High-power Charging Research Articles

High-power chargers for electric vehicles: are they safe for patients with pacemakers and defibrillators?

Battery electric vehicle (BEV) sales and use are rapidly expanding. Battery electric vehicles, along with their charging stations, are a potential source of electromagnetic interference (EMI) for patients with cardiac implantable electronic devices (CIEDs). The new 'high-power' charging stations have the potential to create strong electromagnetic fields and induce EMI in CIEDs, and their safety has not been evaluated. A total of 130 CIED patients performed 561 charges of four BEVs and a test vehicle (350 kW charge capacity) using high-power charging stations under continuous 6-lead electrocardiogram monitoring. The charging cable was placed directly over the CIED, and devices were programmed to maximize the chance of EMI detection. Cardiac implantable electronic devices were re-interrogated after patients charged all BEVs and the test vehicle for evidence of EMI. There were no incidences of EMI, specifically no over-sensing, pacing inhibition, inappropriate tachycardia detection, mode switching, or spontaneous reprogramming. The risk of EMI on a patient-based analysis is 0/130 [95% confidence interval (CI) 0%-2%], and the risk of EMI on a charge-based analysis is 0/561 (95% CI 0%-0.6%). The effective magnetic field along the charging cable was 38.65 µT and at the charging station was 77.9 µT. The use of electric cars with high-power chargers by patients with cardiac devices appears to be safe with no evidence of clinically relevant EMI. Reasonable caution, by minimizing the time spent in close proximity with the charging cables, is still advised as the occurrence of very rare events cannot be excluded from our results.

Impact of Event-Based EV Charging Power Profile on Design and Control of Multi-Source DCFC Stations

<div class="section abstract"><div class="htmlview paragraph">The availability of DC Fast Charging Stations (DCFCs) is considered a fundamental step for the widespread adoption of electric vehicles (EVs). To mitigate the impact of high-power charging events on the grid, DCFCs are often equipped with stationary energy storage and renewable energy resources. In literature, many methods have been proposed to design, control, and optimize the performance of multi-sources DCFCs. Many of the research contributions use the averaged EV charging power consumption as input, not the real-time event-based power request. This paper aims at comparing the effects of average-based and event-based EV charging power profile<b>s</b> on the design and control of multi-sources DCFCs. An algorithm that generates event-based EV charging power profiles has been developed based on the data from the California Energy Commission (CEC) report and NREL's EVI-Pro I tool. Multiple scenarios can be generated based on different weekday and weekend energy consumptions, EV penetrations, and the number or power level of chargers. The case scenario in this paper considers a 150kW charging station with second life energy storage and photovoltaic (PV) plant with a low power grid connection (<50kW). The utilization of local distributed energy resources is fundamental for enabling EV charging power delivery. Event-based and average-based EV charging power profiles, having the same energy requirements, are used to assess the impact on the design and control of the stations.</div></div>

Power unit architecture in a high-power charging system for EVs

The paper proposes a methodology to define the architecture of the power unit of a UFC (Ultra Fast Charging) station for electric vehicles (EVs), capable of reaching a power of 350 kW. The main goal is to improve the efficiency of the system defining the best configuration by a MATLAB software (BEA – Best Efficiency Architecture) developed by the authors. The software allows defining the best architecture taking into account efficiency-power curves of all AC/DC and DC/DC power modules currently available on the market, thus increasing energy savings.Architectures based on different connection of AC/DC and DC/DC converters using DC bus have been taken considered. The best configuration found has been simulated using Simulink software, performing time-domain electrical simulations in order to verify and validate the architecture chosen.

