Electric Vehicle Charging System Research Articles

Energy management of grid connected PV with efficient inverter based wireless electric vehicle battery charger: A hybrid CSA-QNN technique

A Hybrid CSA-QNN approach is proposed in this manuscript for grid-connected PV with an efficient inverter-based wireless electric vehicle (EV) battery charger. The proposed hybrid method combines the performance of both the circle search algorithm (CSA) and quantum neural networks (QNN), commonly named the CSA-QNN technique. The Circle Search Algorithm helps find the best charging spot by creating a virtual circle, while the Quantum Neural Network optimizes the overall power flow and charging efficiency. Together, these technologies contribute to making wireless charging for EVs more efficient and convenient. The major goal of the manuscript is the design of a wireless EV battery charger with PV integration. Wireless EV charging systems (WEVCS) may be a feasible alternative technology for charging EVs without a plug-in problem. The CSA-QNN method is performed in the MATLAB platform and it is compared to different existing approaches. The CSA-QNN method shows better results than the existing approaches like the Salp Swarm Algorithm (SSA), Wild horse optimizer (WHO), and Particle Swarm optimization (PSO).

A 5-kW unidirectional wireless power transfer EV charger with a novel multi-level PFC boost converter on front-end side

The greatest advantages of wireless power transfer (WPT) are its absence of severe environmental hazards, its portability, and its independence from other factors. The wireless charging system for electric vehicles has a serious problem with the amount of misalignment it can tolerate. This study explores the usage of a novel multi-level boost power factor correction (PFC) rectifier with less switch count to improve the efficiency of power conversion of a 5-kW wireless electric vehicle (EV) charger. Especially in the context of wireless charging, which provides convenience and flexibility, there is a pressing need for efficient and dependable charging infrastructure to keep up with the rising demand for electric vehicles. In contrast to wired EV chargers, wireless chargers often have poorer power conversion efficiency because of losses in power semiconductor devices. An innovative multi-level boost PFC rectifier design is offered as a solution to this problem since it uses fewer switches while retaining high-performance levels. The suggested rectifier achieves much higher power conversion efficiency. In addition, power factor correction capabilities are improved, making it comply with global rules. Simpler, cheaper, and more dependable rectifiers improve the whole system.

Comparative study of DC/DC electric vehicle charging system with conventional transformer and planar transformer

Comparative study of DC/DC electric vehicle charging system with conventional transformer and planar transformer

Cybersecurity enabled electric vehicle charging and battery management system

Electric vehicles (EVs), which are become easier to get, are displacing conventional gasoline-powered cars. Because of this, there is a great demand for electric vehicle charging systems (EVCS), which has led to a major expansion of the public and private EVCS infrastructure. The threats related to cybersecurity have significantly increased as a result of the EVCS’s growing network. In this light, this article offers an examination of the cybersecurity threats associated with the network of EVCS. First, recent trends in EV adoption, charging use cases, and the most recent advancements in the EVCS network give context for the research subject. Second, while describing cybersecurity features of EVCS, possible cyberattack scenarios as well as vulnerabilities centered on infrastructure and protocols have been taken into account. Thirdly, risks in EVCS have been confirmed through real-time data-centric analysis of EVs.

A new authentication scheme for dynamic charging system of electric vehicles in fog environment

AbstractThe dynamic charging system of electric vehicles has great potential for development. Electric vehicles initiate charging requests, and charging stations charge authorized electric vehicles. Fog computing improves the efficiency of request processing. However, open channels can be vulnerable to various attacks by a malicious adversary. Mutual authentication schemes allow users and charging stations to confirm each other. Therefore, numerous authentication and key agreement schemes have been proposed. In 2021, Babu et al. proposed an authentication scheme based on fog servers. Unfortunately, we found that their scheme can not resist FS impersonation attack and replay attack. Hence, we propose an authentication scheme between electric vehicles and fog servers to resolve the security weakness. Our scheme uses lightweight hash functions and XOR operations, which is more suitable for resource‐constrained electric vehicles. We proved our scheme can achieve mutual authentication by using BAN logic, and analyzed that our scheme can resist impersonation, replay, and known session key attacks, ensuring anonymity and untraceability. We finally compare computation cost and communication cost of our scheme with the existing schemes. The result shows that our scheme performs better than others overall. Therefore, our scheme is secure and suitable for dynamic charging systems.

