EMPOWERING ELECTRIC VEHICLE WITH DYNAMIC

VEHICLE TO VEHICLE CHARGING

Abinesh N 1, a) , Melvin Adharsh I G 1,b) and Dr.C.N.Gnanaprakasam2, c)

Author Affiliations
1
Student, St. Joseph’s College of Engineering, OMR, Chennai-600119,Tamilnadu,India
2
Faculty, St. Joseph’s College of Engineering, OMR, Chennai-600119,Tamilnadu,India

Author Emails
a)
Corresponding author:abineshnagarajan1@gmail.com
b)
melvinjoseph2514@gmail.com
c)
gnanacn@gmail.com

Abstract. Electric vehicles (EVs) tend to experience problems related to battery drain, resulting in sudden breakdowns.
This project solves this problem by implementing an intelligent charging system that facilitates vehicle-to-vehicle (V2V)
energy transfer. An Arduino Uno microcontroller periodically checks the battery voltage through a DC voltage sensor.
When the battery is near a critical level, the driver can send a request for charging assistance by activating a push button.
This request is transmitted through a ZigBee module to nearby vehicles with corresponding receivers. These vehicles can
respond in real time through an IoT-based webpage, thereby ensuring timely and effective assistance. Upon receiving an
accepted request, confirmation is returned to the requesting vehicle. This system improves energy management, minimizes
sudden power loss, and facilitates cooperation among EVs. By using IoT and wireless communication technologies, the
proposed solution ensures convenient mobility, thereby encouraging sustainability and convenience in EV operations.

Keywords: Vehicle-to-Vehicle Charging, Arduino Uno, ZigBee, IoT, Smart Charging, Energy Management, Wireless
Communication.

