EV Charging Research Articles

An Improvised Modulation and Control Approach for Dual Active Bridge DC–DC Converter System

Aimed at the control and modulation of dual active bridge bi-directional dc (DAB-BIDC) converter, an unconventional approach is applied to explore its effect in symmetrical wave-based isolated dc-dc converters. The existing control schemes of DAB-BIDC converter with unified or optimal phase shift (UPS/OPS) modulation have the constraints like complex control schemes, light load efficiency, current stress, and reactive power. Since a 50 Hz, grid-connected conventional converter system uses the sinusoidal pulse width modulation method to minimize the requirement for passive filters. Similarly, this work investigates the same analogy for the high-frequency (HF) symmetrical wave converters to get effective modulation and control scheme for the DAB-BIDC converter. Furthermore, the proposed sinusoidal pulse width-phase shift (SPW-PS) modulation scheme has been implemented by the optimally derived control parameters using Lagrange's Multiplier Method (LMM) to minimize the reactive power flow and current stress reduction at the HF link. Therefore, the DAB-BIDC converter with the proposed modulation and control approach can be used for EV charging and solid-state transformers applications. Finally, the proposed work is validated using MATLAB simulation and experimental setup having turn ratio 36/12 V, fundamental frequency 5-kHz, and switching frequency 100-kHz for the experimental validation using OPAL-RT.

Cost-benefit analysis of a hydro-solar microsystem with Archimedean screw hydro turbine sized for a prosumer building

This work aims to identify a cost-effective solution for improving the energy performance of a grid-connected prosumer, possibly equipped with electric vehicle chargers. The solution is based on a small-scale energy system based on renewable energy sources (RES). The system is equipped with an Archimedes Screw Turbine (AST) and photovoltaic panels. Energy storage in batteries is also considered. A simple yet efficient method for sizing the AST is proposed. A cost-benefit analysis of the small-scale energy system is performed for six case studies covering different combinations of energy consumers. Three economic scenarios are considered for each case study. The results suggest that the AST-based solution leads to reasonable costs for the prosumer and less impact of energy price fluctuations. Also, if EV chargers are used, their consumption can be covered directly by RES.

Assessing the Nationwide Benefits of Vehicle–Grid Integration during Distribution Network Planning and Power System Dispatching

The diffusion of electric vehicles is fundamental for transport sector decarbonization. However, a major concern about electric vehicles is their compatibility with power grids. Adopting a whole-power-system approach, this work presents a comprehensive analysis of the impacts and benefits of electric vehicles’ diffusion on a national power system, i.e., Italy. Demand and flexibility profiles are estimated with a detailed review of the literature on the topic, allowing us to put forward reliable charging profiles and the resulting flexibility, compatible with the Italian regulatory framework. Distribution network planning and power system dispatching are handled with dedicated models, while the uncertainty associated with EV charging behavior is managed with a Monte Carlo approach. The novelty of this study is considering a nationwide context, considering both transmission and distribution systems, and proposing a set of policies suitable for enabling flexibility provision. The results show that the power and energy demand created by the spread of EVs will have localized impacts on power and voltage limits of the distribution network, while the consequences for transmission grids and dispatching will be negligible. In 2030 scenarios, smart charging reduces grid elements’ violations (−23%, −100%), dispatching costs (−43%), and RES curtailment (−50%).

ANFIS control of four-quadrant DC/DC chopper for wireless EV charging

ANFIS control of four-quadrant DC/DC chopper for wireless EV charging

Comparative Analysis for Off-Board Vienna Rectifier Electric Vehicle Charger Controlled by VOC and DPC Techniques

Electric vehicle charging stations are generally composed of AC-to-DC and DC-to-DC converters. Many topologies of converters, used for both on-board and off-board EV chargers, have been proposed by the researchers. The off-board Vienna rectifier EV charger is the focus of our work. This EV charger should be controlled for adjusting the system outputs at desired references. Among several control methods existing in the literature, the voltage-oriented and direct power control techniques are selected to control the Vienna rectifier. The aim of this paper is to present a comparative analysis for an Off-board Vienna rectifier controlled individually by the previous mentioned control techniques in order to charge the battery of an electric vehicle from the national grid. A three constant current values of 60A, 80A, and 100A, are imposed to the EV battery as reference currents using PI controllers. The comparison is based on the waveforms of three-phase grid voltages and currents, battery voltages, state of the charge of the battery, and the elapsed time of simulation. The total harmonic distortion (THD) of one phase of the input current at the case of 100A is measured using the fast Fourier transform tool of Matlab/Simulink software which employed for modeling and performing the simulation.

