Progress review of US-China joint research on advanced technologies for plug-in electric vehicles

The United States and China are the world's largest automobile markets and oil consumers, and both face a severe challenge to conserve energy and reduce tailpipe emissions. Thus, both countries urgently need to transform conventional internal combustion engines to electrified powertrains. Targeting the advanced core technologies of plug-in electric vehicles(PEVs), a joint research collaboration between China and the US, called the "Clean Vehicle Consortium"(CVC), was set up in 2010. Six years of collaboration on PEV technologies has resulted in significant progress in three technical areas. Based on CVC publications,we review herein the progress made by the CVC research efforts on three key advanced PEV technologies. This includes the development of a safe battery with an energy density of 260 W h kg~(-1) and a systematic method for designing safe traction battery systems. Thus, a breakthrough in high power density and efficient traction motor systems has occurred. In addition to discussing advanced electric-drive powertrains, we also discuss global energy management strategies that aim to improve PEV energy efficiency. This discussion covers scientific and comprehensive analysis methods to analyze energy systems, which include costbenefit analyses of plug-in hybrid electric vehicles, life-cycle assessments for evaluating vehicle emissions, and PEV-ownership projections.     

Energy saving performance improvement of intelligent connected PHEVs via NN-based lane change decision

Plug-in hybrid electric vehicles(PHEVs) unite the advantages of the engine and electric motor which could provide great potential in saving energy. However, the fuel economy performance of the PHEVs is highly associated with the driving condition, especially for parallel PHEVs because they could not decouple the engine work status from the driving condition. Meanwhile, fuel economy performance is not only a longitudinal issue but also related to lane selection. Lane selection is an important driving behavior and the algorithm of lane selection is necessary for the development progress of intelligent connected vehicles. Energy consumption cost is an important part of the vehicle's using consumption cost. Therefore, lane selection strategies must consider this point.With the development of intelligent connected vehicle technology, such as V2X(Vehicle to Everything), the potential of energy consumption performance of intelligent connected PHEVs could be improved by taking environment information from V2X and smart sensors into lane selection. In this paper, a neural network(NN) based method is proposed to predict the future status of the local vehicle using the information from V2X, and then another network is used to estimate the future energy consumption of each lane. The lane selection is decided on energy consumption estimation. Lastly, the effectiveness of the method is validated by simulation using Matlab combined with SUMO(Simulation of Urban MObility).     

Future penetration and impacts of electric vehicles on transport energy consumption and CO<Subscript>2</Subscript> emissions in different Chinese tiered cities

This study focuses on the penetration of electric vehicles (EVs) within the private passenger vehicle market in selected Chinese cities categorized into different tiers. It presents an analysis of factors driving the market diffusion of EVs and the reasons for varying results across the investigated cities and provides estimates of related EV impacts on local energy consumption and CO₂ emissions. A nested multinomial model incorporating technological attributes of vehicles, energy prices, charging conditions, and incentive policies was developed for conducting a scenario analyses covering six cities. The results indicated that in a stagnation scenario in which policy support was absent, the market share of electric vehicles would be less than 7% in all six cities under investigation by 2030. In medium growth and rapid growth scenarios, the market share of EVs across the six cities was projected to be within the ranges of 29%–68% and 49%–80%, respectively. The impacts of EVs on gasoline demand depended not just on their cumulative sales but also on the share of electrified vehicle distance, and the CO₂ emission reduction effect was influenced by local EV stocks and the mix of local electricity sources. Battery costs, charging conditions, and energy prices were primary driving factors. Charging conditions and energy prices were key reasons for differences in the penetration curves among cities. These driving factors were further affected by differences in local income levels, housing and parking conditions, and availability of land resources. Subsidies were found to be effective in the short term, whereas in the medium term, tax breaks could serve as the main monetary incentive. In the long term, national policy should focus on technology-related R&D, whereas local policies should focus on the operational phase and be tailored to specific local situations.     

插入式混合电动汽车充放电行为的概率分析

随着插入式混合电动汽车（PHEVs）的大量使用,其充放电过程将对电网的安全经济运行造成重要的影响.提出与电网连接的PHEVs模型,准确反映PHEVs的充放电特性;开发基于Monte Carlo仿真的插入式混合电动汽车充放电行为的概率分析方法,用以描述PHEVs充放电的随机特性.数值仿真表明PHEVs的放电负荷和汽车接入电网（V2G）的充电容量都具有正态分布特性.     

