The Future Trend of E-Mobility in Terms of Battery Electric Vehicles and Their Impact on Climate Change: A Case Study Applied in Hungary

The transportation sector is responsible for 25% of the total Carbon dioxide (CO2) emissions, whereas 60.6% of this sector represents small and medium passenger cars. However, as noted by the European Union Long-term strategy, there are two ways to reduce the amount of CO2 emissions in the transportation sector. The first way is characterized by creating more efficient vehicles. In contrast, the second way is characterized by changing the fuel used. The current study addressed the second way, changing the fuel type. The study examined the potential of battery electric vehicles (BEVs) as an alternative fuel type to reduce CO2 emissions in Hungarys transportation sector. The study used secondary data retrieved from Statista and stata.com to analyze the future trends of BEVs in Hungary. The results showed that the percentage of BEVs in Hungary in 2022 was 0.4% compared to the total number of registered passenger cars, which is 3.8 million. The simple exponential smoothing (SES) time series forecast revealed that the number of BEVs is expected to reach 84,192 in 2030, indicating a percentage increase of 2.21% in the next eight years. The study suggests that increasing the number of BEVs is necessary to address the negative impact of CO2 emissions on society. The Hungarian Ministry of Innovation and Technologys strategy to reduce the cost of BEVs may increase the percentage of BEVs by 10%, resulting in a potential average reduction of 76,957,600 g/km of CO2 compared to gasoline, diesel, hybrid electric vehicles (HEVs), and plug-in hybrid vehicles (PHEVs).

Network traffic flow evolution with battery electric vehicles and conventional gasoline vehicles

In order to investigate the effect of the use of battery electric vehicles on traffic dynamics,the valid paths of electric battery vehicles are defined and a check-based method is proposed to obtain them.Then,assuming that travelers only focus on their past travel experience,a day-to-day traffic assignment model is established based on reinforcement learning and bounded rationality.In the proposed model,the Bush-Mosteller model,a reinforcement learning model,is modified to calculate path choice probability according to bounded rationality.The modified model updates the path choice probability only if the gap between expected travel time and perceived travel time is beyond the cognitive threshold.Numerical experiments validate the effectiveness of the model and show that traffic flows can converge to the equilibrium in any case of cognitive thresholds and penetration rates of battery electric vehicles.The cognitive threshold has a positive influence on the variation of traffic flows while it has a negative influence on the differences between traffic flows.The adaptation of battery electric vehicles leads to the poor performance of the traffic system.

Towards Realistic Vibration Testing of Large Floor Batteries for Battery Electric Vehicles (BEV)

This contribution shows an analysis of vibration measurement on large floor-mounted traction batteries of Battery Electric Vehicles(BEV).The focus lies on the requirements for a realistic replication of the mechanical environments in a testing laboratory.Especially the analysis on global bending transfer functions and local corner bending coherence indicate that neither a fully stiff fixation of the battery nor a completely independent movement on the four corners yields a realistic and conservative test scenario.The contribution will further show what implication these findings have on future vibration&shock testing equipment for large traction batteries.Additionally,it will cover an outlook on how vibration behavior of highly integrated approaches(cell2car)changes the mechanical loads on the cells.

Performance Study of the MPC based on BPNN Prediction Model in Thermal Management System of Battery Electric Vehicles

In this paper,a model predictive control(MPC)based on back propagation neural network(BPNN)prediction model was proposed for compressor speed control of air conditioning system(ACS)and battery thermal management system(BTMS)coupling system of battery electric vehicle(BEV).In order to solve the problem of high cooling energy consumption and inferior thermal comfort in the cabin of the battery electric vehicle thermal management system(BEVTMS)during summer time,this paper combines the respective superiorities of artificial neural network(ANN)predictive modeling and MPC,and creatively combines the two methods and uses them in the control of BEVTMS.Firstly,based on ANN and heat transfer theory,BPNN prediction model,ACS and BTMS coupling system were established and verified.Secondly,a mathematical method of MPC was established to control the speed of the compressor.Then,the state parameters of the coupled system were predicted using a BPNN prediction model,and the predicted values were passed to the MPC,thus achieving accurate control of the compressor speed using the MPC.Finally,the effects of PID control and MPC based on BPNN prediction model on thermal comfort of cabin and compressor energy consumption at different ambient temperatures were compared in simulation under New European Driving Cycle(NEDC)conditions.The results showed for the constructed BPNN prediction model predicted and tested values of the selected parameters the mean squared error(MSE)ranged from 2.498%to 8.969%,mean absolute percentage error(MAPE)ranged from 4.197%to 8.986%,and mean absolute error(MAE)ranged from 3.202%to 8.476%.At ambient temperatures of 25℃,35℃ and 45℃,the MPC based on the BPNN prediction model reduced the cumulative discomfort time in the cabin by 100 s,39 s and 19 s,respectively,compared with the PID control.Under three NEDC conditions,the energy consumption is reduced by 1.82%,2.35%and 3.48%,respectively.When the ambient temperature was 35℃,the MPC based on BPNN prediction model can make the ACS and BTMS coupling system have better thermal comfort,and the energy saving effect of the compressor was more obvious with the temperature.