INTRODUCTION

The increasing demand worldwide for efficient and sustainable transportation means has fueled great innovation
in intelligent vehicular technologies. As the automotive industry evolves towards electric and autonomous cars,
efficient energy management is one key area of interest. One of the innovative methods of addressing this issue is by
[1] developing peer-to-peer energy-sharing systems that enable vehicles to help each other under emergency
situations. These systems are more sustainable since they optimize the use of energy, reduce dependence on traditional
charging infrastructures, and promote peer-to-peer coordination among drivers. This shift to intelligent, networked
vehicles is closely related to the rising deployment of Internet of Things (IoT) technologies, which promote real-time
communication and resource sharing among vehicles.
The concept of peer-to-peer energy sharing among vehicular networks is inspired by innovations in decentralized
systems, in which resources are shared and transferred among participants [2] in the absence of a central controlling
authority. Analogous to how peer-to peer networks function in data sharing, vehicles can transfer energy directly
among themselves, promotingresource efficiency and reducing wastage of energy. This cooperative system is
especially valuable in emergency situations, where a vehicle that is running low on battery can be assisted by adjacent
vehicles without needing to wait for roadside assistance or travel to distant charging facilities. By leveraging on IoT-
enabled devices and technologies that promote real-time communication, these systems provide a cost-effective and
sustainable means of addressing energy problems in modern-day transportation networks.
An underlying enabler of sophisticated charging systems is the integration of Internet of Things (IoT) technologies,
which integrate vehicles, sensors, and cloud computing platforms into a unified framework. IoT technology allows
vehicles to track their battery [3] levels in real-time and share information with surrounding vehicles when support is
needed. With wireless communication protocols, such as ZigBee, vehicles can share information rapidly and
efficiently. ZigBee, due to its very low energy draws and very short-range communication capabilities, is optimum
for vehicle-to vehicle (V2V) communication in cooperative networks. Further, cloud platforms facilitate real-time
data sharing and provide drivers with the ability to track and respond to requests for support through web or mobile
interfaces. This networked system not only increases the efficiency of communication but also enhances the user
experience through real-time notifications and status updates.
The significance of real-time data sharing in such systems is of utmost significance. Rapid information sharing
ensures that requests for support are instantaneously communicated to [4] surrounding vehicles, ensuring timely
response and reduced downtime. Further, the employment of IoT-enabled web interfaces allows drivers to review
available support options, accept or decline requests, and view the status of current support programs. This real-time
cooperation among vehicles fosters a sense of community among drivers and promotes mutual support, especially in
rural or underserved areas where charging stations are limited. Finally, the integration of GPS modules with IoT
platforms facilitates accurate location tracking, allowing vehicles to identify the closest available support quickly and
efficiently.
From an environmental standpoint, peer-assisted charging systems are crucial to the evolution ofsustainability. By
facilitating resource sharing, such systems minimize energy waste and lower [5] the carbon footprint linked to the
installation and maintenance of large charging networks. Furthermore, they improve the efficiency of energy
distribution in vehicular networks, thereby optimizing the utilization of available resources. Such technologies are
consistent with the worldwide effort to enhance green alternatives to transportation and mitigate the environmental
footprint of vehicular activities.
In spite of the numerous benefits, the implementation of collaborative energy-sharing systems is hindered by
numerous challenges. Reliable communication between vehicles demands an effective, low-latency network capable
of handling numerous simultaneous connections. Moreover, protection of data [6] transmission is paramount, as
unauthorized intrusion into communication channels has the capability to violate user privacy and security. Mitigation
of such challenges demands the implementation of trustworthy wireless communication protocols and sophisticated
security measures, such as encryption and authentication techniques. Further, encouragement of widespread adoption
of such systems necessitates cooperative action among auto producers, technology firms, and regulatory agencies in
formulating standardized communication protocols and assuring interoperability across diverse vehicle models.
Overall, IoT- and V2V-based intelligent charging systems form a viable strategy to address modern challenges in
vehicular energy management. By utilizing the sharing of real-time information and cooperative use of resources, such
systems optimize efficiency, foster sustainability, and enhance [7] driver convenience. As technology and research
progress continue to counter current challenges, peer-assisted charging systems stand well-positioned to become a
core element of future intelligent transportation networks, pushing the transition to sustainable and interdependent
mobility environments.
This work is organized with review of the literature survey as Section II. Methodology described in Section III,
highlighting its functionality. Section IV discusses the results and discussions. Lastly, Section V concludes with the
main suggestions and findings.

