Flexible predictive power-split control for battery-supercapacitor systems of electric vehicles using IVHS

The utilization of traffic information received from intelligent vehicle highway systems(IVHS) to plan velocity and split output power for multi-source vehicles is currently a research hotspot. However, it is an open issue to plan vehicle velocity and distribute output power between different supply units simultaneously due to the strongly coupling characteristic of the velocity planning and the power distribution. To address this issue, a flexible predictive power-split control strategy based on IVHS is proposed for electric vehicles(EVs) equipped with battery-supercapacitor system(BSS). Unlike hierarchical strategies to plan vehicle velocity and distribute output power separately, a monolayer model predictive control(MPC) method is employed to optimize them online at the same time. Firstly, a flexible velocity planning strategy is designed based on the signal phase and time(SPAT) information received from IVHS and then the Pontryagin’s minimum principle(PMP) is adopted to formulate the optimal control problem of the BSS. Then, the flexible velocity planning strategy and the optimal control problem of BSS are embedded into an MPC framework, which is online solved using the shooting method in a fashion of receding horizon. Simulation results verify that the proposed strategy achieves a superior performance compared with the hierarchical strategy in terms of transportation efficiency, battery capacity loss, energy consumption and computation time.

A model-based driving cycle test procedure of electric vehicle batteries

The battery test methods are the key issues to investigate the energy-storage characteristics and dynamic characteristics of electric vehicle(EV) batteries.In this paper,the research advances of existing battery test methods as well as driving cycles are reviewed.An electric vehicle model that consists of EV dynamics model,battery model and electric motor model is built.The dynamic characteristics of the battery in frequency domain are analyzed.Based on the EV model and the frequency domain characteristics of the battery,a driving cycle test procedure of EV battery is proposed.The battery test procedure is able to reflect the real-world characteristics of EV batteries,and can be used as a universal EV battery test method.

Electric Vehicles Analysis inside Electric Mobility Looking for Energy Efficient and Sustainable Metropolis

This paper aims to study and evaluate electric mobility over time, focusing on the development of the electric car. Methodologically, in order to accomplish this intent, the characterization of the electric vehicle (EV) is made based on the variables which determine its performance, such as: assessment of speeds, distance traveled, analysis of facts related to the energy source (electro-chemical accumulators) and analysis of the determining system of electric mobility (the electric engine as a function of power (W) and voltage (V)). This way, to demonstrate the effects of time, this process will be analyzed from the beginning of the 20th century (1930s) to the present (the first decade of the 21st century), methodologically structured in 4 cycles that show the performance of the EV. The results show the existence of vulnerabilities and of electric mobility potential, as well as the nuances of the development of the electric vehicle along the years and along the transformations in what is considered state-of-the-art. Thus, in the case of batteries, it is evident that the lithium-ion type used nowadays reveals better results due to its higher specific efficient energy, which maximizes energy autonomy to 200 km. In the beginning, the insertion of the electric vehicle was commercially harmed by the fundamental limitations of batteries as a power source. Conclusively, on certain occasions there have been improvements in the aerodynamics, engines, weight and size of the batteries, demonstrating the maturity of EVs.

Decision Aid Model for Private-owned Electric Vehicles Participating in Frequency Regulation Ancillary Service Market

To reduce the difficulty and enhance the enthusiasm of private-owned electric vehicles(EVs) in participating in frequency regulation ancillary service market(FRASM), a decision aid model(DAM) is proposed. This paper presents three options for EV participating in FRASM, i. e., the base mode(BM), unidirectional charging mode(UCM), and bidirectional charging/discharging mode(BCDM), based on a reasonable simplification of users' participating willingness. In BM, individual EVs will not be involved in FRASM, and DAM will assist users to set the optimal charging schemes based on travel plans under the time-of-use(TOU) price. UCM and BCDM are two modes in which EVs can take part in FRASM. DAM can assist EV users to create their quotation plan, which includes hourly upper and lower reserve capabilities and regulation market mileage prices. In UCM and BCDM, the difference is that only the charging rate can be adjusted in the UCM, and the EVs in BCDM can not only charge but also discharge if necessary. DAM can estimate the expected revenue of all three modes, and EV users can make the final decision based on their preferences. Simulation results indicate that all the three modes of DAM can reduce the cost, while BCDM can get the maximum expected revenue.