Smart High Power Charging Networks and Optimal Control Mechanism for Electric Ships

On commercial ports, during loading/unloading on cruise, carrier, container, or tanker, its diesel engine creates pollution. Therefore, in ports, shore-to-ship power (Cold Ironing) supply is an alternative way to overcome the pollution issue at shipyards. However, different ships of different countries and different companies require different types of power with different electrical connections, such as ac power with 50 Hz and 3-phase 3-wire connection, ac power with 60 Hz and 3-phase 4-wire connection, ac power with 50 Hz and 1-phase 2-wire connection, dc power, etc. The ship's power requirements are always in the megawatt range and its required potentials are in the kilovolt range. Therefore, in this article, a smart high power charging network and its control mechanism are developed for cold ironing on the ports, which is capable of serving almost all types of power with different types of power supply network. This developed supply system is capable of providing ac power, dc power, 50 Hz frequency, 60 Hz frequency, single phase, three phases, 3 wire, 4 wire, and 5 wire networks, different ac, dc voltages, etc. The capability of the developed smart power network is validated for different types of ships and vessels, on the simulation platform as well as through experimentation on real-time hardware-in-the-loop. The test results on both the platforms satisfactorily demonstrate the proposed power network and control scheme.

Energy Efficiency Optimization of Collaborative Power Supply System with Supercapacitor Storages

To solve the challenge of low efficiency and high operation cost caused by intermittent high-power charging in an energy storage tram, this work presents a collaborative power supply system with supercapacitor energy storage. The scheme can reduce the peak power of the transformer, therefore reducing the grid-side capacity and improving the efficiency. However, there is a lack of quantitative analysis on the performance improvement of the solution. The energy efficiency models of critical components are proposed to evaluate the efficiency of the system, and energy efficiency optimization is conducted. Taking an operational tram line as an example, the improved charging efficiency and reduced operating costs are derived. Further, the ground energy storage capacity is designed and implemented. The measured data demonstrates that the energy efficiency of the optimized charging system is improved, which proves its effectiveness and practicability.

Analytical model for LLC resonant converters in operation below resonance

Electric cars are a great opportunity for reducing greenhouse gas emissions caused by transportation. High-power chargers are required to charge electric vehicles in a reasonable amount of time and considerably increase the driving range. As these high-power chargers currently need to be isolated with respect to the grid, the LLC converter topology emerged as a very good solution for implementing the required isolated DC/DC converter stage. The analysis and optimal design of this resonant converter stage are a challenging task, as some models are oversimplified, resulting in major errors and a high amount of processing time. This paper presents a novel analytical model for the LLC converter operating below resonance, which allows accurate modeling of the converter with minimal effort. In most cases, no iterations are required, and a comparison to numerical results taken from time domain simulations shows that the relative deviation of the proposed model stays far below 1% for a wide range of operating conditions.

Overview of Integration of Power Electronic Topologies and Advanced Control Techniques of Ultra-Fast EV Charging Stations in Standalone Microgrids

For longer journeys, when drivers of electric vehicles need a charge on the road, the best solution is off-board ultra-fast chargers, which offer a short charging time for electric vehicle batteries. Consequently, the ultra-fast charging of batteries is a major issue in electric mobility development globally. Current research in the area of power electronics for electric vehicle charging applications is focused on new high-power chargers. These chargers will significantly increase the charging power of electric vehicles, which will reduce the charging time. Furthermore, electric vehicles can be deployed to achieve improved efficiency and high-quality power if vehicle to microgrid (V2µG) is applied. In this paper, standards for ultra-fast charging stations and types of fast charging methods are reviewed. Various power electronic topologies, the modular design approach used in ultra-fast charging, and integration of the latter into standalone microgrids are also discussed in this paper. Finally, advanced control techniques for ultra-fast chargers are addressed.

