Vehicle Charging Research Articles

A novel battery management scheme for critical loads

AbstractThis article proposes a novel battery management system (BMS) to ensure uninterruptible power delivery to a 48 V DC bus used for electric vehicle charging stations, data centers, telecommunication systems, and critical care units such as hospitals. The proposed BMS facilitates constant current and constant voltage charging to maintain optimal battery performance during normal operation. This BMS is designed for effective control, monitoring and protection of two lead‐acid battery units to form battery energy storage system (BESS). Furthermore, it is capable of isolating batteries in abnormal conditions and operates them independently to provide reliable supply at output terminals with full capacity. The system utilizes a 30 V DC source derived from AC mains or solar photovoltaic system. This supply is used to charge the BESS and also supply to the load. In the event of failure of 30 V supply, it seamlessly transits to BESS mode to supply power to boost converter to maintain constant 48 V DC output at load terminal. The proposed system architecture not only enhances power reliability but also improves overall system efficiency, making it well‐suited for critical applications require continuous and stable power supply. Simulation studies using Matlab/Simulink and analytical results using TINA (Tool kit for Interactive Network Analysis) are presented to show that 48 V DC supply is maintained at output terminals during failure of input 30 V DC source or failure of one battery unit.

Comparing costs and climate impacts of various electric vehicle charging systems across the United States

The seamless adoption of electric vehicles (EVs) in the United States necessitates the development of extensive and effective charging infrastructure. Various charging systems have been proposed, including Direct Current Fast Charging, Battery Swapping, and Dynamic Wireless Power Transfer. While many studies have evaluated the charging costs and greenhouse gas (GHG) intensity of EVs, a comprehensive analysis comparing these systems and their implications across vehicle categories remains unexplored. This study compares the total cost of ownership (TCO) and GHG-intensity of EVs using these charging systems. Based on nationwide infrastructure deployment simulations, the change to TCO from adopting EVs varies by scenario, vehicle category, and location, with local fuel prices, electricity prices, and traffic volumes dramatically impacting results. Further, EV GHG-intensity depends on local electricity mixes and infrastructure utilizations. This research highlights the responsiveness of EV benefits resulting from technology advancements, deployment decisions, and policymaking.

A methodology for optimal placement of energy hubs with electric vehicle charging stations and renewable generation

The use of electric vehicles and renewable energy sources can significantly contribute to the reduction of pollution levels, fostering a cleaner and more sustainable environment. In addition to their positive environmental impact, electric vehicles can also serve as energy storage units, enabling a bidirectional energy flow between the vehicles and the grid. Despite these promising prospects, a disjointed approach to charging infrastructure planning overlooks the synergies between the energy and transportation ecosystem. This calls for a holistic and coordinated approach to infrastructure development that harnesses the benefits emerging from the convergence of electric vehicles, renewable energy, and transport planning. This paper presents a methodology for the optimal placement of future Energy Hubs for electric vehicle charging and renewable generation. The methodology uses data from open-source datasets involving renewable energy sources, traffic density, charging patterns, road topology, and land use. The optimization problem is formulated as a multi-objective linear programming problem, with the objectives of minimizing the number of Energy Hub units, minimizing electric vehicles charging radius coverage and distance from power substations, and maximizing energy generation. The methodology is demonstrated through an application in Trondheim, Norway, which produces a Pareto front for decision-makers to evaluate the best trade-offs between objectives.

A Multiagent Framework for Electric Vehicles Charging Power Forecast and Smart Planning of Urban Parking Lots

A Multiagent Framework for Electric Vehicles Charging Power Forecast and Smart Planning of Urban Parking Lots

Optimal Bivariate Control Strategy of Multistage Constant Current Charging for IPT-Based Wireless Electric Vehicle Charging

Optimal Bivariate Control Strategy of Multistage Constant Current Charging for IPT-Based Wireless Electric Vehicle Charging

