DC Fast Charging Research Articles

Guest Editorial: Fast, Superfast, and Ultra-Superfast Intelligent and Smart Charging Solutions for Electric Vehicles

To Promote and meet the projected levels of electric vehicle (EV) penetration, the development of charging infrastructure, i.e., both slow charging and dc-fast charging, is essential. Slow/onboard chargers pose weight, efficiency, and thermal management challenges to the designers, while the off-board fast/superfast/ultra-superfast chargers pose efficiency, power rating, and control challenges. In particular, the installation of dc fast chargers (including fast/superfast/ultra-superfast) is also dictated by the impact on the utility grid and the existing loads. New installation or retrofitting of the existing infrastructure is another significant investment challenge jointly explored by stakeholders, utility companies, and car/charger manufacturers. Another primary concern is battery life management limiting the charging current intake by the EV battery.

Thermal Characterization Approach for In Situ Estimation of Thermophysical Properties of Magnetic Components of Electric Vehicle Fast Chargers

This article presents a cost-effective thermal characterization approach that relies on temperature measurements and numerical simulations to solve an inverse heat transfer (IHT) problem for the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> estimation of thermophysical properties of high-frequency magnetic components. This approach is applied to the magnetic components of a commercial electric vehicle dc fast charger, specifically, to an air-cooled inductor-transformer assembly. Numerical simulations solve a conjugate conduction–convection IHT problem based on surface temperature measurements collected during realistic operating conditions of the charger. These simulations enable rapid <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> estimation of the specific heat capacities, thermal conductivities, volumetric heat generation rates, and convective heat transfer coefficients of the cores and windings of these magnetic components. These estimated properties are then used as inputs in a direct heat transfer (DHT) simulation for the thermal analysis of these components under different cooling conditions, namely natural and forced convection. The thermal analysis of the inductor-transformer assembly shows that active air cooling with forced convection allows sustaining the measured charging power (28.8 kW) up to 6630 s when the surface temperatures of the cores reach the 100 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{\circ }$</tex-math></inline-formula> C threshold. This charging time is 61.7% longer than that allowed by the passive air cooling at the same charging power.

Effects of electric vehicle adoption for state-wide intercity trips on emission saving and energy consumption

Electric vehicles (EVs) mitigate fossil fuel dependency and reduce emissions; they are considered sustainable alternatives to conventional vehicles. To support EVs’ intercity trips, a recent study proposed a charging infrastructure planning framework implemented for the intercity network of Michigan, considering different projected EV market shares for 2030. This study aims to estimate emission savings, including CO2, HC, CO, and NOx, associated with the projected electrification rate and the proposed infrastructure for light-duty vehicles in the earlier study. To this end, a state-of-the-art emission estimation framework is proposed for state-wide intercity trips. The main contributions of the proposed framework include (1) Incorporating a micro emission estimation model (MOVES) for the simulated vehicle trajectories in a large-scaled network considering monthly travel demand, temperature variations, and heterogeneity of vehicles; (2) Contrasting the required investment in charging infrastructure to support EVs intercity trips with the associated emission savings. To this end, the proposed emission estimation framework is benchmarked against a traditional method based on vehicle miles traveled (VMT). Then, different scenarios of EV adoption are explored to assess potential emission savings. The results suggest that the annual CO2 savings (as the most critical emission) due to intercity travel electrification ranges from 0.34 to 1.45 million ton. The societal cost savings justify the investment in network electrification. Note that only 3.8%–8.8% of the EV energy demand must be satisfied by the DC fast charger network proposed by the charging infrastructure planning framework. This requires 22.45–51.60 BWh annual energy consumption for Michigan’s EV market share for 2030.

