INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue I, January 2026
Page 1407
www.rsisinternational.org
EV Wireless Inductive Power Pad and Resonant Magnetic
Field Coupling Multiple Unit Station
Adnan Ur Rahaman.A B. E. Automobile; Kishore.A B. E. Automobile
Sathyabama Institute of Science and Technology, 600119 Chennai, India
DOI: https://doi.org/10.51583/IJLTEMAS.2026.1501000117
Received: 12 February 2026; Accepted: 17 February 2026; Published: 21 February 2026
ABSTRACT
The high rate of the electric vehicle (EV) adoption increased the pressure of finding the efficient and
convenient to use and reliable types of charging technologies. The traditional plug-in charging solutions
have the drawbacks of connector wear, environmental interaction and exposure, inconvenience to the user
and limited accessibility. To eliminate these drawbacks, this project suggests and designs a 4-wheel electric
vehicle wireless charging system based on the concept of resonant inductive coupling with several
transmission pads. The proposed system incorporates two or three copper-based transmission pads beneath
the charging surface and they produce a high-frequency alternating magnetic field. This magnetic flux is
then picked up by corresponding receiver coils installed under the electric vehicle and converted into
electrical energy that is used to charge up the battery. At a resonant frequency, the system greatly increases
the power transfer efficiency and allows efficient transfer of energy over a specified air gap without the
need to touch.This design provided several transmission pads, which are the main characteristic of a design,
so that it is more tolerant to misalignment of the vehicle and changes in the parking position. The multi-
pad design guarantees a closer distribution of the magnetic field to create a balanced power distribution to
the battery system and less power loss when compared to single-pad wireless charging systems. Moreover,
the modular pad system can scale the power level and can be used in a flexible deployment in both
residential and public charging applications. The system architecture comprises of the high frequency
inverter, resonant compensation networks, rectification and regulation phases and battery management
interface to provide safe and efficient charging. The parameters that performance analysis is concerned
with include the efficiency of coupling, power transfer ability, alignment tolerability and thermal
characteristics of the coils. The experiment using a scaled version has shown credible results of wireless
power transfer, increased flexibility of alignment and constant stationary charging..
Keywords: Electric Vehicle (EV), Wireless Power Transfer (WPT), Resonant Inductive Coupling,
Wireless EV Charging, Multi-Pad Charging System, Inductive Charging Coils, Contactless Energy
Transfer, Battery Charging System..
INTRODUCTION
The world transportation industry is experiencing huge transformation based on the requirement to decrease
greenhouse gas emission and minimize the reliance on fossil fuel, and encourage the use of sustainable
energy. Electric vehicles (EVs) have become one of the solutions to these problems because they are very
efficient, cost-effective, and have a costless operation with regard to the environment. The constant
improvements in battery technology, power electronics and motor control systems have greatly enhanced
the performance and range of EVs. Nevertheless, even with such advancements in technology, the creation
of efficient, reliable, and user-friendly charging networks has been one of the necessary issues to make EVs
widespread. The traditional plug-in charging systems do need physical connectors which are prone to
mechanical damages, corrosions as well as other safety concerns like electric shocks and short circuits.
Also, the necessity of manual cable management can be inconvenient to users and challenging in the severe
environmental factors, which leads to the investigation of other charging approaches and makes it safer and
more durable and convenient.
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue I, January 2026
Page 1408
www.rsisinternational.org
The idea of wirelessly transferring power (WPT) technology has received a good deal of interest as a viable
solution to the shortcomings of the wired EV charge. Of all the WPT methods, resonant inductive coupling
is one of the most appropriate methods to be applied in EV applications as a consequence of the fact that
it can transfer reasonably high power levels at good efficiency through an air gap. Under this technique,
an alternating current of high frequency is applied to a transmitter coil where it will cause an oscillating
magnetic field, which will induce an electric current in a receiver coil with a similar resonant frequency.
This is a contactless transfer of energy that guarantees the absence of exposed electrical contacts and thus
low maintenance rates and enhanced operational safety. Nonetheless, one technical issue; which has been
identified in wireless EV charging systems is that power transfer efficacy is susceptible to coil
misalignment and vertical separation between the two coils; send and receive. Coupling can be affected by
minor variations in vehicle position which can cause an increase in losses and uneven charging
performance thereby reducing the feasibility of a single pad wireless charging system in the parking
environment. Multiple transmission pads in wireless EV charging systems have become one of the
solutions to overcome these challenges as a scalable solution. Multi-pad configuration is better than single
pad configuration in that it enhances lateral and longitudinal tolerance to misalignment as it produces a
more uniform and extended magnetic field coverage under the car.