LITERATURE SURVEY
Various studies have centered on vehicle-to-vehicle (V2V) communication, highlighting its relevance to real time
information exchange to support driver assistance and traffic management optimization. V2V technologies enable
vehicles to share vital information such as geographical location, speed, and battery level, thus encouraging
cooperative driving behavior and reducing the incidence of accidents. Researchers posit that the use of wireless
communication protocols, e.g., ZigBee or LoRa, can enable low-energy, short-range exchanges between vehicles.
The literature also points to the need to standardize communication protocols to support compatibility between
vehicle models. Such advancements are part of the realization of intelligent transportation systems (ITS) that ensure
efficient use of roads and facilitate sustainable mobility systems.
Studies on IoT-based automotive systems point to their implication in real-time monitoring and decision-making
processes for drivers. The integration of IoT technology enables vehicles to share vital information with the
environment, e.g., battery status and available charging facilities. Various studies [8] explain how cloud computing
and mobile applications enable remo8te monitoring and timely alerts for drivers. Researchers have also examined
security loopholes in relation to IoT systems, with a focus on the need for encryption and secure data transfer
mechanisms. Such advancements in IoT technologies improve energy management, optimize resource allocation,
and improve emergency response within vehicular networks, thus facilitating the transition towards intelligent
transportation ecosystems.
 Studies on peer-to-peer (P2P) energy-sharing networks for electric vehicles (EVs) highlight their ability to
reduce reliance on centralized charging stations. Researchers identify that distributed networks enable direct energy
trading between EVs, especially in emergency situations or power outages. These models employ Internet of Things
(IoT) platforms and blockchain for secure and transparent transactions. Additionally, studies highlight the
importance of real-time [9] data exchange in optimizing energy distribution and decongesting charging points. The
findings indicate that peer-to-peer energy sharing can play a significant role in sustainable transport by balancing
demand and supply in vehicle networks efficiently.
Studies on smart transportation systems investigate how new communication protocols can empower seamless
interaction between networked vehicles. Studies highlight the importance of low-latency wireless networks such as
ZigBee, Wi-Fi, and 5G in ensuring real-time data transfer. Researchers believe that integrating cloud services for
data storage and analytics can optimize routes and battery management. Some studies also highlight concerns related
to signal interference and data security. In summary, smart transportation [10] systems with efficient communication
protocols are necessary to enable energy sharing, reduce traffic congestion, and improve vehicle-to-vehicle (V2V)
coordination.
Some studies investigate sensor-based vehicle monitoring systems, highlighting their benefits for real time
diagnostics and predictive maintenance. Researchers highlight how sensors such as voltage meters, accelerometers,
and GPS modules capture and transmit valuable information about vehicle performance. Real-time monitoring
enables drivers to analyze battery health, detect faults, and prevent breakdowns. Additionally, studies highlight the
importance of cloud integration for remote access to vehicle diagnostics. These advancements in sensor technology
enable [11] better energy management, enhanced driver safety, and enhanced decision-making within vehicle
networks, especially in relation to peer assisted charging systems.
Researchers have researched cooperative vehicle networks with the aim of understanding how they can facilitate
peer-to-peer sharing of resources during roadside accidents. Cooperative networks are based on IoT platforms and
real-time communication systems to enablevehicles within a certain distance to exchange information. Studies
indicate how cooperative networks provide energy exchanges and help drivers find assistance nearby. Researchers
also address [12] issues like synchronization of data and network security. Studies indicate that cooperative vehicle
networks can help to cut response times in emergency conditions by a great extent and help create sustainable,
connected transportation systems.
Research on IoT-based notification systems in vehicles is focused on their contribution to driver awareness and
decision-making. Researchers describe how IoT platforms interact with mobile apps and cloud infrastructure to send
real-time notifications of vehicle status, nearby threats, and service availability. Research also describes how real-
time push notifications enable drivers to make quick decisions during emergencies. Some research also focuses on
cybersecurity aspects, describing secure [13] communication protocols. Overall, IoT-based notification systems lead
to enhanced safety, efficient resource utilization, and efficient communication in connected vehicle systems.
Current research on mobile-based IoT interfaces is focused on their contribution to helping drivers monitor
vehicle status and use resources efficiently. Research describes user-friendly mobile apps coupled with cloud
