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).

Energy Control of Plug-In Hybrid Electric Vehicles Using Model Predictive Control With Route Preview

The paper proposes an adoption of slope,elevation,speed and route distance preview to achieve optimal energymanagement of plug-in hybrid electric vehicles(PHEVs).Theapproach is to identify route features from historical and real-time traffic data,in which information fusion model and trafficprediction model are used to improve the information accuracy.Then,dynamic programming combined with equivalent con-sumption minimization strategy is used to compute an optimalsolution for real-time energy management.The solution is thereference for PHEV energy management control along the route.To improve the system's ability of handling changing situation,the study further explores predictive control model in the real-time control of the energy.A simulation is performed to modelPHEV under above energy control strategy with route preview.The results show that the average fuel consumption of PHEValong the previewed route with model predictive control(MPC)strategy can be reduced compared with optimal strategy andbase control strategy.

Simulation research of energy management strategy for dual mode plug-in hybrid electrical vehicles

In this paper, a plug-in hybrid electrical vehicle(PHEV) is taken as the research object, and its dynamic performance and economic performance are taken as the research goals. Battery charge-sustaining(CS) period is divided into power mode and economy mode. Energy management strategy designing methods of power mode and economy mode are proposed. Maximum velocity, acceleration performance and fuel consumption are simulated during the CS period in the AVL CRUISE simulation environment. The simulation results indicate that the maximum velocity and acceleration time of the power mode are better than those in the economy mode. Fuel consumption of the economy mode is better than that in the power mode. Fuel consumption of PHEV during the CS period is further improved by using the methods proposed in this paper, and this is meaningful for research and development of PHEV.

Analysis of Hybrid Rechargeable Energy Storage Systems in Series Plug-In Hybrid Electric Vehicles Based on Simulations

In this paper, an extended analysis of the performance of different hybrid Rechargeable Energy Storage Systems (RESS) for use in Plug-in Hybrid Electric Vehicle (PHEV) with a series drivetrain topology is analyzed, based on simulations with three different driving cycles. The investigated hybrid energy storage topologies are an energy optimized lithium-ion battery (HE) in combination with an Electrical Double-Layer Capacitor (EDLC) system, in combination with a power optimized lithium-ion battery (HP) system or in combination with a Lithium-ion Capacitor (LiCap) system, that act as a Peak Power System. From the simulation results it was observed that hybridization of the HE lithium-ion based energy storage system resulted from the three topologies in an increased overall energy efficiency of the RESS, in an extended all electric range of the PHEV and in a reduced average current through the HE battery. The lowest consumption during the three driving cycles was obtained for the HE-LiCap topology, where fuel savings of respectively 6.0%, 10.3% and 6.8% compared with the battery stand-alone system were achieved. The largest extension of the range was achieved for the HE-HP configuration (17% based on FTP-75 driving cycle). HP batteries however have a large internal resistance in comparison to EDLC and LiCap systems, which resulted in a reduced overall energy efficiency of the hybrid RESS. Additionally, it was observed that the HP and LiCap systems both offer significant benefits for the integration of a peak power system in the drivetrain of a Plug-in Hybrid Electric Vehicle due to their low volume and weight in comparison to that of the EDLC system.

An optimal energy management development for various configuration of plug-in and hybrid electric vehicle

Due to soaring fuel prices and environmental concerns, hybrid electric vehicle(HEV) technology attracts more attentions in last decade. Energy management system, configuration of HEV and traffic conditions are the main factors which affect HEV's fuel consumption, emission and performance. Therefore, optimal management of the energy components is a key element for the success of a HEV. An optimal energy management system is developed for HEV based on genetic algorithm. Then, different powertrain system component combinations effects are investigated in various driving cycles. HEV simulation results are compared for default rule-based, fuzzy and GA-fuzzy controllers by using ADVISOR. The results indicate the effectiveness of proposed optimal controller over real world driving cycles. Also, an optimal powertrain configuration to improve fuel consumption and emission efficiency is proposed for each driving condition. Finally, the effects of batteries in initial state of charge and hybridization factor are investigated on HEV performance to evaluate fuel consumption and emissions. Fuel consumption average reduction of about 14% is obtained for optimal configuration data in contrast to default configuration. Also results indicate that proposed controller has reduced emission of about 10% in various traffic conditions.