Design of a Level-3 electric vehicle charging station using a 1-MW solar system via the distributed maximum power point tracking technique

Solar power is mostly influenced by solar irradiation,weather conditions,solar array mismatches and partial shading conditions.Therefore,before installing solar arrays,it is necessary to simulate and determine the possible power generated.Maximum power point tracking is needed in order to make sure that,at any time,the maximum power will be extracted from the photovoltaic system.However,maximum power point tracking is not a suitable solution for mismatches and partial shading conditions.To overcome the drawbacks of maximum power point tracking due to mismatches and shadows,distributed maximum power point tracking is util-ized in this paper.The solar farm can be distributed in different ways,including one DC-DC converter per group of modules or per module.In this paper,distributed maximum power point tracking per module is implemented,which has the highest efficiency.This technology is applied to electric vehicles(EVs)that can be charged with a Level 3 charging station in<1 hour.However,the problem is that charging an EV in<1 hour puts a lot of stress on the power grid,and there is not always enough peak power reserve in the existing power grid to charge EVs at that rate.Therefore,a Level 3(fast DC)EV charging station using a solar farm by implementing distributed maximum power point tracking is utilized to address this issue.Finally,the simulation result is reported using MATLAB®,LTSPICE and the System Advisor Model.Simulation results show that the proposed 1-MW solar system will provide 5 MWh of power each day,which is enough to fully charge~120 EVs each day.Additionally,the use of the proposed photovoltaic system benefits the environment by removing a huge amount of greenhouse gases and hazardous pollutants.For example,instead of supplying EVs with power from coal-fired power plants,1989 pounds of CO_(2) will be eliminated from the air per hour.

Auto-Test on Motor Temperature Rising in Electric Vehicles with Mutual MRAS

A new method to calculate the motor temperature rising in electric vehicle （EV） is proposed based on the stator resistance identification. The measure theory of the motor temperature rising with the stator resistance is discussed at first. An enhanced magnetism motor dynamic math model is built which is the research object. Then the resistance identification system model is built on the mutual model reference adaptive,system （MRAS） theory. The simulation diagram of the mutual MRAS model is constructed and the resistance identification performance is studied in different motor states. Simulation results indicate that the stator resistance identification model with the mutual MRAS is effective. At the same time, the identification of motor temperature rising is possible with the identification of the stator resistance.

Thermal analysis of surface-mounted permanent magnet synchronous motor for electric vehicle application

As a driving motor, surface mounted permanent magnet synchronous motor exhibits high efficiency and high power density. However, it is susceptible to suffer irreversible demagnetization and insulation failure of coils under severe thermal load condition. Therefore, it is essential to predict temperattrre distribution in the driving motor. In this paper, a lumped parameter thermal mode/of surface mounted permanent magnet is investigated. By using finite element method, the iron loss distribution in various parts of the driving motor is achieved. Moreover, the influences of interface gap and flow rate on temperature distribution are discussed. Finally, the simulation of temperature distribution in different parts of the driving motor is achieved. The presented methodology contributes to verify the feasibility of the driving motor design.

考虑车网互动的园区电网动态双层能量管理策略

为解决大量接入的清洁能源出力波动和充电场内汽车数量的随机变化给电网能量管理带来的困难,提出一种园区电网双层优化控制策略.上层基于模型预测控制技术建立风光储集成动态优化模型,综合应用园区电池储能系统和电动汽车(EV)电池储能系统参与电网能量平衡.下层则考虑同时满足EV车主对EV的充电需求和上层能量调度的车网互动管理需求,制定园区电网内停车场的EV有序充放电策略.仿真算例验证表明:所提策略能将分散园区各处的EV储能集成为统一虚拟储能,扩展园区电网储能系统,增加可再生分布式电源的消纳与园区电网的经济效益.

考虑规划需求的EV充电桩集群管理系统通信方式综合评价

综合考虑经济性、技术性、适用性构建电动汽车(EV)充电桩集群管理系统通信方式的评价指标体系,并提出一种考虑规划需求的管理系统通信方式综合评价方法。该方法利用云模型反映主观评价信息的不确定性和模糊性,而后综合多组评价意见采用最大云相似度原则实现定性指标的定量表征;在此基础上,对各指标引入充电桩集群或充电站的规划需求因素,并采用考虑规划需求的灰色综合评价方法对各待选通信方式进行适应性评价。结合某规划新区所属的充电桩集群进行实例分析,验证了该方法的合理性、准确性以及优越的技术区分度,为实际设计充电桩集群管理系统组网方案提供了一种客观的决策手段。