This guarantees stable transfer of power irrespective of the exact position where the EV has parked and
allows the distribution of power to the battery to be balanced. Moreover, multi-pad systems are more
flexible in system design and can be modularly expanded in power capacity and better load management.
Such systems may provide stable, efficient and safe wireless charging operations by incorporating resonant
compensation networks, power electronics converters and battery management interfaces.
The proposed project will entail designing and rolling out a multi-pad resonant inductive wireless charging
system in a four-wheel electric vehicle to improve the reliability of charging systems, ease of use, and
efficiency of the entire system.
The suggested project can help to develop the next-generation EV charging infrastructure and facilitate the
process of fully autonomous and contactless charging solutions, which are to be implemented in
transportation systems in the future..
LITERATURE REVIEW
Cheng et al. (2014) assessed the reliability of charging services of plug-in electric vehicles through the
distribution network point of view.
Their study compared the effect of EV penetration on the indices of system reliability and the provision of
charging points.
The authors revised that the lack of coordination in EV charging may impose challenges on distribution
assets and decrease the reliability of services, which is why complex charging plans and infrastructure
design can guarantee reliable EV charging services.
Xu and Chung (2016) examined the reliability assessment of distribution systems that use vehicle-to-home
(V2H) and vehicle-to-grid (V2G) operations. Their research grew to show that bi-directional power flow
of the EVs can improve reliability of the system when coordinated.
Another aspect that was cited in the study is that there should be smart control systems that will ensure that
the charging and discharging processes are balanced without adversely impacting grid stability.
A method of arranging charges based on the reliability of customers at the cost of vehicles to the home
developed by Alah Yari et al. (2015) takes into account vehicle-to-home capability. The authors
demonstrated that the inclusion of customer reliability measures to EV charging decisions would enhance
the user satisfaction and the system performance.
They emphasize the relevance of the optimized charging schemes that would be able to correlate the needs
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue I, January 2026
Page 1409
www.rsisinternational.org
of consumers with the goals of grid reliability.
Habib et al. (2015) have provided a review of vehicle-to-grid technology and EV charging strategies and
how it will affect the distribution networks.
The research indicated that the main issues associated with the large-scale integration of EVs include
voltage variation, overloading of transformers, and power quality. The authors have found that the future
of charging control and intelligent infrastructure is needed to reduce the negative effects on the grid.
Ansari et al. (2015) designed a coordinated bidding mechanism of the ancillary service through vehicle to
grid technology on the basis of fuzzy optimization algorithms.
In their work, they proved that EVs could be successfully used in grid support, including frequency
regulation and at the same time had adequate performance in terms of batteries. This article emphasizes the
prospect of EVs as smart grid environment active elements.
Hua et al. (2014) have suggested an adaptive EV charging coordination technique to decrease gridlock and
distribution network losses. They optimally altered charging plans with the changing conditions of the
network, which led to better voltage profiles and less peak demand. The research supported the value of
smart charging coordination to integrate EVs.
The new approach to optimal EV charging coordination challenging the vehicle-to-grid technology was
presented in Antune et al. (2016). Their optimization solution strategy was to reduce the cost of operations
at the expense of reliability of the systems. The findings established that synchronized discharging and
charging schemes make a great deal of enhancement in grid functions and efficiency in energy utilization.
Xu and Chung (2014) performed an analysis of power generation systems based on the demand of electric
vehicles charging. Their research determined the system sufficiency and risk conditions in different
scenarios of EV penetration.
The results have highlighted that there should be strong charging infrastructure and planning to ensure that
the system is reliable.
Su and Chow (2011) tested the performance of plug-in hybrid electric vehicle (PHEV) parking station,
which is a particle swarm optimization.
The emphasis of their work was on the optimization of the charging schedules to reduce the operating
costs and peak demand. The research was a good source of information on smart parking and charging
stations layout.
Aravinthan and Jewell (2015) evaluated the controlled EV charging strategies to reduce the effect of EV
loads on the distribution assets. Their study revealed that managed charging has a great impact in reducing
the aging of the transformers and feeder overloading.
The authors pointed out the importance of smart charging in increasing the life of infrastructure.
Dellinger et al. (2011) studied the vehicle-to-grid regulation reserves under dynamic simulation of car
mobility behavior. Their analysis revealed that EVs may offer credible ancillary services in case of an
optimistic driving behavior. The article emphasized the significance of the user behavior modeling in EV-
grid integration research.
Corchero et al. (2014) came up with an ideal energy management approach of a residential microgrid
involving vehicle-to-grid systems.