Energy and Demand Forecasting Based on Logistic Growth Method for Electric Vehicle Fast Charging Station Planning with PV Solar System

Electric vehicle (EV) charging may impose a substantial power demand on existing low voltage (LV) and medium voltage (MV) networks, which are usually not prepared for high power demands in short time intervals. The influx of E-mobility may require an increase in grid reinforcements, but these can be reduced and optimized by a combination of new technologies, tools, and strategies, such as the deployment of solar PV generation integrated with aggregated energy storage systems. One of the challenges in the implementation of charging infrastructures in public stations is coupling the projected sizes of energy demand and power requirements in each location for each charger. This paper describes a method to estimate projected values for energy consumption and power demand in EV fast charging stations (CS). The proposed ideas were applied in a concept facility located in Campinas, Brazil, in a structure equipped with two 50 kW DC Fast Chargers, local 12.5 kW/13.2 kWp PV generation (to reduce energy impacts to the grid), and a 100 kW/200 kWh storage system, using electrochemical batteries (to minimize peak power requirements).

Hybrid AC/DC-coupled charging station architecture with comprehensive hierarchical control for optimal economical operation and load variance minimization

This paper introduced a novel hybrid AC/DC-coupled charging station architecture and corresponding hierarchical control strategy. The core element of the architecture is an integrated interlinking converter (ILC) named the energy routing unit (ERU). The ERU features multiple conversion stages, dedicated plug-and-play interfaces, and varied operation functionalities. The dual inputs of utility sources enhance the reliability of the power supply. The contained scalable charging module facilitates the DC fast charging via DC grids directly, and the traditional AC slow charging is also accommodated in this architecture. Regarding the architecture, a comprehensive hierarchical control strategy containing the local-level short-timescale transient control and upper-level long-timescale optimal power scheduling is proposed. The multi-objective optimization concerning the optimal economical operation and minimum load variance is incorporated into the upper-level power flow control. The detailed simulation cases demonstrate that the stable operation of the proposed architecture could be realized, and the desirable economical operation and low peak-to-valley load variance are to be implemented simultaneously. The enabled vehicle-to-vehicle (V2V) power coordination achieves mutual power support between AC and DC subgrids and increases the local consumption of renewable energy sources effectively.

Design and analysis of an efficient photovoltaic energy-powered electric vehicle charging station using perturb and observe MPPT algorithm

According to the current directive, we must rely on green energy for sustainable mobility. One of the green transition’s goals is to use renewable energy to charge electric vehicles (EVs). Solar energy is a form of renewable energy sources, and it is classified as being clean, available, and renewable because it is based on sunshine. Nowadays, the world is turning to EVs which have lower running costs and cleaner environments. Lithium-ion batteries are commonly utilized to store energy in EVs. This article covers the design and analysis of a photovoltaic (PV) system to charge five models of EVs such as BMW i3 2019, Volkswagen e-Golf, Fiat 500e, Mercedes EQA 250, and Hyundai Kona Electric in a DC fast charging mode by using a buck converter to minimize the output voltage and without any addition of energy storage. By applying Perturb &amp;amp; Observe (P&amp;amp;O) Maximum Power Point Tracking (MPPT), the maximum power and efficiency from PVs are obtained. The charging time is calculated for each EV of the five models in the State of Charge (SOC) area at 20–80 percent. A MATLAB program is employed to simulate the EV models by calculating the efficiency of the MPPT controller, time of charging, and characteristic of voltage and current levels for each model of these EVs. All models are tested under the condition of irradiance level from 600 W/m2 to 1000 W/m2 and temperature between 20°C and 30°C. The results showed that the PV system is effective and economical as a stand-alone to charge EVs in a rapid charge mode.