基于工况识别的IWM-EV主动悬架MOPSO模糊滑模控制

轮毂电机电动汽车(in-wheel motor electric vehicle,IWM-EV)的电机激励与车辆系统的耦合特性严重的恶化车辆的动力学性能以及电机的工作稳定性,针对这种振动负效应问题,建立了考虑机电耦合的车辆动力学耦合模型,并设计了工况识别的主动悬架多目标粒子群(multi-objective particle swarm optimization,MOPSO)模糊滑模控制器。基于傅里叶级数法建立了轮毂电机的垂向不平衡激励与电机转矩的电机模型;将电机模型与车辆动力学模型结合建立了电机与悬架联合的垂向-驱动非线性动力学耦合模型。基于耦合模型分析了车辆的机电耦合振动负效应特性,针对模型强非线性的特点,设计了耦合模型的非线性控制器。仿真结果表明,控制器能既能有效的减小电机的相对偏心率,抑制电机不平衡电磁力,又能提升车辆动力学性能,有效的抑制了轮毂电机电动汽车的振动负效应。

电动汽车电驱动系统容性轴电压建模研究

基于高频和低频信号的不同特征,进行了分离建模,提出了一种无需通电便可预测电动汽车电驱动系统容性轴电压的模型和估计方法。在轴电压模型的基础上,进一步考虑变速箱的影响,建立了变速箱的电路模型,从而可获得变速箱传动轴与电机轴的轴电压估计,实现电动汽车电驱动系统的轴电压建模和计算。通过实验对电机轴电压进行了测量,并将实测电机轴电压与仿真数据进行了对比,对比结果验证了模型的准确性。

高速公路高峰期部署移动充电车的综合效用分析

随着电动汽车(Electric Vehicle,EV)普及率的不断提高,充电基础设施不足成为其发展的主要瓶颈,特别是在高速公路高峰期,充电需求激增,传统固定充电站无法灵活应对这一挑战。文章提出了一种创新解决方案——部署移动充电车,以缓解高峰期的充电难题。从技术可行性、经济效益和环境影响三个方面对移动充电车进行了综合分析。研究结果表明,移动充电车依靠先进的充电技术和高效的电池管理系统,能够提供快速、安全且稳定的充电服务。与固定充电站相比,移动充电车具有较低的初始投资和运营成本,并通过灵活调度和多样化的收益模式展现出显著的经济效益。同时,移动充电车在减少碳排放、优化能源利用和缓解环境压力方面表现出积极的环保效应。综上所述,移动充电车在解决高速公路高峰期电动汽车充电难题方面具有巨大潜力,未来可在更大范围内推广应用,不仅支持电动汽车产业的可持续发展,还能推动绿色交通体系的建设。

计及多重不确定性的规模化电动汽车接入配电网调度方法

规模日益增长的电动汽车和可再生能源带来的不确定性给配电网的安全运营带来了严峻挑战。为综合考虑多重不确定性、平衡运营成本与系统可靠性,首先,提出一种基于分布鲁棒联合机会约束的电动汽车-配电网充放电调度模型。该模型将节点电压、支路功率、备用需求等通过联合机会约束建模,可以直观地管理系统整体的可靠性。然后,为求解该模型,基于最优Bonferroni近似方法将联合机会约束问题转化为混合整数二次规划模型,其中,风险等级也被视为决策变量。随后,在不同电力系统上验证了所提模型的有效性和可扩展性。结果表明,所提模型克服了经典的随机优化和鲁棒优化存在的问题,能够有效平衡成本和可靠性,计算效率高、可扩展性好,较Bonferroni近似方法降低约6.5%的成本。

电动汽车换电服务使用意愿等研究动态

选取来自国际学术期刊的论文,以概述形式对城市交通理论方法、实证分析等学术研究成果进行总结性介绍,旨在增强城市交通业界和学界对国际学术动向和研究热点的关注,促进学术交流。本期共选取4篇论文,前3篇论文与电动汽车充电、换电相关,分别关注电动汽车换电服务使用意愿、共享微出行服务和新型补能基础设施用户使用意愿,以及公众是否支持建设电动汽车换电站,并针对政策制定者提出了富有建设性的意见;最后一篇论文关注北京市城市绿化对共享单车使用的影响,认为城市绿化具有显著潜力,能够降低汽车依赖并减少出行相关的碳排放。

电动汽车充电平台充电桩数量和价格协同优化

基于随机效用最大化理论,提出电动汽车充电平台用户端的用户行为决策模型.在满足车辆服务需求和充电站约束条件下,分别推导企业利润最大化和社会福利最大化目标函数下的卡罗需-库恩-塔克(KKT)条件、最优数量和最优价格,通过数值实验分析参数敏感性.最优化结果表明,合适的充电价格和充电桩数量决定用户前往不同区域充电的意愿,充电价格和充电桩数量在多区域多时段都有最优解.模型结果表明:在空间上,价格和数量随距离增加呈现递减趋势,且递减幅度增大;在时间上,高峰期的定价高于低谷期的定价,低谷期的区域间定价差异大于高峰期的区域间定价差异.对比不同目标,社会福利最大化目标下的最优充电价格普遍低于利润最大化目标下的价格,社会福利最大化下的最优充电桩数量多于利润最大化下的充电桩数量.敏感性参数分析结果表明,电池容量、单位电池容量的充电时长、多项Logit(MNL)模型中的敏感度均与目标结果呈现负相关,与感知效用呈正相关.