China's battery electric vehicles lead the world:achievements in technology system architecture and technological breakthroughs

Developing new energy vehicles has been a worldwide consensus,and developing new energy vehicles characterized by pure electric drive has been China's national strategy.After more than 20 years of high-quality development of China's electric vehicles(EVs),a technological R&D layout of“Three Verticals and Three Horizontals”has been created,and technological advantages have been accumulated.As a result,China's new energy vehicle market has ranked first in the world since 2015.To systematically solve the key problems of battery electric vehicles(BEVs)such as“driving range anxiety,long battery charging time,and driving safety hazards”,China took the lead in putting forward a“system engineering-based technology system architecture for BEVs”and clarifying its connotation.This paper analyzes the research status and progress of the three core components of this architecture,namely,“BEV platform,charging/swapping station,and real-time operation monitoring platform”,and their key technological points.The three major demonstration projects of the 2008 Beijing Olympic Games,the 2022 Beijing Winter Olympics,and the intelligent and connected autonomous battery electric bus project are discussed to specify the applications of BEVs in China.The key research directions for upgrading BEV technologies remain to be further improving the vehicle-level all-climate environmental adaptability and all-day safety of BEVs,systematically solving the charging problem of BEVs and improving their application convenience,and safeguarding safety with early warning and implementing active/passive safety protection for the whole life cycle of power batteries on the basis of BEVs'operation big data.BEVs have acquired new technological features such as intelligent and networked technology empowerment,extensive integration of control-by-wire systems,a platform of chassis hardware,and modularization of functional software.

Evaluation of Transmission Losses of Various Battery Electric Vehicles

Transmission losses in battery electric vehicles have compared to internal combustion engine powertrains a larger share in the total energy consumption and play therefore a major role.Furthermore,the power flows not only during propulsion through the transmissions,but also during recuperation,whereby efficiency improvements have a double effect.The investigation of transmission losses of electric vehicles thus plays a major role.In this paper,three simulation models of the Institute of Automotive Engineering(the lossmap-based simulation model,the modular simulation model,and the 3D simulation model)are presented.The lossmap-based simulation model calculates transmission losses for electric and hybrid transmissions,where three spur gear transmission concepts for battery electric vehicles are investigated.The transmission concepts include a single-speed transmission as a reference and two two-speed transmissions.Then,the transmission lossmaps are integrated into the modular simulation model(backward simulation)and in the 3D simulation model(forward simulation),which improves the simulation results.The modular simulation model calculates the optimal operation of the transmission concepts and the 3D simulation model represents the more realistic behavior of the transmission concepts.The different transmission concepts are investigated in Worldwide Harmonized Light Vehicle Test Cycle and evaluated in terms of transmission losses as well as the total energy demand.The map-based simulation model allows the transmission losses to be broken down into the individual component losses,thus allowing transmission concepts to be examined and evaluated in terms of their efficiency in the early development stage to develop optimum powertrains for electric axle drives.By considering transmission losses in detail with a high degree of accuracy,less efficient concepts can be eliminated at an early development stage.As a result,only relevant concepts are built as prototypes,which reduces development costs.