The efficiency of PV-Wireless Charging System for Electric Vehicles on Highway Roads

The efficiency of PV-Wireless Charging System for Electric Vehicles on Highway Roads

Autonomous Drone System for Emergency Charging of Electric Vehicles

This study explores the development of an emergency charging system for electric vehicles (EVs) using drones. The system is designed to address the limitations of current EV charging infrastructure, particularly in remote or inaccessible areas. The proposed solution involves a drone equipped with a battery pack, which can be dispatched to a stranded EV to provide immediate power.

Optimizing microgrid performance: Strategic integration of electric vehicle charging with renewable energy and storage systems for total operation cost and emissions minimization.

At present, renewable energy sources (RESs) and electric vehicles (EVs) are presented as viable solutions to reduce operation costs and lessen the negative environmental effects of microgrids (μGs). Thus, the rising demand for EV charging and storage systems coupled with the growing penetration of various RESs has generated new obstacles to the efficient operation and administration of these μGs. In this regard, this paper introduces a multi-objective optimization model for minimizing the total operation cost of the μG and its emissions, considering the effect of battery storage system (BSS) and EV charging station load. A day-ahead scheduling model is proposed for optimal energy management (EM) of the μG investigated, which comprises photovoltaics (PVs), fuel cells (FCs), wind turbines (WTs), BSSs, and EV charging stations, with shed light on the viability and benefits of connecting BSS with EV charging stations in the μG. Analyzing three case studies depending on the objective function-Case 1: execute EM to minimize total operation cost and maximize the profits of BSS, Case 2: execute EM to minimize total emission from the μG, and Case 3: execute EM to minimize total operation cost, maximize the profits of BSS, and minimize total emissions from the μG. The main aim of the presented optimization strategy is to achieve the best possible balance between reducing expenses and lessening the environmental impact of greenhouse gas emissions. The krill herd algorithm (KHA) is used to find the optimal solutions while considering various nonlinear constraints. To demonstrate the validity and effectiveness of the proposed solution, the study utilizes the KHA and compares the obtained results with those achieved by other optimization methods. It was demonstrated that such integration significantly enhances the μG's operational efficiency, reduces operating costs, and minimizes environmental impact. The findings underscore the viability of combining EV charging infrastructure with renewable energy to meet the increasing energy demand sustainably. The novelty of this work lies in its multi-objective optimization approach, the integration of EV charging and BSS in μGs, the comparison with other optimization methods, and the emphasis on sustainability and addressing energy demand through the utilization of renewable energy and EVs.

Performance analysis of GaN based dual active bridge converter for electric vehicle charging application

<p><span>The research work proposes a Gallium Nitride (GaN) based dual active bridge (DAB) converter for electric vehicle (EV) charging applications. The wide bandgap semiconductor device, GaN is implemented in the DAB topology of an Isolated Bidirectional DC-DC converter (IBDC). GaN-based DC-DC converters lead to higher efficiency, smaller size, faster charging, and reduced heat generation improving the overall performance of the EV charging system. The performance characteristics of GaN based DAB converter is analyzed both in simulation and hardware for EV charging application. The same analysis is extended to a Si based DAB converter and comparative results are presented. A 14.25 kW GaN based DAB and <br /> 10.5 kW Si based DAB is designed and evaluated using LTspice XVII software and a scaled-down prototype of 0.612 kW GaN based DAB and 0.25 kW Si based DAB is presented for experimental validation. Result analysis under similar operating conditions indicated an improvement of 36% more output power transfer on the GaN based DAB over the traditional Si based DAB. The developed prototype showcased improved levels of power, voltage, and current under same operating conditions. The power transmission in the developed DAB based IBDC topology is controlled using the single-phase-shift (SPS) control strategy.</span></p>

High current density DC-DC converter with Modified PI controller for fast charging applications in EVs

As electric vehicles (EVs) become increasingly prevalent, the demand for efficient and high-performance DC–DC converters in the charging infrastructure is paramount. Electric vehicles, powered by rechargeable batteries or fuel cells, hence is necessary to have a cost-effective and efficient battery charger to deliver the consistent output current needed for the designated EV's battery. This paper adds a new and more effective approach of design and control of a DC–DC converter with bidirectional capability appropriate for incorporation in EV charging systems aimed at enhancing the current density and control issues inherent in the charging /discharging process. It appears to provide the necessary high current density besides battery out as soon as possible and also to impose an unimportant overshooting of the charging time for demanded lithium-ion battery system while charging it. The converter circuit contains the following equipment in its construction include single phase AC voltage source, linear transformer, passive component that includes the inductor and capacitor and bridge rectifier. Usually, Simulink/MATLAB is used for the purpose of various simulations. Using the MATLAB simulation the design of the concept system offered in this proposal has been proved. Monitored the current in amperes that the battery charger is supplying to the battery, closely observed the condition and voltage of the battery.