Review of Solid-State Transformer Applications on Electric Vehicle DC Ultra-Fast Charging Station

The emergence of DC fast chargers for electric vehicle batteries (EVBs) has prompted the design of ad-hoc microgrids (MGs), in which the use of a solid-state transformer (SST) instead of a low-frequency service transformer can increase the efficiency and reduce the volume and weight of the MG electrical architecture. Mimicking a conventional gasoline station in terms of service duration and service simultaneity to several customers has led to the notion of ultra-fast chargers, in which the charging time is less than 10 min and the MG power is higher than 350 kW. This survey reviews the state-of-the-art of DC ultra-fast charging stations, SST transformers, and DC ultra-fast charging stations based on SST. Ultra-fast charging definition and its requirements are analyzed, and SST characteristics and applications together with the configuration of power electronic converters in SST-based ultra-fast charging stations are described. A new classification of topologies for DC SST-based ultra-fast charging stations is proposed considering input power, delta/wye connections, number of output ports, and power electronic converters. More than 250 published papers from the recent literature have been reviewed to identify the common understandings, practical implementation challenges, and research opportunities in the application of DC ultra-fast charging in EVs. In particular, the works published over the last three years about SST-based DC ultra-fast charging have been reviewed.

Integration of charging station to the smart grid power network by using robust immune feedback adaptive and Rao optimization approaches

AbstractThe adoption of electrical vehicles (EVs) is nowadays a center of attraction, which reduces the carbon footprint and adds to the economic growth of a country. However, providing a proper charging facility to the customers is still a challenging task. This paper presents the mix (AC‐DC) charging station (CS) integrated with the PV array and the smart distribution grid. The acceleration of the EV causes the power quality burden on the grid and this can be taken care of by using advanced adaptive controls. In this paper, the control strategy used for the CS is the immune feedback‐based adaptive (IFA) control technique. It reduces the ripples in the fundamental load current extraction under steady‐state and produces fast response under dynamic conditions and helps to synchronize CS with the grid. The multi‐functional capabilities of the CS are presented with different voltage levels DC fast off‐board chargers and AC onboard slow chargers. Moreover, the Rao optimization technique is utilized to select the gains for the cascaded proportional‐integral (PI) controllers which are used to regulate the DC bus voltage and battery charging/discharging currents. The optimized fitness values of integral time square error (ITSE) by using Rao1, Rao2, and Rao3 techniques are 297.341, 285.023, and 282.924 respectively. The simulated and test results depict the efficacy of the CS. Moreover, the mixed charging facilities with multi DC fast chargers avoid the rush and burden on the grid, which reduces the power outage across the load and rapidly rising energy cost.

Beyond Adoption: Examining Electric Vehicle Miles Traveled in Households with Zero-Emission Vehicles

The environmental benefits of zero-emission vehicles (ZEVs) are affected by both consumer adoption and usage patterns. While numerous studies examine consumers’ stated or revealed preferences for ZEV adoption, ZEV usage patterns have received less attention. Based on the 2019 California vehicle survey data, this paper analyzes the annual mileage of three ZEV types: battery electric vehicle (BEV), plug-in hybrid electric vehicle (PHEV), and fuel cell electric vehicle (FCEV). Results show that ZEVs are driven as much as or more than internal combustion engine vehicles (ICEVs). Furthermore, focusing on households with one ZEV and one or more ICEVs, factors that influence household electric vehicle miles traveled (eVMT) are explored using multiple linear regression models. Greater battery range, home charging capability (regardless of charger type), and provision of special electricity rates for home charging are found to be positively correlated with the eVMT of PHEV households. The eVMT of BEV households is positively associated with Level 2 home charging capability, solar panel installation, access to workplace DC fast charging, and access to public Level 2 and DC fast charging stations. The number of routinely-used public hydrogen refueling stations is associated with higher FCEV household eVMT. Lastly, when high-occupancy vehicle lane access is rated as extremely important in the ZEV purchase decision, greater eVMT is found for both BEV and FCEV households, but not for PHEV households. Results of this study inform policies to encourage eVMT over vehicle miles traveled by ICEV in a household, achieving greater environmental benefits from ZEVs.