High-power electric vehicle charging: Low-carbon grid integration pathways with stationary lithium-ion battery systems and renewable generation

The energy transition in the mobility sector is well underway. The electrification of road transport is resulting in a shift of the energy demand from the oil and gas sector to the electricity grid. Increasingly aggressive targets for low charging times for Electric Vehicles (EVs) are slated to raise the demand for High-Power Charging (HPC). This is likely to lead to bottlenecks and overloading in vulnerable sections of the electricity grid. Battery Assistance (BA) is a promising grid integration measure for High-Power Charging (HPC) to mitigate these problems. As decarbonization is the primary objective of the energy transition, the determination and comparison of the Global Warming Potential (GWP) footprints for HPC stations with BA is crucial. A comprehensive mathematical framework for the modelling and quantification of GWP footprints for HPC has been developed. The Levelized Emissions of Energy Supply (LEES) methodology has been extended and generalized to handle energy from the grid. A new state variable for the Battery Energy Storage System (BESS) — the State of Carbon Intensity (SOCI) has been introduced to calculate the operation phase GWP footprint of the BESS. The energy consumption GWP footprint for the load is also described by a new quantity — the Load Energy Consumption (LEC) emissions. The effect of incorporation of local Photovoltaic Solar (PV) generation in the energy flows is also investigated. An optimized Energy Management System (EMS) strategy with rolling horizon optimization to minimize emissions has been implemented to regulate energy flows in scenarios with BA and local PV generation. The Levelized Emissions of Energy Supply (LEES) values are obtained for all simulated scenarios and compared against a baseline rule-based EMS strategy. In combination with on-site PV generation, BA could achieve a reduction of 24% in the LEES vis-á-vis the baseline strategy. For reference, two scenarios with Grid Reinforcement (GR) for the grid section with and without local PV generation have also been simulated. With Grid Reinforcement (GR), a reduction of over 2% can be achieved with respect to the baseline EMS strategy for BA. Grid Reinforcement (GR) in conjunction with local PV generation can bring about a further reduction of about 6% with respect to the baseline EMS strategy for BA.

Substantial Na-Ion Storage at High Current Rates: Redox-Pseudocapacitance through Sodium Oxide Formation.

Batteries and supercapacitors, both governed by electrochemical processes, operate by different electrochemical mechanisms which determine their characteristic energy and power densities. Battery materials store large amounts of energy by ion intercalation. Electrical double-layer capacitors store charge through surface-controlled ion adsorption which leads to high power and rapid charging, but much smaller amounts of energy stored. Pseudocapacitive materials offer the promise to combine these properties by storing charge through surface-controlled, battery-like redox reactions but at high rates approaching those of electrochemical double-layer capacitors. This work compares the pseudo-capacitive charge storage characteristics of self-organized titanium dioxide (TiO2-x) nanotubes (NTs) to flat TiO2-x surface films to further elucidate the proposed charge storage mechanism within the formed surface films. By comparing TiO2-x NTs to flat TiO2-x surface films, having distinctively different oxide mass and surface area ratios, it is shown that NaO2 and Na2O2 formation, which constitutes the active surface film material, is governed by the metal oxide bulk. Our results corroborate that oxygen diffusion from the lattice oxide is key to NaO2 and Na2O2 formation.

Enabling Safety-Enhanced fast charging of electric vehicles via soft actor Critic-Lagrange DRL algorithm in a Cyber-Physical system

Fast charging of lithium-ion battery (LIB) is critical for the further popularity of electric vehicles. However, the partial pursuit of high-power charging can violate the physical limits of LIB, and further cause unexpected side effects or even catastrophic safety issues. Motivated by this, this paper proposes a multi-state-constrained fast charging strategy for LIB, enabled by a novel deep reinforcement learning (DRL) technique. In particular, the SAC-Lagrange DRL is developed, for the first time, to train the fast-charging strategy assisted by an electro-thermal model for unmeasurable state perceiving. The proposed strategy is further performed within a cyber-physical system-based management framework, where the complicated training is carried out in the cloud, while the trained low-complexity policy is executed in the onboard controller to mitigate the risk of high computing burden. Hardware-in-Loop tests and practical charging experiments are carried out for validation. Results reveal that the proposed strategy can boost the charging speed remarkably while smartly avoid violating the electrical and thermal safety limits of LIB. Compared with the advanced DDPG-based and SAC-based strategies, the proposed one has improved the optimality and stability, and thus enjoys more guaranteed convenience and versatility in practical charging applications.