Vehicle-to-Grid Technology： State-of-the-Art and Future Scenarios

An overview of V2G （vehicle-to-grid） technology is presented in this paper, it aims to highlight the main features, opportunities and requirements of V2G. Thus, after briefly resuming the most popular charging strategies lbr PEVs （plug-in electric vehicles）, the V2G concept is introduced, especially highlighting its potentiality as a revenue opportunity ｜br PEV owners： this is mainly due to the V2G ability to provide ancillary services, such as load leveling, regulation and reserve. Such solutions have been thoroughly investigated in the literature from both the economic and technical points of view and are here reported. In addition, V2G requirements such as mobility needs, charging stations availability and appropriate PEV aggregative architectures are properly taken into account. Finally, future developments and scenarios have also been reported.

考虑用户充电决策行为的电动汽车充电引导策略

快充站(fast charging station,FCS)是电动汽车(electric vehicle,EV)的重要能源供给设施。随着EV的推广应用,快充负荷也逐渐攀升,对配电网运行产生了一定影响。然而,快充负荷作为一种需求侧响应资源,可通过有序充电控制缓解EV接入给配电网运行带来的负面影响,因此文中提出考虑用户充电决策行为的EV充电引导策略。首先,考虑动态交通路况影响,利用出行链理论构建EV移动模型,进行用户出行模拟,并刻画剩余电量的时空分布。其次,考虑剩余电量、充电设施分布与充电服务价格,利用后悔理论构建用户充电决策模型,并刻画充电负荷时空分布。然后,以配电网网损最小为目标,构建充电服务价格优化模型,通过优化公共FCS的充电服务价格,引导充电负荷时空分布。最后,对不同服务价格方案进行对比,结果表明,文中方法对小容量车型的引导效果更好,且用户时间消耗等效折算系数越大,文中方法对充电负荷引导的效果越好。

基于DEB-ABC算法的电动汽车充电优化调度模型

随着电动汽车保有量不断上升,其相关配套设施也面临巨大挑战,不合理的充电资源分配在充电高峰期会造成部分充电站过度拥挤,并且影响电网稳定运行.提出一种考虑多目标优化的调度模型,通过分析充电站内不同充电选项的排队时间,并根据排队率和分时电价提出一种动态定价模型,影响车主充电行为,结合动态定价模型与充电需求计算充电成本,考虑基于起讫点的充电总路径行驶时间,以总成本最少为优化目标,基于DEB-ABC算法进行求解.在某区域内对1500辆电动汽车进行仿真验证,结果表明提出的优化调度模型可减少充电等待时间、充电成本和总行驶时间,提高区域内充电站利用率.

配置光伏变换器电池的电动汽车数学模型研究

目前主要环境问题之一是机动车排放的CO_(2)和其他有害物质。根据测试,所有机动车种类中最环保的还是电动汽车。但是,只有使用环保型电源为电动汽车充电,才能确保低排放。为解决电能传输中的损耗,常用方法是将光伏转换器(PVC)电池应用于电动汽车结构中。该文建立电动汽车在平坦无变形水平地面上直线运动的数学模型,利用地面中压移动理论、系统设计、电路理论和数学建模等方法,验证电动汽车结构中使用的非扁平PVC电池的计算方法,适用于研究电动汽车与PVC电池之间的能量交换过程及其对里程的影响。

Travel Intention with Shared Electric Vehicles Based on Theory of Multiple Motivations for Urban Governance

Determining the travel intention of residents with shared electric vehicles(EVs)is significant for promoting the development of low-carbon transportation,considering that common problems such as high idle rate and lack of attractiveness still exist.To this end,a structural equation model(SEM)based on the theory of multiple motivations is proposed in this paper.First,the influencing motivations for EV sharing are divided into three categories:consumer-driven,program-driven,and enterprise-driven motivations.Then,the intentions of residents in Shanghai to travel with shared EVs are obtained through a survey questionnaire.Finally,an SEM is constructed to analyze quantitatively the impact of different motivations on the travel intention.The results show that consumer-driven motivations with impact weights from 0.14 to 0.63 have the overwhelming impact on travel intention,compared to program-driven motivations with impact weights from−0.14 to 0.15 and enterprise-driven motivations with impact weights from 0.02 to 0.06.In terms of consumer-driven motivations,the weight of green travel awareness is the highest.The implications of these results on the policy to enable large-scale implementation of shared EVs are discussed from the perspectives of the resident,enterprise,and government.