platforms to provide real-time access to battery status, charging requests, and vehicle diagnosis. Researchers
highlight the contribution of intuitive interfaces and multi platform support to smooth user experience. Some
research also focuses on integrating [14] GPS and push notifications to provide real-time notifications. Mobile-based
IoT interfaces are considered an integral part of connected vehicle systems, ensuring accessibility and
environmentally sound driving habits through efficient resource utilization.
Some research on energy-efficient vehicular communication systems is focused on ways to minimize power
consumption without sacrificing connectivity. Researchers refer to lightweight protocols like ZigBee for short-range
communication because of their low power consumption. Some research also describes the contribution of network
[15] optimization techniques like data compression and sleep-wake cycles in minimizing energy consumption.
Research findings show that using energy-efficient communication protocols can greatly enhance the lifespan of IoT
devices, minimize vehicle energy consumption, and support sustainable vehicular operations, particularly in systems
with real-time peer-to peer energy sharing.
Research into sustainable vehicle technologies identifies energy-sharing mechanisms as crucial to the
minimization of electric vehicles' carbon footprint. Researchers examine models that enable peer-to-peer (P2P)
energy transfers, thereby enabling vehicles to share surplus energy among themselves. The research [16] identifies
the application of decentralized blockchain platforms for enabling secure and transparent transactions. The research
further identifies the environmental advantage of minimizing the reliance on charging infrastructure. Such research
identifies that P2P energy-sharing models can be critical to sustainable transport by encouraging effective resource
optimization and minimizing energy waste in integrated vehicle communities.
Research into vehicle telemetry systems examines real-time data collection, cloud-based analytical functions,
and remote monitoring of vehicles. Research analyzes the capacity of IoT-enabled telemetry systems to monitor
various parameters, including battery levels, geographic position, and thermal [17] status. Researchers identify the
advantage of integrating cloud platforms to provide secure storage and remote access to data. Furthermore, the
research enlightens the role of analysis of telemetry data in predictive maintenance and encouraging operational
efficiency. The research concludes that telemetry systems are core components of connected vehicle ecosystems,
providing instant information to drivers and encouraging sustainable transport practices through effective resource
optimization.
Researchers comparing peer-assisted mobility solutions examine the role of crowdsourced networks in
providing instant support in the event of a vehicle emergency. The research identifies the application of IoT
platforms in enabling instant [18] communication between drivers within a specified geographic area. Researchers
identify the advantages of collaborative networks, including the reduction of response times and optimization of
resource sharing. In addition, some research examines challenges surrounding network congestion and data privacy
issues. Peer-assisted mobility solutions are regarded as critical to connected transportation ecosystems'
infrastructure, enabling community-based support systems that can dramatically improve the safety and convenience
of drivers.
Research on digital peer-to-peer (P2P) platforms for vehicle resource sharing emphasizes their scalability and
ability to reduce service latency. Researchers describe how P2P networks allow vehicle-to-vehicle direct
interactions, making [19] efficient exchange of resources such as energy and charging slots possible. Additionally,
research emphasizes the importance of secure authentication protocols in maintaining data integrity in P2P systems.
The research indicates that digital P2P platforms are critical in the creation of self-sustaining transportation systems
by maximizing the efficiency of resource utilization and reducing reliance on centralized infrastructure.
Research on Internet of Things (IoT)-based roadside assistance services demonstrates how connected vehicles
can streamline emergency response procedures. Research explores real-time communication protocols that send
distress signals [20] to nearby vehicles or assistance providers. Researchers emphasize the use of IoT sensors and
cloud-based platforms in enabling early detection of assistance needs. Additionally, research touches on signal
interference issues and possible security risks. The research indicates that IoT-based roadside assistance services
improve driver safety, reduce response time, and optimize resource allocation in connected vehicle networks.
Research on interconnected smart vehicle ecosystems explores the benefits offered by multi-node networks in
efficient resource sharing. Researchers highlight the ability of IoT-based vehicles to share energy resources,
exchange status information, and optimize routes. Additionally, some research emphasizes the use of machine
learning algorithms for network traffic forecasting and load balancing. The research indicates that interconnected
vehicle ecosystems can efficiently improve energy efficiency, reduce congestion, and offer sustainable
transportation alternatives through efficient peer-to-peer collaboration.