Electric Vehicles Charging Services Perspectives and Challenges

Abstract The year 2023 marked another breakthrough in electromobility. Customers accept electric powertrain; sales of battery electric vehicles and plug-in hybrid vehicles are booming and public charging infrastructure follows the similar pace. However, the leading European independent charging stations operators, despite the significant public funding utilized for financing their expansion activities are still experiencing losses, as a result of their operation. Generally, current research work in area of electric vehicle charging is rather focused on specific and rather technical aspects of charging infrastructure operations, like optimization of charger locations, connection to energy networks and operational excellence. Very few authors are focusing on core business essentials of charging infrastructure operation, in particular on sustainability of their operations. Within this paper author conducted financial analyses of selected charging infrastructure operator in Europe, compared the conclusions with its peers. Furthermore, this paper has an ambition to perform synthesis (after thorough review and analysis of relevant information sources) of different aspects of e-mobility ecosystem to conclude innovative recommendations. The main result of this paper is the recommendation for the charging infrastructure operators to adjust their strategies and respective business models in terms to make a move towards slow charging world, by building and operating Vehicle to Grid equipped infrastructure as a supplement to fast chargers’ network. Sooner charging infrastructure operators will develop their competences in Vehicle to Grid world the better, mainly for two reasons. Firstly, it is very probable that Vehicle to Grid market will jump on fast track very soon. Not only from technology point of view, but also from services provided/expected from customers. Secondly, in Vehicle to Grid connected ecosystem lays needed tens or even hundreds of millions EUR opportunities which will be waiting for Electric Vehicle´s owners and any subjects which can facilitate and instrument interconnection between energy network’s needs – auxiliary services, storage of electricity, integration of renewable energy sources and traction batteries of Electric Vehicles.

Wireless Power Transfer System Model Reduction with Split Frequency Matching

Reduced-order dynamic models of wireless power transfer (WPT) systems are desired to simplify the analysis and design of power control, phase synchronization, and maximum efficiency tracking. The reduced-order dynamic phasor model is a good choice because of its straightforward physical meaning and concise mathematical formula. However, the model relies on the assumption of loose coupling and loses accuracy when the coupling becomes stronger. In this paper, a model reduction method with split frequency matching is proposed to improve model accuracy under relatively strong coupling conditions, which is suitable for most short-distance WPT applications, such as wireless electrical vehicle charging. Split frequency matching is achieved through a pair of conjugate equivalent mutual inductances, which are derived from the asymmetry characteristics of the full-order dynamic phasor model in the positive and negative frequency domains. The proposed model retains the advantages of the existing model while significantly improving the accuracy under strong coupling conditions. Its characteristics are verified by comparing the experimental results and model predictions under both large step changes and small-signal perturbations.

Simultaneous Wireless Power and Data Transfer for Electric Vehicle Charging: A Review

Simultaneous Wireless Power and Data Transfer for Electric Vehicle Charging: A Review

Sufficiency of level 1 charging to meet electric vehicle charging requirements

As electric vehicle (EV) deployment increases there is increasing attention to meeting charging needs. We analyze 13 months of real world driving and charging data for 129 battery electric vehicles in Calgary, Canada to evaluate the potential for home-based level 1 charging to deliver the energy needed to satisfy observed driving demand. We find that 29% of vehicles can have their energy needs met entirely with level 1 charging. A further 53% of vehicles in our sample require only occasional supplementary level 3 charges and only a small minority of vehicles require 12 or more supplementary level 3 charges across the sample period. Across all vehicles the median ratio of charge energy that can be shifted to level 1 charging is 0.99. These results challenge the assumption that level 2 charging access is required for convenient operation of EVs and offer a partial solution to enable broader EV charging access and reduce the need for near term electrical panel or distribution grid upgrades.