Operational grid and environmental impacts for a V2G-enabled electric school bus fleet using DC fast chargers

As states replace diesel school buses with electric ones, utilities will want to control charging schedules to capture potential benefits on the grid and avoid all buses charging at the same time, adding a large electric load. Vehicle-to-grid (V2G) services can provide more grid stability and reduced carbon dioxide emissions than simple controlled charging systems, yet the grid impacts of V2G school buses have not been modeled using realistic school bus schedules. This paper develops a methodology for simulating the effect of managed charging of electric school buses on peak shaving in the state of North Carolina using V2G interactions and DC fast chargers to determine potential emissions reductions by minimizing peak load periods. The V2G-Sim model is used to manage fleet-wide charging, while minimizing peak generation of electricity on the grid and flattening the load curve under different battery capacities, charger power ratings, and fleet sizes. Historic annual peak hours are examined to determine the feasibility of reducing generation capacity, and the daily peak hours are examined to determine the potential peak shaving and subsequent avoided emissions. The results demonstrate that at full electric school bus replacement, 14,000 V2G buses can aggregate and shift 2.6 GWh in North Carolina, avoiding up to 1,130 t of carbon dioxide emissions per day, assuming decreased dependence on natural gas peaker plants. An additional 1,500 t of CO2 can be avoided by replacing diesel-powered buses compared to the 320,000 t total daily CO2 emissions from all activities in North Carolina. Additional emissions are avoided by the replacement of diesel buses with electric buses. The largest greenhouse gas emission benefit is the replacement of diesel with electric school buses, and the ability to shave peak loads is maximized on weekend days in the winter. The model can be used by researchers, the utility, and states as these entities evaluate the environmental and operational grid benefits of a V2G school bus program.

DC Fast Charging Optimization for Capacity Fade Minimization

DC fast charging is a critical step to support the recharging demands of electric vehicles and increase their penetration in the market. However, compared to normal Level 1 or 2 charging, DC fast charging imposes additional battery capacity fade which can result in premature aging of the battery, reducing its useful life. This paper proposes a computationally efficient, meta-heuristic approach to optimize the charging C-Rate profile while considering battery degradation associated with not only the charging but also the expected drive cycle following charging. The battery and its degradation are modeled with a semi-empirical, physics-based approach which yields a high accuracy and is computationally efficient. The meta-heuristic approach to optimize the charge profile is first validated for a simplified case with Dynamic Programming. To demonstrate the effectiveness of the approach in attenuating the battery aging, a benchmark case with 15 minutes of constant current charging of a Lithium Iron Phosphate battery is set. A nearly 1% capacity fade improvement is obtained for a single charge-discharge cycle after charging C-Rate optimization, which would generate significant benefit over the electric vehicle life.

Co-Simulation of Optimal EVSE and Techno-Economic System Design Models for Electrified Fleets

As the transition to electric mobility is expanding at a rapid pace, operationally feasible and economically viable charging infrastructure is needed to support electrified fleets. This paper presents a co-simulation of optimal electric vehicle supply equipment (EVSE) and techno-economic system design models to investigate the behaviors of various EVSE configurations from cost and technical aspects. While the system design optimization is performed for a grid-tied PV system, the optimal EVSE model considers all EVSE options that are currently installed at workplaces. To investigate the impact of the EV utilization rate, three fleet sizes are considered, which are generated based on real EV fleet data. Furthermore, the impact of electricity rates is also explored through an innovative business EV-specific (BEV) rate and a conventional time-of-use (ToU) tariff. It is shown that investing in grid-tied renewable energy technologies for workplace charging infrastructure supply can lower charging costs. Cost savings differ from EVSE types and fleet size under the BEV rate, while EVSEs display similar cost-saving behavior under the ToU tariff irrespective of fleet size. DC Fast Charging (DCFC) EVSE is found to be highly sensitive to fleet size as compared to AC EVSEs. Moreover, DCFCs make better use of the BEV rate, which makes their economics competitive as much as AC EVSEs. Finally, it is found that the fleet size and AC EVSE types have a minor effect on the use of renewable energy in contrast to the DCFC case.

