Electric Vehicle Mode Research Articles

Inductively Coupled WPT Circuit Design for Power Battery Charging in New Energy Vehicles

With the development needs of the new era, electric vehicles have become the preferred means of transportation with their environmentally friendly superiority and are moving towards an intelligent, wireless and grid-based future. However, the wired charging mode of electric vehicles does not meet this requirement and has many drawbacks, such as poor port adaptability, long charging time, and large land and labor costs. The wireless charging mode is naturally free of these problems and has been put into use in micro fields such as cell phone charging and watch charging. How to realize the utilization of wireless power transmission in the field of electric vehicles as soon as possible to realize charging while walking. In this paper, I will illustrate the advantages of Inductively Magnetically Coupled - Wireless Power Transmission (MCR - WPT), construct an optimized MCR - WPT circuit model to realize the wireless charging of battery, and give parameters such as energy utilization through Simulink simulation for theoretical justification. The results show that the MCR - WPT circuit can better realize the wireless charging of batteries with high safety and stability, and the MCR - WPT technology can play its advantages in the future large-scale wireless charging applications.

Current management for charging stations with power coupling items and three charging modes of electric vehicles under DoS attacks

Although the electric vehicle supplied through distributed generators (DGs) as one of the most important methods to reduce carbon emissions has become a research hotspot, the current management for charging stations with power coupling items and three charging modes of electric vehicles under denial of service (DoS) attacks, is rarely studied. Based on this, this paper proposes a new fully distributed consensus fuzzy control to achieve accurate current sharing for charging stations with power coupling items and three charging modes of electric vehicles under DoS attacks. Firstly, the system regarding charging stations with power coupling items and three charging modes is modeled which lays the foundation for the next design. Next, DoS attacks as the common network attacks are taken into consideration and modeled. Meanwhile, in order to reduce the communication burden, the fuzzy logic controller (FLC) is designed in this paper. Then the fully distributed consensus fuzzy control considered DoS attacks is proposed to achieve the current sharing control accurately for charging stations with power items and three charging modes under DoS attacks. Moreover, the system under the distributed consensus fuzzy control strategy is discussed in different situations. Finally, simulation comparisons and experiment results are carried out to verify the performance of the proposed control strategy.

Simulation of the Performance of Li-Ion Batteries in DC/AC Operating Mode for Electric Vehicles

This work simulates the performance of lithium batteries for electric vehicles under different charge and discharge rates. The simulation is based on similarity factors for power, voltage, and current, reproducing the current operation conditions of an electric vehicle at the model scale. Most current driving modes are analyzed corresponding to discharge rates from 0.1C to 0.37C. The simulation also applies to determining the charging time using charge power in current conditions, from 6.1 kW to 18.3 kW (0.1C to 0.3C). Driving conditions derive from equations for vehicle motion, including all forces. Tests have been run under two configurations, continuous and alternate current circuits, to reproduce the two types of engines used by electric vehicles. The simulation shows good agreement in charge and discharge processes, with an average deviation of 3% related to current operating conditions and 1.6% between them, proving the validity of the simulation process.

Intelligent Type-2 Fuzzy Logic Controller for Hybrid Microgrid Energy Management with Different Modes of EVs Integration

The rapid integration of renewable energy sources (RES) and the electrification of transportation have significantly transformed modern energy infrastructures, emphasizing the need for efficient and flexible energy management systems. This study presents an intelligent, variable-fed, Type-2 Fuzzy Logic Controller (IT2FLC) designed for optimal management of Hybrid Microgrid (HMG) energy systems, specifically considering different modes of Electric Vehicles (EVs) integration. The necessity of this study arises from the challenges posed by fluctuating renewable energy outputs and the uncoordinated charging practices of EVs, which can lead to grid instability and increased operational costs. The proposed IT2FLC is based on comprehensive mathematical modeling that captures complex interactions among HMG components, including Doubly Fed Induction Generator (DFIG) units, photovoltaic (PV) systems, utility AC power, and EV batteries. Utilizing a yearly dataset for simulation, this work examines the HMG’s flexibility and adaptability under dynamic conditions managed by the proposed intelligent controller. A Simulink-based model is built for this study to replicate the dynamical operation of the HMG and test the precise and real-time decision-making capability of the proposed IT2FLC. The results demonstrate the IT2FLC’s superior performance, achieving a substantial cost avoidance of nearly $3,750,000 and efficient energy balance, affirming its potential to sustain optimal energy utilization under stochastic conditions. Additionally, the results attest that the proposed IT2FLC significantly enhances the resilience and economic feasibility of hybrid microgrids, achieving a balanced energy exchange with the utility grid and efficient utilization of EV batteries, proving to be a superior solution for optimal operation of hybrid grids.