基于实时交通信息的PHEV模型预测控制策略研究

为提升插电式混合动力汽车(PHEV)的燃油经济性,提出了一种基于实时交通信息的车速预测方法,并以燃油经济性最优为目标,借助动态规划(DP)算法在预测时域内进行实时最优转矩分配,建立基于模型预测控制(MPC)的整车能量管理策略。MATLAB/Simulink仿真平台验证结果表明:与传统车速预测方法相比,基于实时交通信息的车速预测方法的车速预测精确度提高了13.5%;与基于历史车速的模型预测控制策略相比,基于实时交通信息的模型预测控制策略使整车燃油经济性提高了9.5%。

基于深度强化学习的THS-Ⅲ平台PHEV能量管理策略研究

针对THS-Ⅲ平台的插电式混合动力汽车提出一种基于深度强化学习的能量管理策略。首先,使用MATLAB/Simulink搭建车辆前向仿真模型;其次,建立车辆能量管理的马尔可夫过程和深度强化学习算法;最后,使用WLTC-Class3和ACC-60工况进行了仿真验证。结果表明,与基于规则的能量管理策略相比,基于深度强化学习的能量管理策略在WLTC-Class3工况下总花费节省16.51%,燃油消耗量下降15.56%,在ACC-60工况下总花费节省31.95%,燃油消耗量下降29.96%。

OPTIMAL TORQUE CONTROL STRATEGY FOR PARALLEL HYBRID ELECTRIC VEHICLE WITH AUTOMATIC MECHANICAL TRANSMISSION

In parallel hybrid electrical vehicle （PHEV） equipped with automatic mechanical transmission （AMT）, the driving smoothness and the clutch abrasion are the primary considerations for powertrain control during gearshift and clutch operation. To improve these performance indexes of PHEV, a coordinated control system is proposed through the analyzing of HEV powertrain dynamic characteristics. Using the method of minimum principle, the input torque of transmission is optimized to improve the driving smoothness of vehicle. Using the methods of fuzzy logic and fuzzy-PID, the engaging speed of clutch and the throttle opening of engine are manipulated to ensure the smoothness of clutch engagement and reduce the abrasion of clutch friction plates. The motor provides the difference between the required input torque of transmission and the torque transmitted through clutch plates. Results of simulation and experiments show that the proposed control strategy performs better than the contrastive control system, the smoothness of driving and the abrasion of clutch can be improved simultaneously.

基于多目标优化的加速意图识别PHEV能量管理策略研究

为了使插电式混合动力汽车(plug-in hybrid electric vehicle,PHEV)能够获得更好的燃油经济性,本文提出了一种基于多目标优化的加速意图识别能量管理策略,在基于规则型能量管理策略的基础上采用模糊控制器构建起加速意图识别模块,通过引入修正系数对整车需求转矩进行实时修正,实现更符合驾驶员意图的转矩输出,同时利用多目标粒子群算法对整车的传动比进行优化以提升整车燃油经济性,利用CRUISE软件搭建整车模型与MATLAB/Simulink进行联合仿真验证策略的有效性。仿真结果表明:在世界轻型车辆测试循环(world light vehicle test cycle,WLTC)工况下,当起始动力电池荷电状态(state of charge,SOC)为70%时,对比基于多目标优化的加速意图识别策略与单一的加速意图识别策略,前者的燃油经济性提升了0.48%;当起始SOC为35%时,前者的燃油经济性提升了2.22%,由此得出基于多目标优化的加速意图识别策略对于提升整车燃油经济性具有较好的效果。

Applications of Serial-Parallel Compensated Resonant Topology in Wireless Charger System Used in Electric Vehicles

There are lots of factors that can influence the wireless charging efficiency in practice, such as misalignment and air-gap difference, which can also change all the charging parameters. To figure out the relationship between those facts and system, this paper presents a serial-parallel compensated(SPC) topology for electric vehicle/plug-in hybrid electric vehicle(EV/PHEV) wireless charger and provides all the parameters changing with corresponding curves. An ANSYS model is built to extract the coupling coefficient of coils. When the system is works at constant output power, the scan frequency process can be applied to wireless power transfer(WPT) and get the resonant frequency. In this way, it could determine the best frequency for system to achieve zero voltage switching status and force the system to hit the maximum transmission efficiency. Then frequency tracking control(FTC) is used to obtain the highest system efficiency. In the paper, the designed system is rated at 500 W with 15 cm air-gap, the overall efficiency is 92%. At the end, the paper also gives the consideration on how to improve the system efficiency.

Vehicle-to-grid power system services with electric and plug - in vehicles based on flexibility in unidirectional charging

With proper power scheduling and dynamic pricing,a unidirectional charger can provide benefits and regulation services to the electricity grid,at a level approaching that of bidirectional charging.Power scheduling and schedule flexibility of electric and plug-in hybrid vehicles are addressed.The use of electric vehicles(EVs)as flexibility resources and associated unidirectional vehicle-to-grid benefits are investigated.Power can be scheduled with the EV charger in control of charging or via control by a utility or an aggregator.Charging cost functions suitable for charger-and utility-controlled power scheduling are presented.Ancillary service levels possible with unidirectional vehicle-to-grid are quantified using sample charging scenarios from published data.Impacts of various power schedules and vehicle participation as a flexibility resource on electricity locational prices are evaluated.These include benefits to both owners and load-serving entities.Frequency regulation is considered in the context of unidirectional charging.