Computer Vision Applications in Intelligent Electric Vehicle Charging Infrastructure

The study examines the use of computer vision technologies into intelligent electric vehicle (EV) charging infrastructure. The objective is to increase station capabilities, maximize resource usage, and enhance user experiences. An examination of the data from charging stations indicates that there are differences in their capacities and capabilities. Certain stations can handle a greater number of cars at the same time because they have higher power outputs and numerous charging connections. The vehicle identification data illustrates the efficacy of computer vision in precisely recognizing various electric vehicle types, hence optimizing authentication procedures for efficient charging. An analysis of charging session data reveals variations in energy use and durations across sessions, underscoring the impact of charging practices on the utilization of charging stations. An examination of use reveals discrepancies in the number of sessions and energy usage among stations, highlighting the need for adaptive infrastructure. Percentage change study management solutions for demonstrates the fluctuating patterns of resource usage, emphasizing the need for flexible resource allocation techniques. The results emphasize the significant impact that computer vision may have on improving the efficiency and flexibility of electric vehicle charging infrastructure. The research highlights the significance of optimizing the allocation of resources, improving algorithms for various contexts, and applying adaptive solutions for optimal management of charging infrastructure. In essence, the study helps to further our knowledge of how computer vision contributes to the development of intelligent EV charging systems. It provides valuable insights into improving the efficiency of infrastructure and enriching user experiences in the field of electric mobility.

Design and implementation of magnetically coupled inductive power transfer system for electric vehicle charging applications

A research paper or proposal on designing a 1.6 kW Resonant Inductive Power Transfer (IPT) system for electric vehicles (EVs). Design, Modeling, and Analysis of a 1.6 kW Resonant IPT System for EVs. To Enhance Design Performance: Improve the efficiency and effectiveness of power transfer compared to traditional EV charging systems. Conduct Loss Analysis and Analyze and minimize losses associated with the IPT system. The Advantage Highlight advantages of the proposed system over existing EV charging methods. Methodology, Integration with AC Grid: Despite EV systems being connected to the grid, this research proposes further integration and improvement using resonant (Compensated Network) circuits within IPT systems. Resonant Circuit Utilization: By matching the supply frequency with the circuit’s resonant frequency, optimal performance is achieved, addressing current IPT system drawbacks. Implementation Steps, Simulation: Evaluate primary and secondary circuits through simulation. Component Selection: Determine component values based on derived equations. Hardware Implementation: Construct the system in hardware based on simulation results. Feasibility Testing: Validate calculations through simulation and practical hardware testing. Contribution, this research aims to contribute to the field by demonstrating, improved performance through resonant IPT systems. Feasibility of integrating such systems into EV applications. Practical benefits over conventional EV charging methods. By leveraging resonant circuits in IPT systems, this study aims to demonstrate enhanced performance and efficiency suitable for EVs, thereby contributing to the advancement of EV technology and grid integration. This structured summary encapsulates the key aspects and goals of the research paper as described.

Solar wireless electric vehicle charging system

vehicles (EVs) are increasingly prevalent on roads today. These vehicles have demonstrated their effectiveness to minimize travel costs through transitioning from traditional fuel sources to electricity, that is notably more cost-efficient, alongside the associated environmental benefits. The primary aim is to implement a charging system that accommodates extended vehicle usage by applying higher charging rates for prolonged periods. Presently, the prevailing charging infrastructure for EVs involves conductive methods where the vehicle connects to a charging station; however, this process typically takes longer. Advancements in technology are introducing wireless charging solutions. Inductive EV charging, a wireless alternative, eliminates the need for physical wires. This innovative approach proposes charging electric vehicles while they are in motion, eliminating the necessity for vehicles to stop for refueling. Notably, this charging mechanism operates on solar energy, obviating the requirement for an exterior source of power. The system-design encompasses the utilization of various components such as batteries, transformers, solar panels, copper coils, regulator circuits, ATmega328p controllers, AC to DC converters, and the LCD.

