role of the Smart Charging Service Provider (SCSP) from the role of the Charge Point Operator (CPO) to provide real flexibility and efficiency of mass deployment. As interoperability is required for this purpose, the challenge is to use standard equipment and protocols in the design of the smart charging Energy Management System (EMS). The use of an Open Charge Point Interface (OCPI) is crucial for an interface between the EMS and the Charge Point Operator. The smart charging EMS developed has been implemented and successfully tested with two CPOs, with different use cases: (1) EV charging infrastructure at office buildings, and (2) EV charging infrastructure installed at a public car park facility.