METHODOLOGY

The suggested vehicle-to-vehicle (V2V) charging system employs the Internet of Things (IoT) and wireless
communication to enable real-time energy exchange between electric vehicles. The central processing unit is an
Arduino Uno microcontroller, which tracks battery levels and triggers charging requests when a vehicle's battery is at
a critical level. The system employs ZigBee technology to relay charging requests to neighboring vehicles, which
respond through an IoT-based webpage. On acceptance, energy transfer is triggered through a controlled relay based
circuit. The approach ensures seamless communication, timely support, and efficient energy distribution, thus
improving electric vehicle performance while fostering sustainability and seamless mobility.
 A. System Architecture
The system revolves around an Arduino Uno microcontroller that interacts with sensors and communication
modules to enable V2V charging. A DC voltage sensor tracks battery levels, while a push button allows
drivers to trigger support when battery depletion is imminent. ZigBee modules ensure wireless
communication between vehicles, ensuring efficient request transmission. An IoT-based webpage provides
a real-time interface for viewing and responding to charging requests. The system also includes a relay-based
circuit for controlled energy transfer, thus ensuring secure and efficient charging. The architecture supports
a decentralized and cooperative energy-sharing network among electric vehicles.

B. Battery Monitoring and Voltage Detection

A DC voltage sensor is linked to a 12V battery to monitor its charge level continuously. The Arduino Uno
senses the voltage levels and decides when the battery is running low. When the voltage drops below a
threshold level, the system notifies the driver of the low battery level. This proactive action avoids sudden
power loss and allows intervention in time. The voltage detection system offers efficient energy management,
thus optimizing battery utilization efficiency. Through constant monitoring of battery condition, the system
offers real-time feedback that improves the reliability and lifespan of electric vehicles, thus minimizing the
chances of sudden failure.

C. Charging Request Initiation

When the battery is critically low, the driver makes a charging request through a dedicated push button. When
the button is activated, the Arduino Uno energizes the ZigBee module to send the request to nearby vehicles.
The request includes critical information, such as vehicle ID, battery level, and geographical location data
from the GPS module. This information allows nearby vehicles to analyze the situation before responding.
The push-button procedure simplifies the request procedure, allowing drivers to request assistance in time
without the need for human intervention. This automatic request initiation improves the responsiveness and
efficiency of the charging system.

D. Transmission and Reception of Charging Request

The charging request is broadcast through ZigBee communication to all vehicles in the vicinity within range.
Each vehicle receiving the request processes it and shows it on an IoT-enabled webpage. The webpage offers
real time visibility of the pending requests, such that vehicles capable of offering assistance can respond in
real time. The short-range, low-power communication of ZigBee provides data transfer reliability while
conserving energy. The mechanism allows for seamless interaction between multiple vehicles, creating a
cooperative energy-sharing network. Utilizing IoT for visibility of requests, the system provides transparency
and efficiency in charging, allowing for quick decision-making and quick response among vehicle owners in
the vicinity.

E. Acceptance of Charging Request

Vehicles in the vicinity accepting the request can do so depending on their battery level and availability.
Drivers can utilize the IoT-based webpage to indicate their willingness to offer assistance. When accepted
by a vehicle, the system creates an acknowledgment message, which is transmitted back to the requesting
vehicle through ZigBee communication. The acknowledgement notifies the requester of the incoming
assistance. The acceptance process ensures coordination, allowing for a seamless transition into the charging
process. Through the incorporation of real-time monitoring of responses, the system avoids delays and
ensures that energy-sharing activities are conducted efficiently and effectively.

F. Charging Process and Energy Transfer

 Once the charging request is received, the support vehicle proceeds to get closer to the requesting vehicle. A
relay based switching circuit is then activated to facilitate a safe and controlled connection for energy transfer.
Energy is transferred from the battery of the support vehicle to the requesting vehicle in controlled conditions,
hence the voltage levels remain stable. Charging proceeds until the receiving vehicle's battery is charged to
a certain level. The controlled energy transfer prevents overcharging and maintains battery integrity. Using
relay-based switching and real-time monitoring, the system facilitates efficient and secure energy transfer,
hence enhancing the reliability of vehicle-to-vehicle charging processes.