Driving and Braking Control of PM Synchronous Motor Based on Low-resolution Hall Sensor for Battery Electric Vehicle

Resolvers are normally employed for rotor positioning in motors for electric vehicles, but resolvers are expensive and vulnerable to vibrations. Hall sensors have the advantages of low cost and high reliability, but the positioning accuracy is low. Motors with Hall sensors are typically controlled by six-step commutation algorithm, which brings high torque ripple. This paper studies the high-performance driving and braking control of the in-wheel permanent magnetic synchronous motor （PMSM） based on low-resolution Hall sensors. Field oriented control （FOC） based on Hall-effect sensors is developed to reduce the torque ripple. The positioning accuracy of the Hall sensors is improved by interpolation between two consecutive Hall signals using the estimated motor speed. The position error from the misalignment of the Hall sensors is compensated by the precise calibration of Hall transition timing. The braking control algorithms based on six-step commutation and FOC are studied. Two variants of the six-step commutation braking control, namely, half-bridge commutation and full-bridge commutation, are discussed and compared, which shows that the full-bridge commutation could better explore the potential of the back electro-motive forces （EMF）, thus can deliver higher efficiency and smaller current ripple. The FOC braking is analyzed with the phasor diagrams. At a given motor speed, the motor turns from the regenerative braking mode into the plug braking mode if the braking torque exceeds a certain limit, which is proportional to the motor speed. Tests in the dynamometer show that a smooth control could be realized by FOC driving control and the highest efficiency and the smallest current ripple could be achieved by FOC braking control, compared to six-step commutation braking control. Therefore, FOC braking is selected as the braking control algorithm for electric vehicles. The proposed research ensures a good motor control performance while maintaining low cost and high reliability.

Development and Verification of the Equilibrium Strategy for Batteries in Electric Vehicles

The inconsistency of the cells in a battery pack can affect its lifespan,safety and reliability in the electric vehicles. The balanced system is an effective technique to reduce its inconsistency and improve the operating performance. A hybrid equilibrium strategy based on decision combing battery state-of-charge（ SOC） and voltage has been proposed. The battery SOC is estimated through an improved least squares method. An equalization hardware in loop（ HIL） platform has been constructed. Based on this HIL platform,equilibrium strategy has been verified under the constant-current-constant-voltage（ CCCV） and dynamicstresstest（ DST） conditions. Experimental results indicate that the proposed hybrid equalization strategy can achieve good balance effect and avoid the overcharge and over-discharge of the battery pack at the same time.

Cycle life prediction and match detection in retired electric vehicle batteries

The lifespan models of commercial 18650-type lithium ion batteries （nominal capacity of 1150 mA-h） were presented. The lifespan was extrapolated based on this model. The results indicate that the relationship of capacity retention and cycle number can be expressed by Gaussian function. The selecting function and optimal precision were verified through actual match detection and a range of alternating current impedance testing. The cycle life model with high precision （〉99%） is beneficial to shortening the orediction time and cutting the prediction cost.

Customized Optimization for Vehicle Acoustic Statistical Energy Analysis

Statistical Energy Analysis(SEA) is one of the conventional tools for predicting vehicle high-frequency acoustic responses.This study proposes a new method that can provide customized optimization solutions to meet NVH targets based on the specific needs of different project teams during the initial project stages.This approach innovatively integrates dynamic optimization,Radial Basis Function(RBF),and Fuzzy Design Variables Genetic Algorithm(FDVGA) into the optimization process of Statistical Energy Analysis(SEA),and also takes vehicle sheet metal into account in the optimization of sound packages.In the implementation process,a correlation model is established through Python scripts to link material density with acoustic parameters,weight,and cost.By combining Optimus and VaOne software,an optimization design workflow is constructed and the optimization design process is successfully executed.Under various constraints related to acoustic performance,weight and cost,a globally optimal design is achieved.This technology has been effectively applied in the field of Battery Electric Vehicle(BEV).