External Liquid Cooling Method for Lithium-Ion Battery Modules Under Ultra-Fast Charging

Electric vehicles (EVs) are booming all over the world for a low carbon emission and greener environment. The fast charging is an urgent demand for consumers. However, the dramatic temperature rising during high-power charging has a high risk of trigging thermal runaway and other safety issues. This article proposes an external liquid cooling method for lithium-ion battery module with cooling plates and circulating cool equipment. A comprehensive experiment study is carried out on a battery module with up to 4C fast charging, the results show that the three-side cooling plates layout with low coolant temperature provides better temperature control effect, while the coolant velocity and type have very weak impact. Then the simulation model with high precision is built for ultra-fast charging, and a safe charging range under 5C charging is proposed. The safe charging range under 5C can be increased by 50.1%. The environment close to the room temperature demonstrates the best effects of external cooling. For actual applications in the EVs, the circulating cooling equipment outside EVs can be integrated with high-power charging infrastructure and provide a 117 km improvement in mileage under 5C safe charging which indicates a tremendous application prospect.

Ultrahigh‐Output Triboelectric and Electromagnetic Hybrid Generator for Self‐Powered Smart Electronics and Biomedical Applications

AbstractBiomechanical energy harvesting shows great potential in the fields of smart electronics and biomedical Internet of Things. However, it is a significant challenge to develop a biomechanically driven energy harvester with high output power and fast charging as a sustainable power source for extended practical applications. Herein, an ultrahigh‐output triboelectric and electromagnetic hybrid generator (UHO‐TEHG) is developed to efficiently harvest biomechanical energy and provide self‐powered systems for numerous applications. The Halbach magnet array is used to concentrate additional magnetic flux in the coil and significantly enhance electromagnetic performance, while the novel poly(ethylene oxide) nanofibers enhance the triboelectric performance. Through the implementation of a mechanical spring‐mass model, and rational integration of electromagnetic and triboelectric generators, the UHO‐TEHG can provide an excellent output power of 1.02 W. Compared with existing mechanical energy harvesting devices, the fabricated device exhibits a much faster battery charging performance. Experimental results reveal remarkable performance related to biomechanical energy harvesting during walking, running, hiking, mountaineering, and self‐powered wireless human motion sensor. Real‐time charging of smartphones, smartwatches, Buds Live, and iTag via customized power management circuits is demonstrated. In addition, the fabricated UHO‐TEHG demonstrates the capability to power healthcare monitoring systems using a laser‐induced hierarchical carbon nanofiber‐based e‐tattoo sensor.

Charging Infrastructure and Schedule Planning for a Public Transit Network with a Mixed Fleet of Electric and Diesel Buses

Promoting battery electric buses (BEBs) can reduce fuel consumption and air pollution from the transit system. A complete transition from the current diesel fleet to BEBs is costly and time-consuming. Thus, the intermediate solution is a combination of diesel, hybrid, and BEBs. Therefore, a planning framework is required that simultaneously tackles three contiguous aspects of transit electrification and their interconnections, namely charging infrastructure, fleet configuration, and scheduling. Accordingly, this study considers a mixed fleet of diesel and BEBs. It aims to concurrently find (i) the optimal location and capacity of charging infrastructure, considering micro-grid specifications, the impact of distributed energy resources, and time-of-use electricity rates and (ii) optimum operation and refueling strategies. Another objective of this study is to capture the impacts of adverse weather conditions on transit electrification. A mixed-integer problem is proposed and solved using a metaheuristic algorithm based on simulated annealing to minimize system costs, including infrastructure, fleet, and operation costs. A subnetwork of transit in Worcester, Massachusetts, is selected as a case study, including three routes, five candidate charging locations, and three bus types. Findings suggest that BEBs can operate and serve the passenger demand with sufficient charging infrastructure. Sensitivity analyses show that even though high-power chargers are more expensive per piece, they reduce the overall cost as fewer chargers are required. The cost rises for chargers with power of 350 kW or more. It is worth noting that the benefits of BEBs are more significant in smaller buses and are heavily affected by adverse weather conditions.