An Overview on Medium Voltage Grid Integration of Ultra-Fast Charging Stations: Current Status and Future Trends

The emphasis on clean and green technologies to curtail greenhouse gas emissions due to fossil fuel-based economies has originated the shift towards electric mobility. As on-road electric vehicles (EVs) have shown exponential growth over the last decade, so have the charging demands. The provision of charging facilities from the low-voltage network will not only increase the distribution system's complexity and dynamics but will also challenge its operational capabilities, and large-scale upgrades will be required to meet the inevitably increasing charging demands. An ultra-fast (UF) charging infrastructure that replicates the gasoline refueling network is urgently needed to facilitate a seamless transition to EVs and ensure smooth operation. This paper presents a review of state-of-the-art DC fast chargers, the charging infrastructure's current status, motivation, and challenges for medium-voltage (MV) UF charging stations (UFCS). Furthermore, we consider the possible UFCS architectures and suitable power electronics topologies for UF charging applications. To address the peak formation issues in the daily load profile and high operational expenses of UFCSs, integration of renewable energy sources and energy storage systems due to their technological and economic benefits is being considered. The benefits of line frequency transformer (LFT) replacement with a solid-state transformer (SST),SST models, SST-based UF chargers, and MV SST-based UFCS architectures, as well as related MV active front-end and back-end power electronics topologies, are presented. Finally, the application of microgrids&#x0027; hierarchical control architecture is considered for chargers and system-level control and management of UFCSs.

A Comprehensive Review of Power Converter Topologies and Control Methods for Electric Vehicle Fast Charging Applications

Wide-scale adoption and projected growth of electric vehicles (EVs) necessitate research and development of power electronic converters to achieve high power, low-cost, and reliable charging solutions for the EV battery. This paper presents a comprehensive review of EV off-board chargers that consist of ac-dc and dc-dc power stages from the power network to the EV battery. Although EV chargers are categorized into two types, namely, on-board and off-board chargers, it is essential to utilize off-board chargers for dc fast and ultra-fast charging so that volume and weight of EV can be reduced significantly. Here, we discuss the state-of-the-art topologies and control methods of both ac-dc and dc-dc power stages for off-board chargers, focusing on technical details, ongoing progress, and challenges. In addition, most of the recent multiport EV chargers integrating PV, energy storage, EV, and grid are presented. Moreover, comparative analysis has been carried out for the topologies and the control schemes of ac-dc rectifiers, dc-dc converters, and multiport converters in terms of architecture, power and voltage levels, efficiency, bidirectionality, control variables, advantages, and disadvantages which can be used as a guideline for future research directions in EV charging solutions.

Design and application of smart-microgrid in industrial park

Due to the uncertain and randomness of both wind power photovoltaic output of power generation side and charging load of user side, a set of wind-solar-storage-charging multi-energy complementary smart microgrid system in the park is designed. Through AC-DC coupled, green energy, such as wind energy, distributed photovoltaic power and battery echelon utilization energy storage power, can be supplemented as factory power. While alleviating the power consumption pressure in the plant, it also realizes functions such as smoothing the fluctuation green energy power generation, and peak loading shifting. Vehicle DC super and fast charging are also integrated in this station. The system realizes real-time state monitoring of different energy sources, energy storage, power distribution, and loads, which can guarantee green, smooth, efficient and economic operation of the multi-energy complementary system in the plant.

Queuing to Charge an Ev vs Utilization of a Dc Fast Charger

Queuing to Charge an Ev vs Utilization of a Dc Fast Charger

Data mining of plug-in electric vehicles charging behavior using supply-side data

This paper aims to better understand the charging patterns of plug-in electric vehicles (PEVs) and identify factors that may significantly impact PEVs’ charging behavior. We collected 189,864 supply-side charging session data over 13 months from 821 charging stations in Illinois from ChargePoint. Through descriptive and regression analyses, we characterize the distributions of key charging behavior indicators, including charging location, dwell time, and battery start state of charge (SOC), and quantify the impacts of closely related factors on these charging behaviors. We find that: (1) PEVs are more likely to charge in the morning at multifamily commercial locations with a lower start SOC compared with single family residential locations; (2) Weekday and morning sessions are more likely to utilize workplace charging and have shorter dwell time compared with weekend and afternoon sessions; (3) Single family residential area and locations with Levels 1/2 chargers have a higher start SOC and longer dwell time compared with other locations and DC fast chargers (DCFCs). These findings provide policy insights to identify potential time and locations to incentivize PEVs for grid services, as well as identify critical location categories for further charging infrastructure investment to better reduce range anxiety and promote PEV adoption.