Optimal hybrid power plants for electric vehicle charging demand

Transmission constraints, increasing motivations to decarbonize, and concerns over peak electric vehicle (EV) load impacts on local grids have driven electric customers to consider behind-the-meter, hybrid power plant generation and storage at the distributed-grid level for EV charging. In this study, we develop capabilities to optimize hybrid power plant component capacities for EV charging. We then demonstrate these capabilities in a case study for Boulder, Colorado, using public EV charging data as well as wind and solar resource data.Our results show system designs that balance the cost of energy with load-meeting and peak shaving performance. Within the case study, systems designed for wind, solar photovoltaic (PV), and storage resulted in lower cost of energy than those optimized for PV and storage only. This indicates that in areas where wind resource exists, hybrid power plants that include wind, PV, and battery assets can better meet EV charging loads (including peak loads that are prone to overloading local grids) than PV and battery assets alone. Future work to address limitations in this paper include extending cost modeling to include performance losses (e.g., based on operations or weather) and charging station costs to estimate levelized cost of charging, and quantifying uncertainty and error in our aggregation methods for estimating EV charging loads at the hourly timescale.

Research on the analysis strategy of electric vehicle charging demand based on multi-correlation daily scenario generation

Abstract With the continuous increase of the penetration rate of OFELECTRIC vehicles, their high random charging loads exert a more significant effect on the stability of the electrical system. Simultaneously, the past charging patterns of electric vehicles indirectly influence the possible future charging activities of these vehicles. Therefore, in order to characterize the correlation between the predicted daily charging behavior of electric vehicles and its historical daily charging behavior, this article uses scene generation theory to fully mine the original multi-correlation Internal characteristics of electric vehicle charging behavior among the original multi-correlation day charging scenario set (OMCDCSS), generating massively generating multi-correlation day charging scenarios (GMCDCS) similar to the probability distribution of OMCDCSS. Secondly, the related scene set (RSS) is screened in the generation of multi-correlation day billing scenario (GMCDCSS) on the basis of weighted Spearman rank (SR). Get the forecast result of electric vehicle load interval.

A Review on the Renewable Sources Based Microgrid for Electric Vehicle Charging using various Emerging Technologies

Abstract: This review examines the integration of renewable energy sources into microgrids for electric vehicle (EV) charging, leveraging emerging technologies such as the fuzzy logic and genetic algorithm. It addresses the challenges of scaling EV infrastructure, focusing on the potential of solar, wind, and bio-energy to enhance sustainability and grid independence. The paper discusses how fuzzy logic, genetic algorithm optimize energy management and maintenance. Overall, the study advocates for a holistic approach to develop efficient, resilient, and sustainable EV charging systems through the synergistic use of renewable microgrids and advanced technologies.

Wireless Power Transfer of Electric Vehicle Battery Charging

Abstract: Wireless power transfer (WPT) is a cutting-edge technology that utilizes magnetic resonance to eliminate the need for cumbersome wires. WPT builds upon the principles of inductive power transfer and has been rapidly advancing in recent years. At power levels of kilowatts, the transfer distance can range from a few millimeters to several hundred meters, achieving an efficiency of over 90%. This progress has made WPT an attractive option for electric vehicle (EV) charging, both in stationary and dynamic settings. This study examines the latest developments in WPT as it pertains to wireless charging for EVs. By integrating WPT into EVs, challenges such as charging time, range, and cost can be effectively addressed. Battery technology is no longer a limiting factor in widespread adoption, and it is hoped that researchers will be inspired by recent advancements to further enhance WPT and expand the use of EVs.

The Parking Management System

This Parking Management System (PMS) is a comprehensive solution designed to streamline and enhance the efficiency of parking operations. Leveraging advanced technology, the system optimizes the utilization of parking spaces, reduces congestion, and improves overall user experience. Key features include real-time occupancy monitoring, automated payment processing, and smart allocation of available spaces. PMS not only ensures seamless entry and exit for vehicles but also integrates with mobile applications for convenient reservation and navigation. With a focus on sustainability, the system promotes eco-friendly practices by encouraging the use of electric vehicle charging stations and implementing intelligent traffic flow management.In summary, the Parking Management System represents a modern, user-friendly approach to address the challenges associated with urban parking, promoting a more organized and environmentally conscious urban environment. Keywords—Real-time Occupancy Monitoring, Automated Payment Processing

Solar-Powered EV Battery Charging and Payment System

Abstract: This innovative project is focused on harnessing solar energy efficiently to power electric vehicle (EV) charging stations. It employs a single-axis solar panel tracking system to follow the sun's path and optimize energy capture. The collected solar energy is stored in a high-capacity battery, ensuring uninterrupted charging, even during periods of limited sunlight. Users have the convenience of managing their accounts through a user friendly mobile app, providing real-time cost updates and secure payment options. The EV charging station maximizes the use of stored solar energy for vehicle charging, reducing reliance on the conventional power grid. Additionally, the system incorporates detailed billing and usage history features to enhance transparency and efficiency, ultimately creating an eco-conscious transportation ecosystem that integrates renewable energy and sustainable EV charging.