Predictive Current Control of Six-Phase IM-Based Nonisolated Integrated On-Board Battery Charger Under Different Winding Configurations

Integrated on-board battery charging (IOBC) constitutes one of the future trends and the potential state-of-the-art technologies proposed for high-power chargers of electric vehicles. Model predictive control has recently been favored in different applications due to its simplicity in defining new control objectives and the straightforward handling of nonlinear constraints. In this article, the predictive current control (PCC) is applied to a six-phase induction-machine-based IOBC with three different winding configurations. From the grid perspective, this article introduces the required winding connections that maximize the charging grid current. Under PCC, different stator phases are controlled to draw balanced three-phase grid currents through controlling the machine nontorque-producing <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>xy</i></b> current components while ensuring zero average/ripple torque production. This article also discusses the effect of winding configuration on the mapping of the 64 available voltage vectors to the <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>αβ</i></b> , <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <i>xy</i></b> , and <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0⁺ 0⁻</b> subspaces. The optimal subset voltage vectors of each configuration that achieve the highest possible dc-link utilization, zero torque production, minimum total harmonic distortion (THD), and unity power factor are then introduced. The feasibility to employ the concept of virtual voltage vectors to improve the current quality is also investigated. The three six-phase configurations are obtained from an externally reconfigured 1 kW 12-phase induction motor, which has been used to experimentally validate the theoretical findings.

Public fast charging infrastructure for battery electric trucks—a model-based network for Germany

Abstract Globally, road freight accounts for 40% of the CO2 emissions in the transport sector, mainly from heavy-duty vehicles (HDVs). All the major truck markets have introduced fuel efficiency regulations for HDV, and the more ambitious regulations require the introduction of zero-emission HDV, for which battery electric trucks (BEVs) are a promising candidate. However, frequent long-distance trips require a dense public high-power charging network if BEV are to meet today's operating schedules in logistics. Here, we develop a model for public BEV high-power fast-charging that uses widely available traffic count data as input and combines this with on-site queueing models. We apply the model to Germany and obtain a fast-charging network where average waiting times do not exceed 5 min. For 15% BEV in the truck stock and 50% public charging, the model shows 267 charging locations, each with 2–8 charging points per location, for a dense network with 50 km distance between charging locations. We calculated 142 charging locations with 2–13 charging points for a wider network with 100 km distance between locations. Our results help to design future charging infrastructure for electric road freight transport.

A False Data Injection Attack Detection Method for Cooperative Charging Systems

Supercapacitors have been widely used in public transportation for the advantages of high power density and extremely long lifetime. Owing to the high-power charging requirements of supercapacitors, the multicharger cooperative charging method has been applied to suppress the current imbalance among chargers. However, the cooperative charging system is vulnerable to cyber attacks with false data injections, which degrades the reliability of the charging system. To address this challenge, in this article, a detection method for a false data injection attack (FDIA) is proposed for the cooperative charging system. First, we introduce the cooperative charging system and analyze the possible cyber attacks. Then, an FDIA detection method is proposed based on a Kalman filter and the time&#x2013;frequency features of chargers&#x2019; currents. A three-charger laboratory platform is built to verify the effectiveness of the proposed method. Extensive experimental results show that the proposed method can detect the FDIA effectively when compared with the existing methods.