Intelligent Vehicle Electrical Power Supply System with Central Coordinated Protection

The current research of vehicle electrical power supply system mainly focuses on electric vehicles（EV） and hybrid electric vehicles（HEV）.The vehicle electrical power supply system used in traditional fuel vehicles is rather simple and imperfect;electrical/electronic devices（EEDs） applied in vehicles are usually directly connected with the vehicle＇s battery.With increasing numbers of EEDs being applied in traditional fuel vehicles,vehicle electrical power supply systems should be optimized and improved so that they can work more safely and more effectively.In this paper,a new vehicle electrical power supply system for traditional fuel vehicles,which accounts for all electrical/electronic devices and complex work conditions,is proposed based on a smart electrical/electronic device（SEED） system.Working as an independent intelligent electrical power supply network,the proposed system is isolated from the electrical control module and communication network,and access to the vehicle system is made through a bus interface.This results in a clean controller power supply with no electromagnetic interference.A new practical battery state of charge（So C） estimation method is also proposed to achieve more accurate So C estimation for lead-acid batteries in traditional fuel vehicles so that the intelligent power system can monitor the status of the battery for an over-current state in each power channel.Optimized protection methods are also used to ensure power supply safety.Experiments and tests on a traditional fuel vehicle are performed,and the results reveal that the battery So C is calculated quickly and sufficiently accurately for battery over-discharge protection.Over-current protection is achieved,and the entire vehicle＇s power utilization is optimized.For traditional fuel vehicles,the proposed vehicle electrical power supply system is comprehensive and has a unified system architecture,enhancing system reliability and security.

Modeling and Optimization of Heat Dissipation Structure of EV Battery Pack

In order to solve the problems of high temperature and inconsistency in the operation of electric vehicle（ EV） battery pack,computational fluid dynamics（ CFD） simulation method is used to simulate and optimize the heat dissipation of battery pack. The heat generation rate at different discharge magnifications is identified by establishing the heat generation model of the battery. In the forced air cooling mode,the Fluent software is used to compare the effects of different inlet and outlet directions,inlet angles,outlet angles,outlet sizes and inlet air speeds on heat dissipation. The simulation results show that the heat dissipation effect of the structure with the inlet and outlet on the same side is better than that on the different sides; the appropriate inlet angle and outlet width can improve the uniformity of temperature field; the increase of the inlet speed can improve the heat dissipation effect significantly. Compared with the steady temperature field of the initial structure,the average temperature after structure optimization is reduced by 4. 8℃ and the temperature difference is reduced by 15. 8℃,so that the battery can work under reasonable temperature and temperature difference.

Operation Strategy of EV Battery Charging and Swapping Station

An operation strategy of the electric vehicle （EV） battery charging and swapping station is proposed in the paper. The strategy is established based on comprehensively consideration of the EV charging behaviors and the possible mutual actions between battery charging and swapping. Three energy management strategies can be used in the station： charging period shifting, energy exchange between EVs, and energy supporting from surplus swapping batteries. Then an optimization model which minimizes the total energy management costs of the station is built. The Monte Carlo simulation is applied to analyze the characteristics of the EV battery charging load, and a heuristic algorithm is used to solve the strategy providing the relevant information of EVs and the battery charging and swapping station. The operation strategy can efficiently reduce battery charging during the high electricity price periods and make more reasonable use of the resources. Simulations prove the feasibility and rationality of the strategy.

Equalization Charging and Protection System for Electric Vehicle

A system is developed to improve the series battery packs uniformities and charging protection and the implementation of battery equalization charging and protection system is also introduced. The functions of equalization charging and overcharging protection are analyzed and the control model of series battery packs equalization charging is setup. The diverting-current and feedback bus voltage are measured during the series Li-ion battery packs equalization charging experiment. The field operation on Electric luxury transit bus BFC6100EV shows that the system betters the battery series charging uniformities and overcharging protection, improves the battery performance and extends the battery life.

The Electric Vehicle beyond Transport： Contexts for Meanings and Services Related to Batteries on Wheels

This paper explores the potential meanings of battery electric vehicles （battery EVs）. Relevant ideas were collated through facilitated exchange of explicated and tacit knowledge, realized by individual essay preparation and a facilitated seminar workshop. Additional classifications and clustering by the author led to the following principal results： the EV as a power source and buffer forms the foundation for most meanings beyond transport. EVs can act both in the context of＂shelters＂ for individuals as well as ＂community vehicles＂ with a focus on, e.g., local renewable energy production integration. Reduced to a simple product, EVs can also be designed to make sense in developing country environments. However, many ＂intelligent＂ features associated to EVs are available also for combustion engine vehicles and thus provide only necessary, but not unique added value to EVs. Concluding, EVs will take over market share from internal combustion vehicles only if they satisfy human needs beyond mobility.

