Development Of Electric Vehicles Research Articles

Relationships between Electroencephalogram and Thermal Perception of Passenger in Winter Vehicle Compartments

The development of electric vehicles (EVs) has prompted a critical examination of the trade-off between range and human thermal comfort. Therefore, an accurate, real-time assessment of human thermal perception inside vehicles is important. This study investigates an electroencephalogram- (EEG-) based method for evaluating human thermal comfort in the vehicle passenger compartment. Under transient winter heating conditions, the study experimentally investigates the correlation between objective physiological parameters (skin temperature and electroencephalogram) and subjective human thermal perception. The results reveal distinct patterns in EEG signals corresponding to changes in thermal perception. Specifically, the δ rhythm exhibits a U-shape variation with increasing thermal perception, while the θ, α, β, and γ rhythms display an inverted U-shape variation. Differences in each frequency band across thermal comfort states in humans are greater than differences in the frequency band across thermal sensation states. Furthermore, the relative power of the θ rhythm emerges as the most effective in discerning the thermal perception state of the human body. The EEG signal characteristics of the T7 and T8 channels align more closely with human thermal sensation, whereas the AF4 channel excels at discriminating the state of human thermal comfort. The insights gained from this study serve as a foundation for evaluating human thermal perception in vehicles, enhancing human-vehicle interaction, and addressing challenges related to human thermal comfort and vehicle range.

Burns Resulting from Electric Vehicle Manufacturing in Silicon Valley.

The development of electric vehicles (EVs) has introduced novel technologies and manufacturing processes that expose workers to new risks of burn injury. We identified six patients who were admitted to our burn center for injuries that occurred while working in EV manufacturing facilities. The burns fell into three categories: flash flame burns due to lithium-ion battery explosions, high-voltage electrical injuries, and burns caused by contact with molten metal. Recognizing these recurrent patterns of injury should inform future prevention efforts and prepare health systems to evaluate and treat patients burned in EV manufacturing.

A case study on the potential impact of a private vehicles switch to electric vehicles in Lagos, Nigeria.

Lagos is a major city in Africa that faces environmental challenges such as carbon emissions and air pollution. With the rising cost of fossil fuels and increasing environmental awareness, the movement of private vehicles to electric vehicles is worth discussing. This paper explores the potential impacts of switching private vehicles to electric vehicles in Lagos, including the impacts on air quality, carbon emissions, and energy infrastructure. The paper analyses the data by analysing the current state of transportation in Lagos, current energy demand and supply. It also discusses the future technology and costs of switching private vehicles to electric vehicles in Lagos, and forecasts the challenges and opportunities for the future development of electric vehicles in Lagos. It also explores current government actions and progress in related areas. The paper discusses and analyses various aspects of the conversion of private vehicles to electric vehicles in Lagos, Nigeria, and provides a reference for the future development of related areas.

Electric Vehicle Supply Chain Risk Assessment Based on Combined Weights and an Improved Matter-Element Extension Model: The Chinese Case

In order to meet energy and environmental challenges, many countries will implement the replacement of fuel vehicles for the future clean energy transition; so, the number of electric vehicles (EVs) operating in cities will grow significantly. It is crucial to assess the risks of the electric vehicle supply chain (EVSC) and prevent them. Based on this, this paper proposes an EVSC risk research framework with combined weights and an improved matter-element extension model: (i) Firstly, the EVSC evaluation index system is constructed from the six stages of supply chain planning, sales, procurement, manufacturing, distribution, after-sales, and external risks. (ii) The subjective and objective weights are calculated by the decision laboratory method and entropy weight method, respectively, and then the minimum deviation method is used for a combined design to overcome the defects of a single method. (iii) An improved matter-element extension model (MEEM) is constructed by introducing asymmetric proximity degree and risk bias. (iv) The model is applied to a case study and its feasibility and superiority are verified through sensitivity analysis and comparative analysis. The final results show that the method and framework proposed in this paper are in line with EVSC risk assessment standards and superior to other models, which can help EVSC managers to identify potential risks, formulate appropriate risk prevention measures, promote the stable development of electric vehicles, and provide a reference for the development of energy and environment.