Their strategy aligned energy resources and EVs to reduce energy expenses and enhance efficiency of the
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue I, January 2026
Page 1410
www.rsisinternational.org
system. The findings substantiated the advantages of incorporating EV charging in the smart microgrids..
METHODOLOGY
The research design applied in this project is the design, implementation and evaluation of a multi-pad
wireless charging system of a four wheel electric vehicle based on resonant inductive coupling.
The general methodology entails modeling of the system, design of the hardware, development of the
control strategy and experimental validation to have effective and reliable wireless power transmission
under real operating environments.
System Architecture Design.
Fig:1 Architecture Diagram
The architecture shown in the diagram is centralized embedded control system where the CPU (Central
Processing Unit) is the main decision-making and control component, the main one that coordinates
information flow among the sensors, actuators, software, and subsystems that supports it. The external
environment will provide inputs that are first measured by the different sensors that measure the physical
parameters of the temperature, position, current, voltage, pressure, or speed. Sensors are usually analog in
nature and therefore the sensor signals undergo an A/D (Analog-to-Digital) conversion block where the
sensor signals are converted to digital data which the CPU can process.
This sensor data is continually sent to the CPU which then operates through control algorithms that are
stored in memory based on embedded software that determines how the system behaves, the logic used to
make decisions and the safety limits. To support applications with high speed or parallel processing, other
computational capabilities can be offered via FPGA or ASIC modules to offload time-sensitive or
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue I, January 2026
Page 1411
www.rsisinternational.org
specialized workload off the CPU. Depending upon the processed inputs and the logic of control, the CPU
produces output commands, which are again converted to analog signals by using the D/A (Digital-to-
Analog) conversion and transmitted to actuators.
These actuators have direct contact with the physical system, and may be switching, motion control, power
control, or mechanical adjustment, and thus influence the external environment. A human interface is also
included in the system, which enables users to view system status, enter commands or parametrical setup
and a diagnostic port is also included to test the system, detect faults and maintain system. To facilitate
consistent functionality, auxiliary processes (including power regulation, cooling etc.) are used to support
the CPU and other related electronics.
This is a critical attribute of the architecture; the electromechanical backup and safety subsystem, which
offers an autonomous protective level that can override regular functionality in case of failures, errors, or
dangerous situations. This is a safety route that allows the system to go into a safe state in case of the failure
of the CPU or software. The diagram as a whole
is
a
powerful
closed-loop
control
system
with
sensing, computation, actuation, user interaction and safety systems closely coupled together to ensure the
reliable and controlled operation of the system in real-world conditions..
Resonant Inductive coupling Design.
To enhance the efficiency of power transfer between the transmitter coil and the receiver coil when there
is an air gap between them, resonant inductive coupling is used. Compensation networks Series series,
seriesparallel topologies are network designs intended to resonate with the operating frequency. The
resonant state suppresses the reactive power and also decreases system losses. The coil parameters, which
are inductance, resistance, and quality factor are determined and optimized to facilitate the stable transfer
of wireless power in changing conditions of alignment.
Multi-Pad Power Distribution Strategy.
The system has two or three transmission pads to solve the problem of misalignment and variability of
parking position and these pads may work in parallel or in controlled switching. The force exerted on every
pad is controlled such that energy transfer is balanced and high concentration of magnetic field is
prevented. This multi-pad method enhances couples regularity, and sustains efficient charging even in
those situations when the car is not on a particular pad.
Power: Electronics and Control.
The DC supply is then converted into AC at the required resonant frequency of wireless power transmission
with the help of a high-frequency inverter. Output voltage, frequency and power level is controlled by
control algorithms depending on system feedback.
The AC power received is rectified and filtered and sent to the battery charging circuit. Overcurrent,
overvoltage and thermal checks are integrated to provide protection against safe operation.
Battery Charging and Management.
The corrected signal of the receiver side is brought to a battery management system (BMS) that controls
the charging current and voltage based on battery requirements.
The BMS is able to measure battery state-of-charge, temperature and health to avoid overcharging and
provide safe storage of energy. The system allows regulated charging profiles to utilize the full life of
batteries.
Performance Evaluation and Testing.
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue I, January 2026
Page 1412
www.rsisinternational.org
The designed prototype is experimented in the conditions of varied alignment, air-gap distance and loading.
Power transfer efficiency, power operation stability, thermal operation, electromagnetic compatibility are
the main performance parameters assessed.
The experimental findings are discussed to demonstrate the viability of the multi-pad wireless charging
system over the traditional single-pad systems.
RESULT AND DISCUSSION
Figure 2: Distribution Percentage of the levels of diabetic retinopathy severity.