On the integration of battery electric buses into urban bus networks

Cities all around the world struggle with urban air quality due to transportation related emissions. In public transport networks, replacing internal combustion engine buses by electric buses provides an opportunity to improve air quality. Hence, many bus network operators currently ask for an optimal transformation plan to integrate battery electric buses into their fleet. Ideally, this plan also considers the installation of necessary charging infrastructure to ensure a fleet’s operational feasibility. Against this background, we introduce an integrated modeling approach to determine a cost-optimal, long-term, multi-period transformation plan for integrating battery electric buses into urban bus networks. Our model connects central strategic and operational decisions. We minimize total cost of ownership and analyze potential reductions of nitrogen oxide emissions. Our results base on a case study of a real-world bus network and show that a comprehensive integration of battery electric buses is feasible and economically beneficial. By analyzing the impact of battery capacities and charging power on the optimal fleet transformation, we show that medium-power charging facilities combined with medium-capacity batteries are superior to networks with low-power or high-power charging facilities.

Planning of High-Power Charging Stations for Electric Vehicles: A Review

Electrification of mobility is paving the way in decreasing emissions from the transport sector; nevertheless, to achieve a more sustainable and inclusive transport system, effective and long-term planning of electric vehicles charging infrastructure will be crucial. Developing an infrastructure that supports the substitution of the internal combustion engine and societal needs is no easy feat; different modes of transport and networks require specific analyses to match the requirements of the users and the capabilities of the power grid. In order to outline best practices and guidelines for a cost-effective and holistic charging infrastructure planning process, the authors have evaluated all the aspects and factors along the charging infrastructure planning cycle, analysing different methodological approaches from scientific literature over the last few years. The review starts with target identification (including transport networks, modes of transport, charging technologies implemented, and candidate sites), second, the data acquisition process (detailing data types sources and data processing), and finally, modelling, allocation, and sizing methodologies. The investigation results in a decision support tool to plan high-power charging infrastructure for electric vehicles, taking into account the interests of all the stakeholders involved in the infrastructure investment and the mobility value chain (distributed system operators, final users, and service providers).

A Review on Charging Infrastructure for Electric Transit Buses

The Electric transit buses (ETBs) are the main source for public transit to get the cleaner environment. The ETBs have gained popularity around the globe since the last decade. The ETBs are 14 % of the total transit buses around the world.&nbsp; The ETBs are heavy EVs and need more power to charge the high capacity batteries. The batteries used in these buses have the energy capacities between 80 kWh to 550 kWh. Such high capacity batteries take more to get charged. In order to increase the adoption of ETBs, a suitable number of high power dc charging infrastructures need to be installed in various main cities of the nations. The ETBs can operate with battery alone or fuel cell or combination of these two. Such ETBs are named as battery electric transit bus (BETB), fuel cell electric transit bus (FCETB) and hybrid electric transit bus (HETBs). As of 2020, out of total ETBs around the globe, 70 % are HETBs, 20 % are FCETBs and 10 % are BETBs. In this paper, the key parameters and comparison among these three batteries are shown. The major EV market holders are China, US, Europe and japan. The charging protocol used in the US and Europe is combined charging system. The charger capacity has reached up to 500 kW as of 2020. With such high power chargers it takes only less than half an hour to charge the high power batteries.

Model Predictive Control for Multi-Port Modular Multilevel Converters in Electric Vehicles Enabling HESDs

In this paper, the authors propose a model predictive control (MPC) algorithm for multi-port modular multilevel converters (MP-MMCs). MP-MMCs are used to enable the use of hybrid energy storage devices (HESDs) in a scalable energy management system (EMS) for electric vehicle (EV) applications. HESDs refer to the use of multiple types of energy storage cells in an EV drivetrain system. In this paper, battery cells are sized for the EV energy density, while ultra-capacitor cells are used for high acceleration periods. This system reduces the EV drivetrain's weight and size due to eliminating high-power inverters and their filtering components. Using MPC, this system can achieve the following control objectives: 1) extend the battery cells lifetime and driving range by shielding them from high power pulses, 2) balance the state of charge levels of every storage cell, 3) increase the system efficiency through optimizing the supplied motor voltage and reducing the switching losses. Moreover, the proposed solution provides means for onboard high-power charging of EV storage cells. Finally, validation results are provided in the paper using a developed hardware prototype, co-simulations, and hardware in the loop system to verify the system's effectiveness.