End User Incentive-based Approach for Fast Charging Station

The development of electric vehicles (EVs) is influenced by various factors such as cost, autonomy, charging speed, and infrastructure. The objective of this research paper is to model an EV fast-charging station that provides incentives to end users in terms of money. The charging station incorporates a renewable energy source (solar) and an energy storage system, taking into account the demand for EVs, state of charge (SOC), and vehicle arrival and departure times. This approach aims to increase the revenue of the station and reduce the high energy demand from the grid. To incentivize end users, the vehicle-to-grid (V2G) and battery swapping modes have been implemented. The Monte Carlo approach is used to model the demand for EVs and the production of renewable energy, considering hourly intervals. Subsequently, the installation and utilization of the EV fast-charging station (EVCS) are optimized using the Adaptive Harris Hawk Optimization (AHHO) algorithm. The system is analyzed with and without V2G and battery swapping modes. The comparison between the two modes reveals that the system with V2G and battery swapping provides both revenue and incentives to end users.

Enhancing control disorder and implementing V2X-Based suppression methods for electric vehicle CO2 thermal management systems

In recent years, the development of electric vehicles (EVs) thermal management systems has underscored the crucial role in ensuring driving safety and optimizing driving range has become increasingly prominent. However, the inherent dynamic complexity of EV operation coupled with automatic control systems, can sometimes lead to unstable behavior, resulting in performance degradation and safety risks for compressors and batteries. To effectively address this issue, an evaluation was conducted on the dynamic control characteristics of an EV thermal management system utilizing CO2 as the refrigerant in this study. Through mathematical modeling and experimental analysis, the erratic nature of the dynamic thermal process was first identified. The underlying reasons were elucidated, focusing on system control characteristics and intrinsic mechanisms. It was found that control disorder could induce abnormal actions in thermal management system components like compressors and expansion valve, leading to significant performance decline and issues such as liquid carryover in compressor suction. Furthermore, specific control disorder regions of CO2 heat pumps for EVs were delineated, providing a framework for assessing the likelihood of system control disorder. Notably, control disorder was more likely to occur under conditions of low indoor air flow rate, high ambient temperature, and low supply air temperature. Given the widespread nature of this issue and the lack of suitable solutions, two control disorder suppression schemes were developed using V2X technology and validated through simulation. Results showed that adoption of V2X communication technology prevented an average of 70.1 % COP degradation, ensuring stability and safety of compressors and batteries under various operating conditions. The research provides useful information for exploring the dynamic characteristics of CO2 thermal management systems, offering a novel approach to enhance the system stability and efficiency.

Medium- and Long-Term Electric Vehicle Ownership Forecasting for Urban Residents

With the rapid development of electric vehicles (EVs) in Chinese cities, accurately forecasting the number of EVs used by urban residents in the next five years and more long term is beneficial for the government to adjust industrial policies of EVs, guide the rational planning of urban charging facilities and supporting distribution network, and achieve the rational and orderly development of the EV industry. The paper considers the advantages of using the grey GM(1,1) prediction model to predict the short-term ownership of EVs by urban residents. Then, by forecasting the number of EV users in a certain city in the future and predicting the number of private vehicles in the future, the boundary conditions for long-term year ownership of EVs by residents are determined. Combined with historical data and short-term forecast data generated by the grey prediction model, the model parameters that include the innovation coefficient and imitation coefficient of the Bass model are trained using a genetic algorithm. Finally, the Bass model is used for medium- to long-term ownership forecasting from 2023 to 2040. The prediction error for the target year is provided. The simulation results indicate that the ownership of resident EVs in this city will experience rapid growth in the next five years.

Review on preheating systems for Lithium-ion batteries of electric vehicles under low temperature circumstance

Nowadays, energy and environmental protection issues have become the focus of most attention. The development of electric vehicles which depends on lithium ion battery as power source is one of the most applicable way in dealing with these issues. Lithium-ion battery (LIB) is highly favoured for its outstanding features in energy density, cycle life and energy retention. However, its severe sensitivity to working temperatures leads to problems when driving electric vehicles. Therefore, researchers and engineers have explored approaches to guaranteeing a suitable working temperature for LIB, one of which is the battery preheating system. To clarify the advancement of this system, both internal and external preheating methods studied in recent years are summarized, and the discussion for future research is included.