FIGURE 1:Block Diagram for Transmitter side

FIGURE 2:Block Diagram for receiver side

RESULT AND DISCUSSION

The use of the suggested vehicle-to-vehicle (V2V) charging system demonstrated effective real-time energy
management and smooth communication among electric vehicles. The Arduino Uno efficiently regulated
battery voltage levels by using the DC voltage sensor, thus allowing immediate detection of low charge levels.
Upon the detection of the fall in battery voltage below the defined threshold by the system, it immediately
started a charging request, which was then transmitted through ZigBee communication to the neighboring
vehicles. The system aided in reducing response time and provided an automated approach for solving battery
draining in electric vehicles. The use of ZigBee technology allowed for robust short range communication, thus
transmission of charging requests.
During testing, the IoT-based webpage provided real time access to the charging request, thus allowing
neighboring vehicle owners to assess and respond accordingly. The interface for the webpage was made
accessible and user-friendly in order to provide fast decision-making. Vehicles implemented with the system
were able to assess received requests and decide based on battery capacity whether they can provide assistance
or not. Once a vehicle accepted the request, a successful verification was returned to the requesting vehicle, thus
validating the agreement. The entire process, including generation of the request, acceptance, and verification,
was accomplished in seconds, thus providing minimal downtime for the requesting vehicle.
The relay-switching circuit was at the heart of enabling secure energy transfer among vehicles. The relay, on
receiving the request, completed the circuit between the donor and receiver vehicle batteries and ensured a
regulated power flow. Voltage levels were monitored continuously to prevent overcharging or draining power.
The charging session was ended automatically when the receiver battery reached a predetermined safe level.
Outcomes showed that the system efficiently controlled power transfer and ensured battery integrity, hence
preventing electrical system damage in the vehicle.
Performance of the system was tested considering request transmission time, response time, and rate of
energy transfer results showed that the ZigBee communication module enabled fast and consistent data
exchange, with practically zero transmission delay. The average response time in accepting a request was within
the optimum range, thus ensuring immediate intervention in the event of an emergency. Additionally, the rate of
energy transfer was consistent, and power loss was negligible, thus demonstrating the system's applicability in
 real-time applications. IoT, ZigBee, and relay-based energy transfer integration enabled smooth and effective
operation.
The data logging aspect of the Internet of Things (IoT) platform offered critical insights into system
performance. Every charging session was logged with precision, including request initiation time, response
time, energy transferred, and session termination. The data allowed for extensive analysis and helped identify
patterns in charging demand and availability. The logged data also improved transparency and accountability,
such that support was properly recorded. In repeated trials, the system showed consistency in performance,
hence improving its credibility for real-world application in electric vehicle networks.
The results analysis showed that the proposed system substantially improved the efficiency of energy
sharing between vehicles. Through the use of IoT for real-time monitoring and ZigBee for communication, the
system reduced dependency on external charging infrastructure. The decentralized system provided a more
sustainable means of treatment for battery drain conditions in electric vehicles. The system also promoted
cooperation between drivers, enabling a more connected and efficient transport network. The reduction in
charging downtime also improved the overall convenience for users of electric vehicles, making the system a
viable option for mobility improvement.
In general, the successful testing and implementation of the vehicle-to-vehicle (V2V) charging system
showed its capability to improve energy management in electric vehicles. The real-time interaction and efficient
energy transfer were enabled through the seamless integration of hardware components and wireless
communication modules. The results confirmed that the system was capable of offering timely support under
emergency conditions, and hence the chances of unplanned vehicle stoppages due to battery drain were
minimized. Through the direct energy transfer between vehicles, the proposed solution enabled the development
of smart mobility and sustainable transport systems.