Python supervised co-simulation for a day-long harmonic evaluation of EV charging

To accurately simulate electric vehicle DC fast chargers' (DCFCs') harmonic emission, a small time step, i.e., typically smaller than 10 &#x03BC;s, is required owing to switching dynamics. However, in practice, harmonics should be continuously assessed with a long duration, e.g., a day. A trade-off between accuracy and time efficiency thus exists. To address this issue, a multi-time scale modeling framework of fast-charging stations (FCSs) is proposed. In the presented framework, the DCFCs' input impedance and harmonic current emission in the ideal grid condition, that is, zero grid impedance and no background harmonic voltage, are obtained based on a converter switching model with a small timescale simulation. Since a DCFC's input impedance and harmonic current source are functions of the DCFC's load, the input impedance and harmonic emission at different loads are obtained. Thereafter, they are used in the fast-charging charging station modeling, where the DCFCs are simplified as Norton equivalent circuits. In the station level simulation, a large time step, i.e., one minute, is used because the DCFCs' operating power can be assumed as a constant over a minute. With this co-simulation, the FCSs' long-term power quality performance can be assessed time-efficiently, without losing much accuracy.

Control of Low-Frequency Oscillation on Electrical Power System Under Large EV-Charging Station Installation Using PSO Technique for Turning PSS Parameters

This paper presents a low-frequency oscillation compensation in an electrical power system connecting large-scale electric vehicle loads (EVs). The Particle Swarm Optimization (PSO) method has been adapted to adjust the control parameters of the generator under Power System Stabilizer (PSS) parameters. The EVs charging stations have been directly installed to the power grid for the battery charging process of the EVs according to the increasing number of EVs. The DC fast charging of the large scale EVs has been significantly affected by the low-frequency oscillation of the grids that have been considered in terms of power system stability margin. This paper has aimed to solve the methodology for turning the PSS parameters by adapting the PSO via MATLAB® and DIgSILENT®. The PSS could control the low-frequency oscillation in the proposed power grids. The simulation system has selected the 6-bus testing system, which has increased the EVs loads by 50, 100, 150, 200, and 300 percentages at bus No. B3. The simulation results have indicated that the rotor low-frequency oscillation could control instability region. Therefore, the proposed PSS controller turning could handle the power system swing and adjust the power system stability. In this condition, the proposed PSO method should have been explicitly used for low-frequency swing control of the generator's rotor into a balanced state under the large-scale EVs penetration level.

Characterization of Large Format Pouch Cells by Electrochemical Impedance Spectroscopy for Automotive Applications

The influence of operating conditions such as temperature and state of charge on the performance of a high-power commercial lithium-ion pouch cell is explored using electrochemical impedance spectroscopy. State-of-charge and temperature ranges were selected based on relevance to automotive applications, such as DC Fast Charging, cold start, and high rate discharge events. Typical vehicle operation varies on the order of a few seconds and is therefore comparable with impedance values at frequencies higher than 0.1 Hz. Therefore, vehicle designers can utilize EIS as a tool to probe available power under standard operating conditions, as well as low temperatures and SOC in the vehicle at the battery cell level, offering the ability to decrease the amount of battery pack or vehicle level testing.Here, the full cell impedance is used to calculate electrochemical modeling parameters. Simulations using the parameters obtained from EIS are then compared to pulse tests and drive profiles for a large format pouch cell. Trends in the diffusion coefficients, reaction kinetics, and electrode conductivity as a function of state-of-charge and temperature will be discussed.