Low-Carbon Economy Optimization of Integrated Energy System Considering Electric Vehicles Charging Mode and Multi-Energy Coupling

To realize the multi-energy coupling integrated energy system to meet the multi-class load demand and achieve the goal of low-carbon economic operation, a bi-level optimal configuration method for low-carbon economic operation of multi-energy coupling integrated energy system under different charging modes of electric vehicles is proposed. Firstly, an integrated energy system including cooling-heating-power-gas coupling is established. Then, within the level of intraday scheduling, factors such as ladder carbon trading mechanisms and different charging modes of electric vehicles are considered to achieve the lowest daily scheduling cost. In the configuration planning level, based on the daily operation cost, the equipment capacity is configured with the lowest equipment investment and annual operation costs. The bi-level model is solved by CPLEX solver and the optimal configuration scheme and scheduling results are obtained by mutual iteration. Finally, the impact of different charging methods of electric vehicles on the system economy and low-carbon performance is demonstrated through simulation examples. The results show that the charging method of electric vehicles and the carbon trading mechanism in this paper can significantly reduce carbon emissions and improve the system's operating cost. The proposed configuration approach can well achieve low-carbon economic operation of the multi-energy coupling integrated energy system.

Simulation analysis of energy metering error of non-vehicle charger

This paper studies three methods of DC energy measurement for non-vehicle chargers, namely, the average value method, effective value method, and time domain integration method, introduces the definition of ripple, and analyzes the characteristics of constant voltage, constant current charging mode and pulse charging mode of electric vehicles, providing an algorithm basis for the establishment of DC energy metering error model and simulation analysis. This paper studies high-power DC energy measurement algorithms with ripple parameters, analyzes the error characteristics of various algorithms, summarizes the relevant laws, and provides a theoretical basis for the design of a high-precision DC metering module under the influence of ripple.

Inventory management of battery swapping and charging stations considering uncertainty

The battery swapping mode of electric vehicles (EVs) is expected to play an essential role in transportation and power systems. Plenty of batteries are managed by the battery swapping and charging stations (BSCSs) as the core assets. Proper inventory scale and charging/discharging control of batteries are essential to the planning and operation of BSCSs. This paper addresses two critical aspects of BSCS batteries: the optimal amount of inventory batteries and the tradeoff between the initial number of depleted and fully-charged batteries at the beginning of each scheduling horizon. Aiming at these, the time coupling between initial inventory, charging/discharging strategy, and swapping time sequence is analyzed. Afterward, it establishes the initial inventory based charging/discharging (IIC) model. The uncertain swapping demand is fully considered by utilizing a data-driven distributionally robust optimization (DRO) approach with an improved K-means clustering algorithm. A duality-free column-and-constraint generation (C&CG) algorithm solves the problem iteratively. The simulation results demonstrate the validity of the IIC model and show that the obtained optimization results achieve the balance of economy and robustness. Moreover, the impact of battery technology development on inventory batteries is analyzed, and suggestions are given.

Impact of Electrification in the Road Transport Sector on the Level of Electricity Consumption and Daily Load Curve in the UES of Russia

The article assesses the impact of potential motor transport sector electrification on the value of the aggregate demand for electricity and capacity in the UES of Russia. Despite official documents suppose quite modest quantitative targets for the electric transport until 2030, in the longer term, a large-scale replacement of oil fuel with electricity will have a significant effect on reducing greenhouse gas emissions, but will also require a more intensive development of generating and network capacities in the electric power industry. The scenaric forecast for the development of electric transport is made with the allocation of three segments - cars, trucks and buses, which allows taking into account the characteristics of electricity consumption characteristic of each of them. Another important result is an assessment of the possible extent of the influence of electric transport on the configuration of a typical daily load curve. The paper considers various modes of using infrastructure for electric transport charging, which result in different daily load curves. It is shown that, depending on the scales of electric transport development, their annual electricity consumption in the country will lay in the diapason from 168 to 460 TWh. At the same time, depending on the charging mode of electric vehicles, the additional power demand will vary from 26 to 74 million kW, and the amplitude of fluctuations in the hourly loads of electric vehicles will vary from two to four times.