An Investigative Study on the Development Strategies for Electric Vehicle Enterprises

With the continuous development of science and technology, cars have become an indispensable means of transportation for human beings in daily travel. More and more cars appear in our life. In recent years, as consumer awareness of energy conservation and environmental protection has increased, global demand for sustainable development has increased, and many new energy vehicles. Because the non-renewable resources such as oil and natural gas needed by traditional fuel cars are consumed faster and faster, the exhaust emissions of traditional cars are polluting the environment increases, so new energy vehicles are the future development trend of the automobile industry. With the international context of the rapid development of new energy trams, the sales volume of electric vehicles in China's automobile market is not good. Through data analysis and industry research, the key factors and reasons affecting the development of electric vehicles are found, make certain suggestions to Chinese new energy electric vehicle companies, in order to change the current situation of low sales of new energy vehicles, the report objectively and truly analyses the future planning of the development of Chinese electric vehicle enterprises and the change of the development trend, as well as the moderate fine-tuning of the sales pricing.

Enhancing electromagnetic compatibility and energy efficiency of electric vehicle charging stations

Problem. The article proposes a single-link structure for an electric vehicle charging station utilizing an active four-square rectifier with power factor correction. A Matlab model of the proposed charging station is developed, taking into account parameters such as the power network, the switches of the active rectifier, its automatic control system, and an equivalent model of the battery compartment. Additionally, a mathematical model for calculating static and dynamic losses is created based on polynomial approximation of the energy dependencies of IGBT modules. The analysis investigates power quality parameters, components of energy losses, and efficiency of the charging station across various charge currents and PWM frequencies during a full battery charge interval. Goal. The aim of this study is to propose a single-link structure for an electric vehicle charging station using an active four-square rectifier with power factor correction. It includes an analysis of power quality parameters, components of energy losses, and efficiency of the charging station at different charge currents and PWM frequencies during a full battery charge interval. Methodology. To achieve the goal, several key steps are considered. These include theoretical substantiation of the scheme of the electric microgrid charging station for electric vehicles with one-stage energy conversion, analysis of the battery connection scheme in the Tesla Model S electric car, research and calculation of efficiency, modeling of the charging station, development of a Matlab model of a microgrid system for the charging station, SAC analysis of battery charge voltage and current of a three-phase AV with PWM, modeling of losses in IGBT modules by polynomial approximation of dependencies, distribution of losses in the charging station system, and analysis of energy efficiency parameters. Results. The study presents the energy efficiency parameters of an external DC EV charging station using an active rectifier. It reveals that maximum efficiency of the system is achieved at minimum charge current. However, decreasing the charge current prolongs the charge process and slightly affects power quality parameters. Originality. A mathematical model for calculating static and dynamic losses was developed based on polynomial approximation of the energy dependencies of IGBT modules. The analysis encompasses power quality parameters, components of energy losses, and efficiency of the charging station across various charge currents and PWM frequencies during a full battery charge interval. Practical value. This study contributes to the further development of electric vehicles by improving the energy indicators of electric vehicle batteries and converters of electric vehicle charging stations, enabling fast charging modes. Active development is observed in each of these directions.