Solar Wireless Electrical Vehicle Charging System

Abstract: Electric vehicles are becoming more popular as an alternative to conventional gasoline- powered vehicles. In order to strengthen charging infrastructure, dynamic wireless charging (DWC) is apromising technology through which the vehicle battery can be continuously charged while the vehicle is in motion. The main challenge of the DWC system is to investigate the capability for power transfer with the variation in operating parameters in consideration of enhanced efficiency. This project proposes an innovative approach to improve the performance of dynamic wireless charging systems by investigating the magnetic coupler via finite element analysis, exploring power pulsation and mutual inductances with variations in longitudinal, lateral, and air gap distances as variable factors. In addition to this, efficiency analysis is also explored with respect to the mutual inductance and various compensation schemes. The simulation studies are carried out using computer-assisted software, i.e., MATLAB version2022b. Finally, a comparative analysis of power transferred, mutual inductance, and efficiency is presented by the compensation schemes

Analysis of dual active bridge-based on-board battery charger for electric and hybrid vehicles

This paper presents an in-depth analysis of a Gallium Nitride (GaN) Dual Active Bridge (DAB)-based on-board battery charger for electric and hybrid vehicles. It focuses on the superior efficiency and reliability of GaN-based power electronics over traditional Silicon-based systems. The study explores the implementation of the DAB topology, recognized for its bidirectional power flow and high efficiency, in enhancing vehicle charging infrastructure. Efficiency analysis, switching behavior and losses are thoroughly examined. Simulation results in PSIM software validate the theoretical predictions, showing significant improvements in operational flexibility and energy efficiency.

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

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

Resilient day-ahead microgrid energy management with uncertain demand, EVs, storage, and renewables

Managing microgrid energy presents a complex challenge due to unpredictable renewable sources, fluctuating demand, and diverse equipment like batteries, distributed generators, and electric vehicles. This paper introduces a novel two-step optimization model, the Robust Day-Ahead Scheduling for Enhanced Resilience, tailored for microgrid operations. The model addresses the integration of electronic generation, uncertain demand patterns, and small-scale renewable resources. Detailed formulations optimize microgrid energy use, including strategic battery usage, efficient electric vehicle charging, balancing device utilization, and distributed generation dispatch. This multi-faceted approach aims to minimize costs over 24 h, including energy loss, power purchases, reduced power usage, generator operation, and battery/EV expenses. Employing a column-and-constraint generation (C&CG) algorithm ensures efficient problem solving. The proposed model achieved a significant reduction in operational costs, outperforming existing methods by at least 8%. Notably, it minimized energy purchases, energy losses, and load shedding while improving voltage stability, showcasing its effectiveness in enhancing microgrid performance and resilience.

Electric Vehicle Charging Infrastructure Study for Apartment Buildings

Changes in the engine type of cars aimed at climate goals also have an impact on the habit of electricity consumption at home. Charging electric cars from the residential grid also increases the total electricity consumption of the residential building. If all apartment owners in an apartment building want to charge their electric car at the same time, this may create a situation where the main protection of the apartment building is activated. The purpose of this research is to identify possible options to avoid this problem, based on different real-life data. For example: adding an energy storage to the electrical system of an apartment building is seen as one solution. Also supplement of an energy management software to the electrical and battery bank system to enables residents to schedule and prioritize their electric car charging times to avoid simultaneous high-demand periods. This system can also be used to optimize electricity distribution and consumption in apartment buildings under volatile electricity price conditions.