MAIN ASPECTS OF IMPLEMENTATION OF CHARGING STATIONS FOR ELECTRIC TRANSPORTS IN LOGISTICS

The paper analyzes and compares charging stations for small electric vehicles, including fast and slow boats, electric cars and their components. The analysis of charging modes of electric vehicles showed that four internationally standardized modes are used, three of which use alternating current with single-phase and three-phase switching and only one – direct current. When charging on direct current, the fastest charging is provided. There are three main options for connecting the electric vehicles to the charging station: by means of a special power cable; by means of a pantograph from bottom to top and from top to bottom; wirelesses connection. There are four standardized cases of connecting charging stations to electric vehicles. Three cases of cable connection can be used on alternating current, only the third case – on direct current, and the fourth case – when wirelessly charging an electric vehicle. A comparison of existing types of connectors for charging electric vehicles has shown that the standardized interface between the charging station and the electric vehicle remains one of the most acute problems.

Інтеграція електротранспорту в Об’єднану енергетичну систему України

The fleet of electric vehicles in the world is growing rapidly, as its use allows reducing the consumption of fossil fuels, as well as the corresponding emissions of greenhouse gases and pollutants into the atmosphere. The elaboration of Ukraine’s national strategy for the development of electric transport should be based on thorough studies of the impact of its implementation on the functioning of the Integrated Energy System of Ukraine. The aim of the paper was to study the impact of the potential introduction of electric transport on the operation of the Integrated Energy System of Ukraine, namely the effect of EM charging modes on the fossil fuel consumption of the IES and therefore emissions of GHG and other pollutants. The information and software complex developed at the Institute of General Energy of the National Academy of Sciences of Ukraine was used for the calculations. A set of calculations of the operation of the IES was carried out for different charging modes of electric transport: standard, uniform and night. The use of the night charging mode of electric vehicles allows reducing the amount of fossil fuel combustion and emissions of GHG and pollutants by approximately 9%.

A novel optimization method for high-penetration electric vehicles integration to electrical distribution network

With the implementation of China’s “double carbon” strategy, the usage scale of electric vehicles has grown rapidly. Therefore, how to maintain the ideal voltage and energy curve in the distribution network with high penetration of electric vehicles is a challenging problem. In this paper, the random behaviors of fast charging, ordinary charging and discharging modes of electric vehicles have been analyzed and the mathematical formulation of the algorithm has been presented. Then, the strategy of coordinated charging-discharging stack of electric vehicles is proposed. The improved particle swarm optimization algorithm based on mixed real number and binary vector is used to solve the optimization model. The results of several case studies have also been presented in this paper to show that optimum capacitor switching and transformer tap adjustment solutions can be found to minimize the total operation cost including energy consumption, power quality and reactive power compensation equipment action cost. The paper demonstrates that the impact of high-penetration electric vehicles on the energy and voltage control of the distribution network has been solved. The proposed EV coordinated stacking method can make electric vehicles charge and discharge in an orderly queue, and ensure that the line flow does not exceed the limit. Through the proposed control strategy, the voltage curve is obviously improved, and the cost of the distribution system with large-scale EVs can be effectively reduced.

Research on the Operation Modes of Electric Vehicles in Association with a 5G Real-Time System of Electric Vehicle and Traffic

With the popularity of 5G technology and electric vehicles, many countries around the world have adopted 5G technology to build sustainable smart city systems, and intelligent transportation is an important part of smart cities. From the perspective of 5G technology innovation bringing changes to traditional industries, in this paper, we analyze the mechanism by which 5G technology drives the transformation and upgrading of the electric vehicle industry. Based on the changes brought by 5G technology to the three industries of agriculture, industry and services, we analyzed the transformation of business models brought about by 5G with respect to electric vehicle operation. Furthermore, we analyzed the data of a 5G real-time system of electric vehicle and traffic operating in Nanjing, China, for a month in 2021, with a total of 10,610 electric vehicles and 1,048,575 cases to model the modes of electric vehicle operation associated with the platform. Based on the frequency density method, we identified three typical operating modes of urban electric vehicles: private electric vehicle use instead of walking accounts for 24.8%, passenger vehicles (Uber/Didi and taxi) account for 64.4% and logistic distribution electric vehicles account for 10.8%. We developed a method to automatically identify the operating mode of electric vehicles using data from a 5G real-time electric vehicle traffic platform, which provide a reference for the operation of electric vehicles associated with the platform. This work also provides data that can be used to support the establishment of models for the commercial operation of charging points.