Development of an electric drive for personal light electric vehicles

Problem. The article addresses the challenge of enhancing inclusive mobility and environmental cleanliness by developing a traction electric drive for personal light electric vehicles. A study was conducted on modern electric drive systems for personal light electric vehicles. Goal. The aim is to boost inclusive mobility and environmental cleanliness through the development of a traction electric drive for a personal light electric vehicle, specifically based on a tricycle. Methodology. The methodology involves scientific analysis and synthesis of traction electric drives for electric vehicles. An assessment of the nominal capacity of the battery module from the Nissan Leaf electric car was conducted using both partial discharge procedures and the Leaf Spy Pro program. Results. Based on an analysis of existing electric drive systems, a traction electric drive for a tricycle was developed. A functional diagram of the electric bicycle drive was generated. A control system for a sensorless brushless motor was developed, determining rotor position by measuring EMF in the free phase. This led to the creation of a stable voltage electrical circuit with a virtual midpoint. The tricycle's electric drive utilizes two 10-inch motor wheels on the rear wheels, enabling high speed and efficiency. Controllers specifically designed for electric wheel motors with a power of 350 W were selected to control the traction electric drive. Modules from the 2015 Nissan Leaf electric car's battery, which had depleted 20% of their capacity, were chosen to power the electric drive. The battery health status is 77.95%. A model of the battery's electrical equivalent circuit was constructed, and partial discharge graphs of the Nissan Leaf battery module were analyzed. Originality. The results provide a comprehensive insight into the development of a traction electric drive for personal light electric vehicles, using a tricycle as an example. Practical value. The research led to the development of an electric drive for a three-wheeled vehicle, with two motor wheels of 350 W nominal power each. The power supply voltage ranges from 36 V to 48 V, powered by six battery modules from the Nissan Leaf electric car, totaling 48 V. The energy capacity of one battery module is 0.3898 kWh, resulting in a total energy capacity of 2.3388 kWh for the vehicle's battery. However, the realizable capacity does not exceed 1.871 kWh, providing a travel distance of approximately 75 km on one battery charge. These findings demonstrate the feasibility of reusing batteries from electric cars with diminished capacity to power light electric vehicles. The results are relevant for scientific and technical professionals involved in electric vehicle development.

Technical Study for the Development of Air Brake Compressor in Electric Commercial Vehicles

<div>The development of electric commercial vehicles brought up novel challenges in the design of efficient and reliable air brake systems. The compressor is one of the critical components of the air brake system and is responsible for supplying pressurized air to the brake system. In this study, we aimed to gather essential information regarding the pressure and flow rate requirements for the compressor in the air brake system of electric commercial vehicles. We extensively analyzed the existing air brake systems utilized in conventional commercial vehicles. We examined the performance characteristics of reciprocating compressors traditionally employed in these systems. Recognizing the need for novel compressor designs tailored to electric commercial vehicles, we focused on identifying the specifics such as efficiency, performance characteristics, reliability, and cost of the compressor.</div> <div>Our study utilized theoretical calculations to ascertain the optimal pressure and flow rate parameters. By thoroughly evaluating vehicle brake standards and meticulously analyzing relevant data, we gained a comprehensive understanding of the performance requirements for compressors in electric commercial vehicle air brake systems. Our analysis considered various factors, including vehicle weight, stopping distance, and operational conditions, providing valuable insights into the specific needs of these systems.</div> <div>The research results serve as the foundation for developing compressors that are more efficient, reliable, and compatible with electric vehicles equipped with regeneration capabilities. Ultimately, implementing these improvements will raise the standard for safety, reliability, and overall performance in the air brake systems of electric commercial vehicles.</div>

Graphene oxide–lithium-ion batteries: inauguration of an era in energy storage technology

Abstract A significant driving force behind the brisk research on rechargeable batteries, particularly lithium-ion batteries (LiBs) in high-performance applications, is the development of portable devices and electric vehicles. Carbon-based materials, which have finite specific capacity, make up the anodes of LiBs. Many attempts are being made to produce novel nanostructured composite anode materials for LiBs that display cycle stability that is superior to that of graphite using graphene oxide. Therefore, using significant amounts of waste graphene oxide from used LiBs represents a fantastic opportunity to engage in waste management and circular economy. This review outlines recent studies, developments and the current advancement of graphene oxide-based LiBs, including preparation of graphene oxide and utilization in LiBs, particularly from the perspective of energy storage technology, which has drawn more and more attention to creating high-performance electrode systems.

A-LLTO Nanoparticles Embedded Composite Solid Polymer Electrolyte for Room Temperature Operational Li-metal Batteries.