Emissions generated by electric vehicles in the 9-500 kHz band: Characterization, propagation, and interaction

Electric Vehicle Charging Processes (EVCPs), due to the involved power electronics with high-switching frequencies, generate high-amplitude emissions that could have a negative impact on Power Quality (PQ) and Narrowband Power Line Communications (NB-PLC) systems. In this context, this paper deals, first, with the frequency and time characterization of the disturbances generated by four EVCPs in the 9-500 kHz frequency range. The study is based on measurements carried out in a controlled Low Voltage (LV) grid. For this purpose, a novel procedure for the frequency and time characterization is proposed. The frequency characterization is based on the calculation of a set of parameters, which allows evaluating not only the amplitude of the disturbances in the frequency band under analysis, but also their spectral distribution. The time variability is characterized by means of a Fast Fourier Transform (FFT) analysis that leads to a simplified model to evaluate the time-dependent behavior of the disturbances, which shows a sub-cycle periodic pattern of the emissions in the frequency band of interest. Second, the propagation of the previously characterized emissions is analyzed, concluding that they propagate several meters through the LV grid. Although in most cases the disturbances are attenuated with distance, there might be resonances that lead to higher amplitudes at an electrical point distant from the source of the emissions. Finally, the influence of the simultaneous charging of several EVs is studied. The results show that, in general, the amplitudes correspond to the superposition of the individual disturbances, in addition to intermodulation products due to the switching frequencies of the inverters.As a conclusion, the high amplitude time-varying emissions, together with their capacity for propagation and interaction, are a matter to be analyzed due to their influence on PQ and their potential degradation of the performance of PLC in the frequency band from 9 kHz to 500 kHz.

Modelling Public Intentions to Use Innovative EV Chargers Employing Hybrid Energy Storage Systems: A UK Case Study Based upon the Technology Acceptance Model

The current study investigates public intentions to use an innovative, off-grid renewably powered EV charging technology called FEVER (Future Electric Vehicle Energy networks supporting Renewables). We report the findings of a questionnaire-based survey (QBS) conducted at a zoo in the south of England, exploring the prospect of demonstrating FEVER. The QBS was designed around a context-specific technology acceptance model (TAM) and administered both face-to-face (n = 63) and online (n = 158) from April to May 2023. The results indicate that most participants were willing to pay to use FEVER, particularly where revenue would benefit the zoo. The participants agreed they intended to use the chargers, and that they would be useful and easy to use. The participants agreed that there would be normative pressure to use the chargers, but that their use would be enjoyable. Of greatest concern was that the chargers would be blocked by others. The participants were ambivalent about concerns over charging duration and charge sufficiency. Structural equation modelling confirmed that the context-specific TAM explained 58% of people’s use intentions. The core relationships of the TAM were confirmed, with ‘perceived usefulness’ additionally predicted by subjective norms and ‘perceived ease of use’ additionally predicted by anticipated enjoyment. Of the other variables, only concern that the chargers would be blocked was retained as a marginal predictor of ‘perceived ease of use’. The implications of these findings for the co-design and demonstration of FEVER are discussed.

Spatial-temporal Distribution Prediction of Electric Vehicle Charging Load Considering Vehicle-road-station-network Integration

Aiming at the problem of inaccurate prediction of spatial-temporal distribution of electric vehicle charging load due to insufficient consideration of vehicle-road-station-network interaction, a prediction model of spatial-temporal distribution of electric vehicle charging load based on gravitation model was proposed. Firstly, considering road network traffic flow and ambient temperature, the relationship between external environment and energy consumption of electric vehicles is analyzed. Secondly, considering the influence of external environmental factors such as temperature on user travel, a travel chain model based on travel intention modification is established. Finally, the selection model of EV charging station based on gravitation model is established. The simulation results show that the proposed model can take into account the interaction of EV, road network, charging station and power grid, and accurately calculate the spatio-temporal distribution of EV charging load, and analyze the characteristics of EV charging demand load in multi-regions.