Robust optimal operation of energy hub incorporating integrated thermal and electrical demand response programs under various electric vehicle charging modes

Although the energy hub (EH) concept results in different benefits, the system uncertainties might affect the optimized decisions. Several studies have studied EH’s optimal operation, considering the system uncertainties. However, there is a research gap in proposing a novel EH’s robust optimal operation under various charging modes of electric vehicles (EVs), besides integrated electrical and thermal demand response programs (DRPs). The main purpose of this research is to fill such a knowledge gap. In this paper, the uncertainties of renewable energy distributed resources and electricity price have been concerned using the robust optimization method. The integrated charging load of EVs under coordinated and uncoordinated charging modes has been distinguished using the Monte Carlo simulation (MCS). Another contribution is to study different schemes of hybrid electrical, heat, and cooling energy storage systems in the introduced robust framework. Simulation results infer that a 15.87% decrement in EH’s operation cost is achievable by applying the integrated thermal and electrical DRPs, using the electric heat pump (EHP) and hybrid storage system consisting of the ice storage system. The comparative test results show that the advantages of integrated thermal and electricity DRPs and charging management of EVs are highlighted by using EHPs. The sensitivity analyses of the EH’s operation cost against the robustness efficiency parameters corresponding to the uncertainty level show that the advantages of the proposed method are highlighted while the EH’s uncertainties increase.

Service Failure Risk Assessment and Service Improvement of Self-Service Electric Vehicle

Electric vehicle sharing is necessary for achieving carbon neutrality. The self-service electric vehicle mode offers unique advantages in terms of freedom of movement and privacy protection. Meanwhile, this mode requires a high-quality service guarantee because of the separation of management and use. The purpose of this study is to propose a framework for the risk control and service optimization of self-service electric vehicles, which includes service life cycle analysis, risk assessment by using a newly integrated fuzzy failure mode and effect analysis, and a consumer satisfaction survey based on the Kano model. Sixteen services were extracted through the service life cycle analysis and online review study, and their corresponding service failures were then ranked through risk assessment. The risk assessment showed that the reliability of vehicle-related services has the greatest impact on safety, followed by financial-related and driving-safety-related services. A Kano model-based survey showed that all kinds of service failures brought significant customer non-satisfaction, while different service improvements brought differentiated satisfaction. To deeply improve service satisfaction, a Risk-Satisfaction analysis was conducted, indicating that services with high risk and high satisfaction deserve further investment.

COMPARATIVE ANALYSIS OF TECHNICAL CHARACTERISTICS OF CHARGING STATIONS OF ELECTRIC VEHICLES

The article analyzes and compares charging stations for electric vehicles and their components. The analysis of charging modes of electric vehicles showed that four internationally standardized modes are used, three of which use alternating current with single-phase and three-phase switching and only one – direct current. When charging on direct current, the fastest charging is provided. There are four standardized cases of connecting charging stations to electric vehicles. Three cases of cable connection can be used on alternating current, only the third case – on direct current, and the fourth case – when wirelessly charging an electric car. Analysis of the principles of use of charging stations showed that they classify portable, wall, and stationary stations. National standards introduce road signs for electric vehicles, and a European standard establishes harmonized identifiers for the power supply of electric vehicles. There are some standardized protocols for the interaction of the charging station and the control server, which are designed to optimize energy resources and energy production systems. A comparison of existing types of connectors for charging electric vehicles has shown that the standardized interface between the charging station and the electric vehicle remains one of the most acute problems. Recommendations on approaches to metrological support of charging stations are formulated. The issue of international and regional standardization of electricity meters of direct current for use in charging stations remains relevant. International standards are transformed into relevant European standards without changes. However, in some cases, it is necessary to develop a special European standard, in particular for meters of active electrical energy of the direct current.

Research on Urban Electric Vehicle Public Charging Network Based on 5G and Big Data

Under the pressure of energy and environmental protection, we will promote the technological progress and demonstration of electric vehicles, and the construction of charging facilities will continue. Charging facilities planning and orderly charging, as two major research directions of electric vehicle infrastructure, are of great significance for the future development of electric vehicles. The optimal charging of electric vehicles can effectively improve the safe and economic operation ability of distribution network, which is of great significance to its safe operation. Therefore, this paper proposes the outsourcing test experiment and processing of urban electric vehicle public charging network based on 5G and big data. In this paper, through the analysis of the development status of urban electric vehicles, this paper proposes to optimize the charging mode of electric vehicles by combining the charging network forward and backward algorithm. In the outsourcing test experiment, the electrical safety test shows that when the current reaches 1.1-37.1kw: 5000A, when the power factor is 0.8 ∼ 0.9, when the short-circuit current impact is tolerated, the connection device will not affect the breaking operation by contact fusion welding, and the insulation protection will not be invalid. Through investigation and analysis, the satisfaction degree of electric vehicle optimization algorithm is increasing year by year. Through the analysis of the test results, the research in this paper has achieved ideal results and made a contribution to the research of urban electric vehicle public charging network.