Plug-In Vehicle Acceptance and Probable Utilization Behaviour

This paper presents a study undertaken to understand the plug-in vehicle acceptance and probable utilization behaviour in terms of charging habits and utility factor (probability of driving in electrical mode). A survey was designed to be answered via World Wide Web, throughout 3 months and only accessible to Portuguese inhabitants. The survey was composed by biographical and car ownership info, mobility patterns, awareness toward plug-in vehicle technologies, price premium and, finally, potential buyer’s attitudes regarding charging vehicles with electricity from the grid. An explanation of how each vehicle technology works in the case of a regular hybrid (HEV), a plug-in hybrid (PHEV) and a pure electric vehicle (EV) was provided. A total sample of 809 volunteers answered the survey, aged above 18 years old, 50% male and 50% female. The results allowed the estimation of the typical daily driving distance, the Utility Factor curve for plug-in hybrid future users, the charging preferences for future users of pure electric or plug-in hybrid vehicles and the necessary feebates to promote the market penetration of such technologies. Other correlations were also analyzed between driving patterns, type of owned car, price premium and the willingness to buy pure electric and plug-in hybrid vehicles. The main policy implications are that an increase of awareness campaigns is necessary if the government intends to support the plug-in electric vehicle technology widespread and a minimum of 5000 € investment per ton of avoided CO2 will be necessary in a year.

PHEV电池包热管理系统设计优化与仿真分析

为实现电池包热管理系统低能耗和高效率散热的目的,文章通过流体动力学(CFD)仿真及实验对某插电式混合动力汽车(PHEV)乘用车电池包热管理系统进行优化研究。电池包热管理系统采用液冷散热,流场压力损失设计目标值为27kPa。初始方案中,流场压力损失实测值约为60 kPa,CFD仿真分析表明,液冷系统流场进出口是产生压力损失的主要部件;采用增大进出口管径的方法对液冷系统进行优化,仿真和实验结果表明,优化后的液冷系统压力损失减小至26 kPa左右;液冷系统流场优化后,对电池包散热特性进行仿真和实验分析,结果表明,在67.6 kW工况下电池包最高温度为53.2℃,低于目标值55℃。综合分析可以得出结论,优化后的电池包液冷系统各项指标达到目标状态。

Plug-in混合动力汽车能量管理策略全局优化研究

应用动态规划全局优化算法,针对并联式Plug-in混合动力汽车在不同行驶里程下的能量管理策略进行了全局优化研究。结果表明:车辆的行驶里程小于55km时应使用电动机为主的能量管理策略,当车辆的行驶里程大于55km时应使用发动机为主的能量管理策略;在动态规划最优控制下,车辆行驶里程为55km时整车经济性能最佳,行驶里程小于110km时整车平均等价油耗为2.7L/100km,相对于原型车经济性提高了近58%。

Plug-In并联式混合动力汽车实时优化能量管理策略

能量管理策略是混合动力汽车的核心技术之一,其品质直接影响车辆的动力性、经济性和排放性能。首先制定了基于确定性规则的Plug-In并联式混合动力汽车能量管理策略;然后,为了提高车辆的燃油经济性,设计了电池能量观测单元,并对等效燃油消耗最小策略进行改进,提出了适用于Plug-In混合动力汽车的实时优化能量管理策略。研究结果表明,该能量管理策略显著提高了Plug-In并联式混合动力汽车的燃油经济性。

并联式混合动力汽车(PHEV)动态协调控制方法硬件在环仿真

在指出并联式混合动力汽车(Parallel hybrid electric vehicle,PHEV)发动机与电动机动力耦合过程中存在的协调问题基础上,提出基于模型匹配控制的动态协调控制方法,开发出双驱动电动机结构的硬件在环仿真试验平台硬件系统和基于Matlab/Simulink/RTWT与Visual C++环境的软件系统,并建立PHEV动态协调控制方法硬件在环仿真试验台。对所设计的动态协调控制方法进行硬件在环仿真试验,试验结果表明,该动态协调控制方法能有效控制两个动力源的动力耦合过程,具有较高的转矩控制精度和很好的动态响应特性。

基于模糊控制策略的PHEV仿真研究

针对并联式混合动力汽车,在电辅控制策略的基础上设计一种基于模糊逻辑推理的动力分配控制策略。将其模型嵌入仿真软件ADVISOR中,在CYC_EUDC循环道路工况下进行仿真计算。仿真结果表明:与电辅控制策略相比,采用模糊逻辑控制策略的混合动力电动汽车具有较好的经济性、排放性、鲁棒性,能够使发动机尽量集中工作在优化工作曲线附近,并保证电池SOC在较小的范围内变化。