Predictive power fluctuation mitigation in grid-connected PV systems with rapid response to EV charging stations

Currently, renewable energies and electric vehicle charging stations are essential for energy sustainability. However, the variable generation from renewable sources, such as photovoltaic systems, can lead to power peaks that impact the stability of the grid. This challenge is exacerbated by the increasing demand in fast-charging stations. Addressing these demand peaks is crucial to ensure the stability of the electrical grid. This paper introduces the predictive-flex smoother, an innovative method designed to mitigate power fluctuations in grid-connected photovoltaic systems while optimizing energy management in electric vehicle charging stations. The predictive-flex smoother method incorporates a hybrid energy storage system comprising supercapacitors and vanadium redox flow batteries to respond rapidly to electric vehicle charging stations demands, enhance grid electricity purchase optimization, and improve energy quality delivery. The proposed method integrates two control strategies: photovoltaic fluctuation reduction strategy and peak demand reduction strategy for electric vehicle charging stations. By leveraging prediction algorithms and machine learning techniques, the predictive-flex smoother method achieves precise power fluctuation forecasts, allowing efficient utilization of supercapacitors and vanadium redox flow batteries to smooth photovoltaic power fluctuations and reduce electrical vehicles peak demand. Comprehensive experimental investigations and simulations validate the method's performance under various operational conditions. The results demonstrate the effectiveness of the predictive-flex smoother method, significantly improving the quality of power delivered to the grid while reducing costs. The experimental platform, validates the real-time response of the proposed method, with response times under 500 ms. The experimental results further confirm the efficiency of the method in power smoothing and charging strategies with varying electrical vehicles models and connection coefficients.

Modelling of PV sources & techno-economic of analysis of hybrid system for EV charging in residential buildings

Modelling of PV sources & techno-economic of analysis of hybrid system for EV charging in residential buildings

Robust and fast control approach for islanded microgrid system and EV charging station applications

Robust and fast control approach for islanded microgrid system and EV charging station applications

Finding Attractive Electric-Vehicle-Charging Locations with Photovoltaic System Integration

The rise of electric mobility poses a challenge and an opportunity for the housing industry to provide charging infrastructure. The housing industry can take advantage of its large roof areas to install photovoltaic (PV) systems and use the electricity generated to charge electric vehicles. This study explores how the charging demand can be allocated to specific locations based on socio-economic parameters and determines whether PV integration is economically viable for EV charging. Two models are used, one with extensive spatial and traffic data to determine the charging demand for over 300 locations, and another with a time-series-based approach for four specific locations to analyze the seasonal dependencies. The results indicate that PV integration is economically advantageous when electricity purchase prices exceed 0.15 EUR/kWh. Higher electricity prices can lead to significant additional profits through PV integration. Slow charging and charging during the day are beneficial, as they increase self-consumption, making PV systems economically viable. However, fast-charging infrastructure should be combined with PV storage systems for effective PV integration.

Nonisolated Three-Phase Current DC-Link Buck–Boost EV Charger With Virtual Output Midpoint Grounding and Ground Current Control