A Dual Receiver Inherent Hybrid CC-CV Topology With Half Active Rectifier Control Scheme for Semi-Dynamic WRIPT Electric Vehicle Charging System

A Dual Receiver Inherent Hybrid CC-CV Topology With Half Active Rectifier Control Scheme for Semi-Dynamic WRIPT Electric Vehicle Charging System

Development of wind and solar systems for power charging: An application of an electric vehicle to grid systems

<abstract> <p>In response to escalating environmental concerns driven by greenhouse gas emissions, Pakistan, amid accelerated climate change and deteriorating air quality, struggles with power crisis. Our purpose of this research was to develop a pivotal strategy to address the power crisis and provide clean transportation facilities by involving power transitioning from fossil fuel vehicles to electric vehicles (EVs). We aimed to establish EV charging stations powered by renewable sources like solar and wind energy using grid to vehicle (V2G) mechanism. Utilizing MATLAB Simulink, an optimal electric vehicle charging system with a Level 2 fast charging mechanism was designed, aiming to significantly reduce greenhouse gas emissions from both the transportation and energy sectors. This framework aligned with global trends in climate change mitigation, providing developing countries like Pakistan with a practical solution. The results indicated a 10-kW, AC power output at 240 V coupled with an ideal 50 kWh EV battery rating, which was achieved for EV charging. The output parameters, including current voltage and power output of solar PV, micro wind, and battery levels, were used before and after the incorporation of a boost converter. Consequently, the application of a boost converter and proportional integral (PI) controller resulted in low overshoot and steady state output parameters of the proposed system. Also, the battery backup helped to optimize the power output for load driven EVs.</p> </abstract>

Recent Results in Shielding Technologies for Wireless Electric Vehicle Charging Systems

Recent Results in Shielding Technologies for Wireless Electric Vehicle Charging Systems

Enhanced Power Quality Control in Microgrid-Assisted Electric Vehicle Charging Systems Using ATOGI and CIDPC

Enhanced Power Quality Control in Microgrid-Assisted Electric Vehicle Charging Systems Using ATOGI and CIDPC

Recognizing Multitype Misalignments in Wireless EV Chargers With Orientation-Sensitive Coils: A Data-Driven Strategy Using Improved ResNet

In wireless electric vehicle charging systems, misalignments between ground-assembled transmitter and vehicle-assembled receiver are undesirable but inevitable, which may cause efficiency deterioration and even thermal risks. The recognition of horizontal misalignment, including that in the longitudinal and lateral direction, has been made gradual progress by previous works. While yaw angle, with rare attention, can also degrade the charging performance, especially for those employing non-centrosymmetric coupling coils, such as rectangular coils. In this paper, a data-driven strategy based on improved ResNet is proposed to recognize the above multi-type misalignments simultaneously, which is accurate, reliable, and of practical and general value. Large-scale data is sampled using the proposed detection coils by double-group cooperation, which features high sensitivity to the misalignments of all kinds, especially yaw angle. Benefit to the compression technique in the pre-processing phase, the number of training data and labels can be successfully reduced by 3/4. As the core algorithm of the overall strategy, the adaptive channel parameter recalibration ResNet (ACPR-ResNet) can effectively perceive slight differences among similar input samples and map them to proper labels. This is achieved by an adaptive operation of nonlinear transformation and recalibrated importance of channel features during the training process. The effectiveness of the proposed strategy is verified experimentally using a 6.6-kW prototype. Within the 24×24 cm range, 95.2% of the test cases have an error of less than 1.7 cm when recognizing horizontal misalignment, and 91.7% of the test cases have an error of less than 1.5° when recognizing yaw angle.

Solar wireless electric vehicle charging system

Solar wireless electric vehicle charging system

An Inherent CC-CV Charging Architecture for Dual Receiver Semi-Dynamic Resonant Inductive Wireless Electric Vehicle Charging System

An Inherent CC-CV Charging Architecture for Dual Receiver Semi-Dynamic Resonant Inductive Wireless Electric Vehicle Charging System