CONCLUSION

The implemented vehicle-to-vehicle (V2V) charging system has been successfully demonstrated to have an
efficient and smart mechanism for energy sharing between electric vehicles. With the use of an Arduino Uno
microcontroller, ZigBee communication, and IoT-based monitoring, the system has allowed real-time battery
depletion detection and charging support in an instant. The implementation has allowed electric vehicles with low
battery levels to request power from neighboring vehicles effortlessly, thus minimizing the interruption of mobility.
The real-time monitoring of battery voltage and automatic transmission of requests has improved response time and
reliability, effectively solving a critical problem in electric vehicle energy management. The use of ZigBee modules
for wireless communication has been effective in low latency charging request transmission. The IoT-based interface
has allowed vehicle owners to monitor and respond to requests in real-time, thus ensuring ease of use and transparency.
The relay-based switching circuit has allowed efficient power transfer between vehicles without affecting battery
integrity. With controlled energy exchange, the system has avoided overcharging and electrical component protection
in vehicles, thus ensuring a secure and stable charging process.
Testing and analysis have ensured that the system works reliably under various conditions, with effective
transmission of charging requests, timely responses, and high-energy transfer efficiency. Data logging capability has
further ensured accountability and provided insights for optimizing energy-sharing strategies. By decentralizing the
charging process, the system has minimized the reliance on conventional charging infrastructure, thus offering a more
sustainable and accessible solution for electric vehicle users. The results have shown that the proposed system could
substantially improve energy utilization, thus allowing seamless and uninterrupted mobility. The research proved a
viable and creative solution to optimizing electric vehicle energy sources. The integration of IoT, wireless
communication, and real-time monitoring created a strong and scalable solution to battery drain issues. Through the
promotion of coordination among electric vehicle consumers, the system facilitated the creation of a smarter and
cleaner transport system. Further improvement could further strengthen the system, such as the deployment of artificial
intelligence for predictive analysis and improving compatibility with various vehicle models. The research provides
proof of the viability of V2V charging as a viable step towards better energy management in electric mobility.
 REFERENCES