Analysis of Adverse Effects on Performance due to Battery Deterioration Installed in BEV and HEV

This paper reports the results of investigating the permissible amount of battery deterioration. An investigation was carried out using the following two types of vehicles： a BEV （battery electric vehicle） and a HEV （hybrid electric vehicle）. First, a detailed evaluation was carried out to identify how the vehicle performance was adversely affected as the lithium-ion batteries installed in the vehicles deteriorated. Next, an attempt was made to determine the permissible amount of deterioration for the vehicle-mounted lithium-ion batteries. In the case of the BEV, the driving distance declined by 20% when the capacity maintenance rate was approximately 80%. Therefore, this was specified as the permissible amount of battery deterioration for the BEV. In the case of the HEV, the fuel consumption increased by 20% when the maximum battery output maintenance rate was approximately 40%. Therefore, this was specified as the permissible amount of battery deterioration for the HEV.

Numerical Study of Heat Transfer Enhancement in the Electric Vehicle Battery via Vortex‑Induced Agitator

Convective heat transfer plays an important role in the development of a high-performance battery cell.Electric vehicles carry a large amount of the battery cells to reach a longer range of endurance mileage.Thermal diffusion around the battery cells can be considered as obstacles to improve the convective heat transfer coefficient.In this paper,a novel agitator taking advantage of strong vortices is designed to disrupt the thermal boundary layer around the battery cells,thereby improving the fluid mixing for enhanced convective heat transfer.A fluid–structure interaction algorithm is developed to simulate the convective heat transfer rate at various flapping motion.Under the comparison with clean channel,the vortex-induced vibra-tion by the agitated beam can increase the average Nusselt number by 119.59%.This research can be applied to optimize the thermal-structure design inside the electric vehicle battery.

Storage technologies for electric vehicles

This review article describes the basic concepts of electric vehicles(EVs)and explains the developments made from ancient times to till date leading to performance improvement of the electric vehicles.It also presents the thorough review of various components and energy storage system(ESS)used in electric vehicles.The main focus of the paper is on batteries as it is the key component in making electric vehicles more environment-friendly,cost-effective and drives the EVs into use in day to day life.Various ESS topologies including hybrid combination technologies such as hybrid electric vehicle(HEV),plug-in HEV(PHEV)and many more have been discussed.These technologies are based on different combinations of energy storage systems such as batteries,ultracapacitors and fuel cells.The hybrid combination may be the perspective technologies to support the growth of EVs in modern transportation.The advanced charging systems may also play a major role in the roll-out of electric vehicles in the future.The general strategies of advanced charging systems are explained to highlight the importance of fast charging time with high amount of power and its cost-effectiveness for electric vehicles.Furthermore,the battery pack designing calculation is briefly explained along with all mechanical,electrical and environmental battery tests,which helps in the evaluation of batteries.Moreover,this paper also has a brief summarizing with the help of a flow chart,which clearly demonstrates all the parts of electric vehicles in a much simpler way.

Techno-economic analysis of the adoption of electric vehicles

Significant advances in battery technology are creating a viable marketspace for battery powered passenger vehicles.Climate change and concerns over reliable supplies of hydrocarbons are aiding in the focus on electric vehicles.Consumers can be influenced by marketing and emotion resulting in behaviors that may not be in line with their stated objectives.Although sales of electric vehicles are accelerating,it may not be clear that purchasing an electric vehicle is advantageous from an economic or environmental perspective.A technoeconomic analysis of electric vehicles comparing them against hybrids,gasoline and diesel vehicles is presented.The results show that the complexity of electrical power supply,infrastructure requirements and full life cycle concerns show that electric vehicles have a place in the future but that ongoing improvements will be required for them to be clearly the best choice for a given situation.

Performance of the Transmission Parking Mechanism of a Battery Electric Vehicle Simulated with Adams Software

The electric parking mechanism is studied for an electrically controlled two-speed auto transmission that is being developed for electric vehicles.Safety requirements include low-speed safe parking,reliable self-lock and the avoidance of abnormal parking.A dynamic model of the parking mechanism is established and analyzed using Adams software.Finally,failure of the parking mechanism due to wear is observed in bench testing and compared with experimental results after optimization.