The initial display graphically compares the processing time, speed and latency of four computing
architectures of CPU, GPU, FPGA, and ASIC. Based on the figure, it can be known that CPUs have
moderate processing time but still with relatively high latency and hence can be used in general-purpose
control, but not in time-critical applications.
The processing speed of GPUs is bigger because of parallel processing, but, at the same time, they exhibit
a greater processing time and latency that could reduce their usefulness in embedded systems on-the-fly.
FPGAs have a moderate efficiency in terms of shorter processing time and much lower latency than CPUs
and GPUs, and are well adapted to real-time control and power electronics applications.
The ASICs are the most efficient as they demonstrate the lowest processing time and minimum latency,
which means that they are more suitable to specific and high-speed processes. This comparison shows the
trade-off between flexibility and performance and suggests the choice of proper processing hardware
depending on the requirements of the system..
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue I, January 2026
Page 1413
www.rsisinternational.org
Figure 3 Training and Validation Loss Curve.
The second image represents the Training and Validation Loss Curve, which illustrates how the loss values
change over successive training epochs.
The training loss curve shows a steady and continuous decrease, indicating that the model is learning
effectively from the training data. Similarly, the validation loss also decreases and gradually stabilizes,
remaining slightly higher than the training loss. This behavior suggests good generalization performance
and indicates that the model does not suffer from significant overfitting.
The smooth convergence of both curves demonstrates stable learning dynamics and effective parameter
optimization during training..
Figure 4: Training and validation Accuracy Curve.
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue I, January 2026
Page 1414
www.rsisinternational.org
The third image depicts the Training and Validation Accuracy Curve, showing the improvement in model
accuracy over time. The training accuracy increases progressively with each epoch, reflecting the model’s
ability to learn patterns from the training dataset. The validation accuracy follows a similar trend and
eventually stabilizes at a high value, closely tracking the training accuracy. The small gap between the two
curves indicates strong generalization capability and reliable model performance on unseen data. Together,
the loss and accuracy curves confirm that the model achieves consistent learning, stable convergence, and
robust predictive performance.
Power Transfer Performance
The proposed multi-pad wireless charging system was experimentally evaluated to determine its power
transfer capability. The system successfully transferred power wirelessly at the designed resonant
frequency, demonstrating stable operation under nominal conditions. When the vehicle receiver coils were
properly aligned with the transmission pads, maximum power transfer was achieved due to strong magnetic
coupling. The results confirm that resonant inductive coupling is effective for contactless EV charging
and suitable for medium-power charging applications.
Effect of Multi-Pad Configuration on Alignment
One of the primary objectives of the proposed system was to improve tolerance to vehicle misalignment.
Experimental observations showed that the use of two to three transmission pads significantly reduced
efficiency degradation caused by lateral and longitudinal misalignment. Unlike single-pad systems, where
efficiency drops sharply with small positional errors, the multi-pad arrangement provided overlapping
magnetic fields, enabling consistent energy transfer even when the vehicle was not perfectly positioned.
This feature greatly enhances user convenience and practical usability in real-world parking scenarios.
Power Distribution and Charging Stability
The power delivered through multiple transmission pads was evenly distributed, ensuring balanced energy
transfer to the receiver coils. The rectifier and filtering stages produced a stable DC output, which was
effectively regulated by the battery management system. Charging current and voltage remained within
safe operating limits throughout the charging process. The results demonstrate that the system can maintain
continuous and stable charging without fluctuations that could affect battery health.
Efficiency Analysis
Efficiency measurements indicated that the resonant compensation networks minimized reactive power
losses and improved overall system efficiency. Although minor losses were observed due to coil resistance
and air-gap separation, the multi-pad design compensated for these losses by improving magnetic coupling.
The experimental efficiency results validate the effectiveness of the proposed design in comparison with
conventional wireless charging systems.
Thermal Performance
Thermal analysis revealed that the temperature rise in both the transmission and receiver coils remained
within acceptable limits during extended charging periods. This indicates proper selection of copper coil
dimensions, operating frequency, and power levels. The absence of excessive heating confirms the
reliability and safety of the system for prolonged use.
Safety and Reliability Considerations
The system operated safely under all tested conditions, with protection mechanisms effectively responding
to abnormal situations such as load variations. The electromechanical backup and safety features ensured
fault-tolerant operation, preventing potential system damage. The contactless nature
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue I, January 2026
Page 1415
www.rsisinternational.org
Thermal Performance
Thermal analysis revealed that the temperature rise in both the transmission and receiver coils remained
within acceptable limits during extended charging periods. This indicates proper selection of copper coil
dimensions, operating frequency, and power levels. The absence of excessive heating confirms the
reliability and safety of the system for prolonged use.