1. Y. Shanmugam et al., "A Systematic Review of Dynamic Wireless Charging System for Electric Transportation,"
in IEEE Access, vol. 10, pp. 133617-133642, 10.1109/ACCESS.2022.3227217.
2. Y. Yu, L. De Herdt, A. Shekhar, G. R. C. Mouli and P. Bauer, "EV Smart Charging in Distribution Grids–
Experimental Evaluation Using Hardware in the Loop Setup," in IEEE Open Journal of the Industrial Electronics
Society, vol. 5, pp. 13-27, 2024, doi: 10.1109/OJIES.2024.3352265.
3. E. ElGhanam, H. Sharf, Y. Odeh, M. S. Hassan and A. H. Osman, "On the Coordination of Charging Demand
of Electric Vehicles in a Network of Dynamic Wireless Charging Systems," in IEEE Access, vol.
4. M. Pasetti, S. D. Iacono and D. Zaninelli, "Real-Time State of Charge Estimation of Light Electric Vehicles
Based on Active Power Consumption," in IEEE Access, vol. 11, pp. 110995-111010, 2023, doi:
10.1109/ACCESS.2023.3322651.
5. S. Deb, M. Pihlatie and M. Al-Saadi, "Smart Charging: A Comprehensive Review," in IEEE Access, vol. 10, pp.
134690 134703, 2022, doi: 10.1109/ACCESS.2022.3227630.
6. Y. -J. Lin, Y. -C. Chen, J. -Y. Zheng, D. -W. Shao, D. Chu and H. T. Yang, "Blockchain-Based Intelligent
Charging Station Management System Platform," in IEEE Access, vol. 10, pp. 101936-101956, 2022, doi:
10.1109/ACCESS.2022.3208894.
7. J. Zhao, A. Arefi, A. Borghetti and G. Ledwich, "An Optimization Model for Reliability Improvement and Cost
Reduction Through EV Smart Charging," in Journal of Modern Power Systems and Clean Energy, vol. 12, no.
2, pp. 608-620, March 2024, doi: 10.35833/MPCE.2022.000837.
8. X. Zhu, P. Mishra, B. Mather, M. Zhang and A. Meintz, "Grid Impact Analysis and Mitigation of En-Route
Charging Stations for Heavy-Duty Electric Vehicles," in IEEE Open Access Journal of Power and Energy, vol.
10, pp. 141-150, 2023, doi: 10.1109/OAJPE.2022.3233804.
9. J. Rahulkumar. et al., "An Empirical Survey on Wireless Inductive Power Pad and Resonant Magnetic Field
Coupling for In-Motion EV Charging System," in IEEE Access, vol. 11, pp. 4660-4693, 2023, doi:
10.1109/ACCESS.2022.3232852.
10. A. A. Sadawi, E. Elghanam, M. S. Hassan and A. H. Osman, "On the Utilization of Blockchain and Smart
Contracts in Charging Coordination of Roadway-Powered Electric Vehicles," in IEEE Access, vol. 12, pp.
10.1109/ACCESS.2024.3359423. 29222-29237, 2024.
11. C. Diaz-Londono, P. Maffezzoni, L. Daniel and G. Gruosso, "Comparison and Analysis of Algorithms for
Coordinated EV Charging to Reduce Power Grid Impact," in IEEE Open Journal of Vehicular Technology, vol.
5, pp. 990-1003, 2024, doi: 10.1109/OJVT.2024.3435489.
12. Z. Jia, J. Li, X. -P. Zhang and R. Zhang, "Review on Optimization of Forecasting and Coordination Strategies
for Electric Vehicle Charging," in Journal of Modern Power Systems and Clean Energy, vol. 11, no. 2, pp.
10.35833/MPCE.2021.000777. 389-400, March 2023.
13. Y. Tomizawa et al., "Multipurpose Charging Schedule Optimization Method for Electric Buses: Evaluation
Using Real City Data," in IEEE Access, vol. 10, pp. 56067-56080, 2022, doi: 10.1109/ACCESS.2022.3177618.
14. P. K. Chittoor, B. Chokkalingam, R. Verma and L. Mihet-Popa, "An Assessment of Shortest Prioritized Path-
Based Bidirectional Wireless Charging Approach Toward Smart Agriculture," in IEEE Access, vol. 11, pp.
123742-123755, 2023, doi: 10.1109/ACCESS.2023.3329976.
15. M. Senol et al., "Harmonics Measurement, Analysis, and Impact Assessment of Electric Vehicle Smart
Charging," in IEEE Open Journal of Vehicular Technology, vol. 6, pp. 109-127, 2025, doi:
10.1109/OJVT.2024.3505778.
16. R. N. E. Idrissi, M. Ouassaid and M. Maaroufi, "A Constrained Programming-Based Algorithm for Optimal
Scheduling of Aggregated EVs Power Demand in Smart Buildings," in IEEE Access, vol. 10, pp. 28434-28444,
2022, doi: 10.1109/ACCESS.2022.3154781.
17. K. Phipps, K. Schwenk, B. Briegel, R. Mikut and V. Hagenmeyer, "Customized Uncertainty Quantification of
Parking Duration Predictions for EV Smart Charging," in IEEE Internet of Things Journal, vol. 10, no. 23, pp.
20649-20661, 1 Dec.1, 2023, doi: 10.1109/JIOT.2023.3299201.
18. S. Hamdare et al., "EV Charging Management and Security for Multi-Charging Stations Environment," in IEEE
Open Journal of Vehicular Technology, vol. 5, pp. 807-824, 2024, doi: 10.1109/OJVT.2024.3418201.
19. L. J. Lepolesa, K. E. Adetunji, K. Ouahada, Z. Liu and L. Cheng, "Optimal EV Charging Strategy for Distribution
Networks LoadBalancing in a Smart Grid Using Dynamic Charging Price," in IEEE Access, 12, vol. pp.
10.1109/ACCESS.2024.3382124. 47421-47432, 2024.
20. A. Shahin et al., "A Comprehensive Analysis: Integrating Renewable Energy Sources With Wire/Wireless EV
Charging Systems for Green Mobility," in IEEE Access, vol. 12, pp. 140527 140555, 2024, doi:
10.1109/ACCESS.2024.3466729.