Random Modeling of Optimal Economic, Security and Environmental Operation of Micro-grid by Managing Responsive Loads and Charging and Discharging Electric Vehicles

The micro-grid operator must provide the energy required by its customers at the lowest cost and consider issues such as greenhouse gas emissions and security. The operator is faced with a multi-objective optimization problem in which customer demand must be provided at the lowest cost and safely. This research provides a new energy management system for islanded micro-grids. The small size of the islanded micro-grids, the high level of intermittentoperationand the low inertia of distributed generation ofinverter energy production resources make the frequency and voltage security two vital factors in the energy management system, which must be managed alongside economic-environmental policies. In this study, two practical tools are provided to help with the optimal operation and increase the profitability of the micro-grid operator. The first tool is the optimal and managed use of the V2G mode of electric vehicles. In the proposed approach, not only the penetration of electric vehicles in the network is managed but also this equipment is used to solve some of the network's challenges. The second tool is responsive loads and demand response programs in order to achieve the goals of the micro-grid operator. Covering the uncertainty of renewable energy sourcesby responsive loads, and how to model a demand response program in a micro-grid, arefollowed in this study.The strategy pursued several goals, including reducing energy and load costs, reducing the cost of charging EVs, and improving network parameters and security, such as voltage and frequency.The results confirm the effectiveness of the proposed approach

Optimal energy management strategy for plug-in hybrid electric vehicles based on a combined clustering analysis

Based on the optimization results of dynamic programming, this paper proposes an optimal rule design method for a series-parallel plug-in hybrid electric vehicle mode division strategy combining K-means clustering and improved artificial bee colony. The improved artificial bee colony algorithm uses the average of the sum of the squares of the distances method to initialize the colony to overcome the randomness of initialization and best utilize the useful information, constructs a fitness function adapted to the clustering analysis, and introduces an acceleration factor into the search equation to dynamically adjusted search scope. Combining the improved artificial bee colony algorithm with the K-means clustering algorithm, the clustering performance is improved and the optimal rule-based mode division strategy is obtained. The simulation results show that the new strategy reduces fuel consumption by 4.78% and electricity consumption by 1.81% comparing with the original strategy.

Two-phase collaborative optimization and operation strategy for a new distributed energy system that combines multi-energy storage for a nearly zero energy community

The combination of a distributed energy system and multi-energy storage system has the potential to use renewable energy on a large scale and to further improve the system’s energy efficiency. Therefore, a new type of distributed energy system that combines multi-energy storage is proposed in this paper. Its novelty is that the three types of energy storage, i.e., cold, heat and electricity, are considered simultaneously, and the electric vehicle load is also included in the distributed energy system in combination with the multi-energy storage system, which allows full consideration of the effect of multi-energy storage on the distributed energy system. Three operation modes are proposed to give full play to the advantages of the new system according to the charging mode for electric vehicles. Subsequently, a two-phase collaborative optimization method for system configuration and operation optimization is proposed, and it is applied to a nearly zero energy community. The results show that the primary energy savings rate of the distributed energy system that combines multi-energy storage is 53.5% when the electric vehicle charging load is provided by the new system, which is 17.5% higher than that of the traditional distributed energy system, while the annual cost savings rate increased by only 8.3%. In addition, the hourly operating cost of the distributed energy system that combines multi-energy storage is also significantly reduced compared with the separated production system. Therefore, the method of two-phase collaborative optimization in the new system proposed in this paper can be used to realize the optimal system configuration and operation design for energy savings and consumption reduction. Finally, the new system can provide a feasible scheme for the energy supply of a nearly zero energy community in the future.

The operating mode of electric vehicles and its impact on renewable energy consumption

Nowadays, under the dual pressure of fossil energy shortage and ecological environmental pollution, new energy vehicles have flourished in our country by virtue of their clean and low noise advantages. But correspondingly, the grid connection of electric vehicles will also bring many problems. Therefore, this article attempts to explore the operating mode of electric vehicles and its impact on the consumption of renewable energy, so as to provide reasonable planning of charging facilities and improve the top-level design of the grid.