Solid-state batteries (SSBs) have the potential to revolutionize the current energy storage sector. A significant portion of the current development of electric vehicles and the electrification of various appliances relies on Lithium (Li)-ion batteries. However, future energy demands will require the development of stronger and more reliable batteries. This report presents a novel solid state electrolyte (SSE) composed of a self-healing composite solid polymer electrolyte (CSPE) matrix and aluminum-doped (Li0.33La0.56)1.005Ti0.99Al0.01O3 (A-LLTO) nanofillers. The CSPE contains Jeffamine ED-2003 monomer, Benzene-1,3,5-tricarbaldehyde (BTC)crosslinker dissolved in a 1:1 ratio of Dimethylformamide (DMF) to LiPF6, and a certain amount (x) of A-LLTO nanofillers (x=5, 7.5, 10, 12.5%). A CSPE containing x-amount of A-LLTO fillers (referred to as CAL-x%) demonstrates excellent ion-conducting properties and stable battery performance. The CAL-10% demonstrates 1.1×10-3Scm-1 of ionic conductivity at room temperature (RT). A-LLTO nanofillers dispersed uniformly within the polymer matrix form a percolation network, which is believed to improve ionic conductivity and the diffusion of Li+ ions. The CR-2032 cell, consisting of LiFePO4 (LFP)║CAL-10%║Li, at RT offers an initial discharge capacity of ≈165mAhg-1 at 0.1C rate for 120 cycles with 98.85% coulombic efficiency (C.E.).

Dynamic Wireless Charging of Electric Vehicles Using RFID Protection

Abstract: Electric vehicle (EV) development in transportation is growing rapidly, offering clean and sustainable transportation. The key challenges in the EV are high cost, limited range, battery recycling, charging infrastructure, and many more. Among these challenges, charging presents a double difficulty: limited availability and slow charging times. To address these challenges, charging infrastructure needs to be expanded, develop wireless charging technologies and advancements in battery technologies. In wireless charging there is static, charging while the vehicle is at rest, and dynamic, charging when the vehicle is in motion. EVs can be charged dynamically while they are moving, maximizing energy efficiency and reducing downtime for charging. In this paper a small-scale prototype for dynamic wireless charging with Radio Frequency Identification (RFID), is discussed. RFID integration enables convenient and secure user access and prevents energy theft by unauthorized charging. RFID tag is positioned at the start of the charging path. The dynamic charging system with RFID protection is shown to be feasible and effective by the prototype. The prototype has to demonstrate its capacity to safely and effectively charge EVs in real time while reducing the possibility of unwanted access or energy theft.

A frequency cooperative control strategy for multimicrogrids with EVs based on improved evolutionary-deep reinforcement learning

The construction of microgrid has fully promoted the large-scale access of distributed power and the rapid development of electric vehicles (EVs). And microgrid system faces operational issues such as strong random disturbances from distributed power sources and loads, as well as unexpected events during operation. These issues can lead to unstable microgrid frequency, excessive discharge of EVs, and increased control costs. To solve the issues, a frequency cooperative control strategy for multimicrogrids with EVs based on improved evolutionary-deep reinforcement learning (EDRL) is proposed in this paper. First, consider the effect of the vehicle-to-grid (V2G) process on the minimum time required to fully charge an EV, and the impact of the output distribution of micro turbines (MTs) on the regulation cost, and based on the coupling relationship between generator terminal voltage regulation and system frequency control, a multimicrogrid comprehensive control model is constructed. Second, in order to deal with engineering tasks with deceptive rewards and sparse rewards such as integrated frequency control, evolutionary algorithms and deep reinforcement learning algorithms are combined to effectively assist the training process to jump out of local optimal solutions and approach optimal control strategies. Meanwhile, the algorithm is improved based on the novelty search and intelligent partition strategy, so that the strategy has better convergence characteristics and can reduce the cost of information transmission and computational complexity under the premise of ensuring the control effect. Furthermore, the state space, action space and reward function of the controller are defined. Finally, the simulation results show that the proposed controller has the ability of coordinated control, can effectively reduce the adjustment cost of MT unit and the unnecessary discharging of EVs while ensuring the frequency regulation requirements of each submicrogrid, which is far superior to PID control, fuzzy control, and traditional deep reinforcement learning control.