Non-isolated three-phase AC/DC converter concepts facilitate more compact and more efficient realizations of future EV chargers. However, without the galvanic isolation and/or high common-mode (CM) impedance provided by an isolation transformer, non-isolated chargers must employ other means to suppress CM leakage currents to ground sufficiently and to prevent nuisance tripping of mandatory residual current devices (RCDs). Typically, the required EMI filters reduce high-frequency (HF) CM leakage currents to uncritical values. However, low-frequency CM voltages, e.g., generated by third-harmonic injection, may drive significant LF CM currents through the parasitic capacitances of the DC output (including the battery pack) to protective earth (PE). Therefore, considering a non-isolated three-phase buck-boost current DC-link PFC rectifier system that consists of a buck-type current-source rectifier (CSR) stage and a three-level boost-type DC/DC-stage, this paper first proposes a virtual grounding control (VGC) of the DC output voltage midpoint. VGC employs the DC/DC-stage to compensate the LF (third-harmonic) CM voltage inherently generated by the CSR-stage, and thus controls the LF CM voltage between the DC output midpoint and PE to zero. This enables further a direct connection of the DC output midpoint to PE, where an additionally proposed ground current control (GCC) ensures near-zero LF CM leakage current. The proposed concepts are verified with a 10kW hardware demonstrator (power density of 6.4 kW/dm3 or 107.5 W/in3, full-load peak efficiency of 98.5%) considering TT (Terra-Terra) and TN (Terra-Neutral) grounding systems. With a direct connection of the DC output midpoint to PE, GCC limits the LF CM leakage current to < 6mA RMS, i.e., significantly below typical RCD trip levels, and, using the human-body impedance model according to UL 2202, achieves a test voltage of 110mV that is clearly below the most stringent limit (250 mV) of the standard.

A dataset for multi-faceted analysis of electric vehicle charging transactions

This study discloses a dataset of electric vehicles’ (EVs’) charging transactions at a scale for multi-faceted analysis from both EV charger and user perspectives. The data comprises whole sessions that occurred during a charging operation company’s annual commercial operation period, specifically including identifiers and charger location categories. For data acquisition, machine-to-machine wireless communication system with proper retransmission for interruption is utilised. The entire dataset is newly collected and is available with 72,856 sessions from 2,337 EV users and 2,119 chargers. The dataset can be used in a variety of ways for the functioning of power systems and markets, including EV charging service businesses, charger installation siting, demand transaction market design, and long-term investment planning of EV-related infrastructure.

Electric vehicle charging infrastructure deployment: A discussion of equity and justice theories and accessibility measurement

The ultimate goal of this discussion paper is to inject more rigorous consideration and measurement of equity and justice issues into research and policymaking around the deployment of electric vehicle charging infrastructure (EVCI). To achieve this, we first examine equity and justice theories in transportation and their alignment with the concept and measurement of accessibility. Equity and justice frameworks abound (e.g., horizontal vs. vertical equity, ladder of justice standards, theories of equity and justice from economic and political philosophy), but all tend to offer different normative perspectives on how to distribute resources among members of society. The accessibility concept is a promising tool for operationalizing these theories, because it explicitly measures opportunities and can be applied to quantify existing disparities or the differential or aggregate outcomes of policies. Next, we interpret these justice/equity frameworks and accessibility measurement in the context of EVCI deployment and literature on disparities in access to charging stations. We discuss which population subgroups to analyze, how to quantify EV charging opportunities and activities, and what to include in travel time and cost calculations. Our paper concludes with additional discussions on community engagement, supply vs. demand, externalities of EVCI, and other issues. A key takeaway for policymakers and researchers is to clarify the ethical perspective being applied in EV analyses and policy, as different equity/justice theories yield diverse responses to how policies should address disparities, including those related to access to EV charging infrastructure.

Simulation and Fabrication of Hybrid Electric Bicycle with Multi Charging Mode

The use of electric vehicles actively contributes to environmental conservation. Lack of EV charging infrastructure is one of the most common challenges associated with the electric vehicles. The conventional method for the electric propulsion system deals with the single mode of charging techniques. The alternative battery charging techniques helps to enhance the usage of electric vehicles. In this work hybrid electric bicycle is designed with multi charging method. In addition to the conventional wall charger, a solar panel and dynamo is used to charge the battery. Increasing the performance and efficiency by means of BLDC motor. The entire propulsion system is connected with the PI controller which calculate the speed and relevant voltage needed for the drive. The performance of the proposed method is evaluated through simulation using MATLAB/ Simulink software.