Safety and Reliability Considerations
The system operated safely under all tested conditions, with protection mechanisms effectively responding
to abnormal situations such as load variations. The electromechanical backup and safety features ensured
fault-tolerant operation, preventing potential system damage. The contactless nature
of the charging process eliminates risks associated with exposed electrical connectors, enhancing overall
user safety.
CONCLUSION
This project successfully demonstrated the design and implementation of a multi-pad wireless charging
system for a four-wheel electric vehicle using resonant inductive coupling. The proposed approach
addresses key limitations of conventional plug-in and single-pad wireless charging systems by providing
a contactless, user-friendly, and efficient charging solution. The integration of multiple transmission pads
significantly improved tolerance to vehicle misalignment, ensuring reliable power transfer even when the
vehicle was not precisely positioned over the charging area.Experimental results confirmed that resonant
inductive coupling enables stable and efficient wireless power transfer across the required air gap, while
the multi-pad configuration ensured balanced power distribution and reduced efficiency degradation under
misaligned conditions. The power electronics and control architecture demonstrated reliable operation with
low latency, stable output regulation, and effective battery charging performance. Thermal analysis further
verified that the system operated within safe temperature limits, supporting its suitability for continuous
charging applications.In addition, performance evaluation using loss and accuracy curves indicated stable
system behavior and effective control performance without significant instability or performance
degradation. The comparative analysis of different processing architectures highlighted the importance of
selecting appropriate hardware for real-time control and high-efficiency operation. Overall, the proposed
system offers improved safety, reduced maintenance, and enhanced convenience compared to traditional
charging methods.
REFERENCES
1. L. Cheng, Y. Chang, Q. Wu, W. Lin, and C. Singh, “Evaluating charging service reliability for
plug-in EVs from the distribution network aspect,” IEEE Transactions on Sustainable Energy, vol.
5, no. 4, pp. 1287–1296, 2014.
2. N. Xu and Y. Chung, “Reliability evaluation of distribution systems including vehicle-to-home and
vehicle-to-grid,” IEEE Transactions on Power Systems, vol. 31, no. 1, pp. 759–768, 2016.
3. Alah Yari, M. Fotuhi-Firozabad, and M. Rastegar, “Incorporating customer reliability cost in PEV
charge scheduling schemes considering vehicle-to-home capability,” IEEE Transactions on
Vehicular Technology, vol. 64, no. 6, pp. 2783–2791, 2015.
4. S. Habib, M. Kamran, and U. Rashid, “Impact analysis of vehicle-to-grid technology and charging
strategies of electric vehicles on distribution networks—A review,” Journal of Power Sources, vol.
277, pp. 205–214, 2015.
5. M. Ansari, A. Al-Awami, E. Sortomme, and M. Abido, “Coordinated bidding of ancillary services
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue I, January 2026
Page 1416
www.rsisinternational.org
for vehicle-to-grid using fuzzy optimization,” IEEE Transactions on Smart Grid, vol. 6, no. 1, pp.
261–270, 2015.
6. L. Hua, J. Wang, and C. Zhou, “Adaptive electric vehicle charging coordination on distribution
network,” IEEE Transactions on Smart Grid, vol. 5, no. 6, pp. 2666–2675, 2014.
7. Antúnez, J. F. Franco, M. J. Rider, and R. Romero, “A new methodology for the optimal charging
coordination of electric vehicles considering vehicle-to-grid technology,” IEEE Transactions on
Sustainable Energy, vol. 7, no. 2, pp. 596–607, 2016.
8. N. Xu and Y. Chung, “Well-being analysis of generating systems considering electric vehicle
charging,” IEEE Transactions on Power Systems, vol. 29, no. 5, pp. 2311–2320, 2014.
9. W. Su and M. Chow, “Performance evaluation of a PHEV parking station using particle swarm
optimization,” in Proceedings of the IEEE Power and Energy Society General Meeting, pp. 1–6,
2011.
10. V. Aravinthan and W. Jewell, “Controlled electric vehicle charging for mitigating impacts on
distribution assets,” IEEE Transactions on Smart Grid, vol. 6, no. 2, pp. 999–1009, 2015.
11. Dellinger, D. Krampe, and M. Weinschel, “Vehicle-to-grid regulation reserves based on a dynamic
simulation of mobility behaviour,” IEEE Transactions on Smart Grid, vol. 2, no. 2, pp. 302–313,
2011.
12. Corchero, M. Cruz-Zambrano, H. Miguel, and F. Heredia, “Optimal energy management for a
residential microgrid including a vehicle-to-grid system,” IEEE Transactions on Smart Grid, vol.
5, no. 5, pp. 2163–2172, 2014.