Low-carbon planning of urban charging stations considering carbon emission evolution characteristics and dynamic demand

As a new generation of transportation, electric vehicles play an important role in carbon-peak targets. The development of electric vehicles needs the support of a charging network, and improper planning of charging stations will result in a waste of resources. In order to expand the charging network of electric vehicles and give full play to the low-carbon and efficient characteristics of electric vehicles, this paper proposed a charging station planning method that considers the characteristics of carbon emission trends. This paper combined the long short-term memory (LSTM) network with the stochastic impacts by regression on population, affluence, and technology (STIRPAT) model to predict the carbon emission trend and quantified the correlation between the construction speed of a charging station and the evolution characteristics of carbon emission by Pearson’s correlation coefficient. A multi-stage charging station planning model was established, which captures the dynamic characteristics of the charging demand of the transportation network and determines the station deployment scheme with economic and low-carbon benefits on the spatiotemporal scale. The Pareto frontier was solved by using the elitist non-dominated sorting genetic algorithm. The model and solution algorithm were verified by the actual road network in a certain area of Shanghai. The results showed that the proposed scheme can meet the charging demand of regional electric vehicles in the future, improve the utilization rate of charging facilities, and reduce the carbon emission of transportation networks.

Visual research on data distribution of electric vehicle charging piles in China

With the popularity of electric vehicles, the demand for charging piles is also increasing. It is of great significance that the distribution of electric vehicle charging piles is studied for urban planning, traffic management and energy policy. This paper discusses the distribution of charging piles in China using visual charts, analyzes in detail the growth in the number of charging piles of different companies, the characteristics of geographical distribution, and the types of charging pile. Meanwhile, the differences in the distribution of charging piles in different types of cities are discussed using Shanghai and Nanchang as examples. Through the analysis of these data, the charging pile network structure can be further optimized, a valuable reference basis is provided for urban planning and the development of electric vehicles.

Performance of Modular Multilevel Converter in Electric Vehicles Charging Station

The awareness of air pollution is the main reason for the development of Electric Vehicles. Hence, the many number of Electric vehicle connected to grid produce power quality problem in conversion of AC-DC. In this paper, to avoid this drawback, the MATLAB/SIMULINK model of Modular Multi Level Converter is implemented in charging station. MMC not only provide bidirectional flow but also improve power quality. The converter works on boost mode and buck mode. In G2V, the boost mode is for charging the battery of electric vehicle and buck mode is discharging the battery. For, the G2V, the buck mode reduces the voltage to charge the battery with current or voltage constant which is about the state of the charge of the battery. The out of the battery is pure dc with mmc which replace the filter also. It increases the life of the battery. The model of the MMC-based charger for electric vehicle was created in MATLAB/Simulink, and simulation results shows the output power of the MMC and circulation current is controlled.

Large-scale research on durability test cycle of fuel cell system based on CATC

Durability is one of the technical bottlenecks restricting fuel cell electric vehicle development. As a result, significant time and resources have been invested in research related to this area worldwide. Current durability research mainly focuses on the single cell and stack levels, which is quite different from the usage scenarios of actual vehicles. There is almost no research on developing durability test cycles on the fuel cell system level. This paper proposes a universal model for developing a durability test cycle for fuel cell system based on the China automotive test cycle. Large-scale comparison tests of the fuel cell systems are conducted. After 1000 h test, the output performance degradation of three mass-produced fuel cell system is 14.49%, 9.59%, and 4.21%, respectively. The test results show that the durability test cycle proposed in this paper can effectively accelerate the durability test of the fuel cell system and evaluate the durability performance of the fuel cell system. Moreover, the methodology proposed in this paper could be used in any other test cycles such as NEDC (New European Driving Cycle), WLTC (Worldwide Harmonized Light Vehicles Test Procedure), etc. And it has comprehensive application value and are significant for reducing the cost of durability testing of fuel cell systems and promoting the industrialization of fuel cell electric vehicles.