Smart AC-DC Coupled Hybrid Railway Microgrids Integrated with Renewable Energy Sources: Current and Next Generation Architectures

In recent years, there has been increasing interest in integrating the smart grid concept into railway networks, which has been driven by the need to enhance energy efficiency and reduce air pollution in such energy-intensive systems. Consequently, experts have actively sought innovative solutions with which to tackle these challenges. One promising strategy involves integrating renewable energy sources (RESs), energy storage systems (ESSs), and electric vehicle charging stations (EVCSs) into current electric railway systems (ERSs). This study begins by examining the concept of implementing smart grids in railway systems through bibliometric analysis. It then delves into the realization of a hybrid railway microgrid (H-RMG) designed to enhance power flow capacities, improve energy efficiency, and address power quality issues in traditional AC railway networks. This paper introduces various future AC–DC-coupled hybrid railway microgrid (ADH-RMG) architectures centered around a shared DC bus acting as a DC hub for upgrading conventional AC railway systems utilizing interfacing static converters. Through an exploration of different possible ADH-RMG configurations, this research aims to offer valuable insights and a roadmap for the modernization and reconstruction of existing railway networks using smart grid technologies. The integration of RESs and EV charging infrastructures within the ADH-RMG concept presents a promising pathway toward establishing more sustainable and environmentally friendly railway systems.

Development of a prediction-based scheduling control strategy with V2B mode for PV-building-EV integrated systems

Extending the energy boundary from the building-integrated photovoltaic to E-mobility is an effective alternative to further improve the integrated energy system performance. In this study, a new prediction-based scheduling control (PSC) strategy was developed considering vehicle-to-building mode for PV-building-EV integrated systems. The control strategies consisted of three components, model predictive control (MPC), simple operation mode, and schedule control. First, the MPC was based on the weather forecast, while the calculated daily renewable power generation and building energy consumption were used for mode selections. Second, the simple operation mode was based on system operation using conventional methods. Third, the developed scheduling control strategy was activated based on the periods of the day, involving different operating modes (e.g., V2B mode, renewable-to-building mode, etc.). Overall, the developed PSC can effectively improve energy performance and achieve cost savings. Validation tests were conducted for an office building, whose results showed higher renewable energy penetration and renewable power use efficiency at 9.56% and 30.48%, respectively. The levelized cost of energy (LCOE) values for building energy consumption and EV charging decreased to 0.4561 CNY/kWh and 0.6304 CNY/kWh, respectively. It indicated that the annual cost savings of building energy consumption and EV charging decreased by 16.5% and 42.7%, respectively.

Development of renewable energy fed three-level hybrid active filter for EV charging station load using Jaya grey wolf optimization

This work develops a hybrid active power filter (HAPF) in this article to operate in conjunction with the energy storage system (ESS), wind power generation system (WPGS), and solar energy system (SES). It employs three level shunt voltage source converters (VSC) connected to the DC-bus. Optimization of the gain values of the fractional-order proportional integral derivative controller (FOPIDC) and parameter values of the HAPF is achieved using the Jaya grey wolf hybrid algorithm (GWJA). The primary objectives of this study, aimed at enhancing power quality (PQ), include: (1) ensuring swift stabilization of DC link capacitor voltage (DCLCV); (2) reducing harmonics and improving power factor (PF); (3) maintaining satisfactory performance under different combinations of loads like EV charging load, non linear load and solar irradiation conditions. The proposed controller's performance is evaluated through three test scenarios featuring different load configurations and irradiation levels. Additionally, the HAPF is subjected to design using other optimization algorithms such as genetic algorithm (GA), particle swarm optimization (PSO), and ant colony optimization (ACO) to assess their respective contributions to PQ improvement.

Queueing analysis of imbalance between multiple server pools with an application to 3-phase EV charging

We consider systems where multiple servers operate in parallel, with a particular feature: servers are classified into d classes, and we wish to keep approximate balance between the load allocated to each class. We introduce a relevant imbalance metric, and study its behavior under stochastic demands with different task routing policies. For random routing, we analyze two cases of interest, depending on whether capacity constraints are operative: we obtain expressions for the stationary distribution and analyze the scaling behavior of our metric as a function of system size. Subsequently, we analyze active routing to the least loaded class, obtaining sharp bounds for the imbalance metric. As a practical application, we study the problem of imbalance between d = 3 phases, for the service of electrical vehicle charging. We show the engineering relevance of our imbalance metric in this context, and validate the theoretical results with simulations and real traces from EV charging data.