道路营运新能源汽车减碳测算

测算车辆运行碳排放,包括燃料消耗直接碳排放与电能利用间接碳排放。基于质量平衡法得出各种燃料的碳排放系数,基于火力发电煤耗量提出纯电动汽车间接CO₂排放计算方法。采集车辆运营数据与能耗数据,计算出各运输类型与各能源类型车辆CO₂年度排放量,得出电动车辆替代传统燃料车辆后的CO₂减排率。发现除大型柴油公交及中短途城际运输车辆外,电动汽车均有明显减碳效果,小型城市配送车辆减碳率最高,达48.62%。预测火电占比降低及火力发电煤耗量降低后电动汽车的碳减排量,相对于2016年,2020年将再减碳7.07%。     

汽油品质对车辆尾气排放影响的试验研究

车辆排放标准的日益严格使油品对车辆排放的影响更加重要。通过5辆车组成的车队在各种指标不同的8种燃油上进行尾气排放试验。研究了汽油中硫含量和烯烃体积含量的变化对汽车尾气排放的影响。运用严格的统计方法对试验结果进行分析，结果表明在综合工况下，汽油中硫的质量含量的降低可以明显地降低车辆尾气的各种污染物排放；烯烃体积含量的降低对排放也有明显影响。     

Design and optimization of equivalent consumption minimization strategy for 4WD hybrid electric vehicles incorporating vehicle connectivity

This paper presents an optimized equivalent consumption minimization strategy(ECMS) for four-wheel-drive(4 WD) hybrid electric vehicles(HEVs) incorporating vehicle connectivity. In order to be applicable to the 4 WD architecture, the ECMS is designed based on a rule-based strategy and used under the condition that a certain propulsion mode is activated. Assuming that a group of 4 WD HEVs are connected and position information can be shared with each other, we formulate a decentralized model predictive control(MPC) framework that compromises fuel efficiency, mobility, and inter-vehicle distance to optimize the velocity profile of each individual vehicle. Based on the optimized velocity profile, an optimization problem considering both fuel economy and battery state of charge(SOC) sustainability is formulated to optimize the equivalent factors(EFs) of the ECMS for HEVs over an appropriate time window. MATLAB User Datagram Protocol(UDP) is used in the codes run on multiple computers to simulate the wireless communication among vehicles, which share position information via UDP-based communication, and dSPACE is used as a software-in-the-loop platform for the simulation of the optimized ECMS. Simulation results validate the control effectiveness of the proposed method.     

V2G模式下电动汽车的有序充放电策略

电动汽车规模化接入电网会对配电网的安全运行造成负面影响,研究如何控制电动汽车的充放电过程有利于配电网的安全经济运行。以削峰填谷作为优化目标,建立了基于电动汽车与电网互动(V2G)技术的光储式电动汽车充电站系统模型,提出了电动汽车定时模式、定峰模式、负荷整形模式以及V2G与储能配合模式4种有序充放电策略。基于MATLAB软件平台的算例仿真结果表明,所提策略可在一定程度上起到削峰填谷的作用,验证了所提策略的可行性和有效性。     

杭州市区机动车危险气态污染物排放的模型计算

通过对杭州市区机动车保有量及其构成、车辆登记分布和累积行驶里程的调查分析，获得了杭州市区机动车的基本运营特征参数.采用修正的MOBILE6.2 模型计算了杭州市区2003年机动车排放的危险气态污染物（苯、1,3-丁二烯、甲醛、乙醛和丙烯醛）的排放因子.并在此基础上计算了杭州市区机动车危险气态污染物的排放清单和分车型的排放分担率.结果表明，杭州市区机动车危险气态污染物的综合排放因子很高，汽油车、摩托车、重型柴油车的
排放因子分别是美国同期水平的1.3～6.9、1.7～4.4和3倍，2003年杭州市区机动车危险气态污染物苯、1,3-丁二烯、甲醛、乙醛和丙烯醛总量分别为810.0、116.7、412.2、123.8和18.0 t.研究还表明，车速对此类污染物的排放影响很大，当平均车速大于30 km/h时，排放因子明显减小.     

中国纸产品全生命周期GHG排放分析

基于生命周期评价理论与国家温室气体清单指南中废弃物处理温室气体排放计算方法,对中国2010年和2015年纸产品生命周期不同阶段的主要温室气体排放分别进行了分析.研究的纸产品生命周期评价边界包括:林木种植管理、制浆造纸过程、运输过程、废纸回收制浆、焚烧和填埋.结果表明:中国2010年和2015年纸产品生命周期温室气体排放量分别为13.4、20.3 Mt CO2-eq,其中林木种植和管理阶段为碳汇,能存储的CO2分别为82.6和108.2 Mt CO2-eq,制浆和造纸阶段为碳源,排放的GHG2分别为52.4、77.3 Mt CO2-eq,运输阶段为8.3、10.3 Mt CO2-eq,废纸焚烧和填埋阶段为35.3、40.9 Mt CO2-eq.     

汽油車顆粒物排放特性

在底盤測功機上按NEDC循環工況,使用輕型汽油車、輕型柴油車排放測試系統以及電子低壓沖擊儀(ELPI)對滿足國Ⅲ、國Ⅳ的氣道噴射和缸內直噴汽油車進行了冷起動和熱起動條件下的顆粒物排放特性研究。結果表明:國Ⅲ汽油車冷起動排出的顆粒物數目和粒徑比其他汽油車都高,而國Ⅳ直噴汽油車排出的顆粒物的表面積濃度和質量濃度最大。各種汽油車排放的粒子數濃度的數量級相同,均為106,熱起動下的顆粒物排放比冷起動減少40%。汽油車的粒徑濃度90%以上都分布在0.007～0.378μm,表面積濃度90%以上都分布在0.055～9.83μm,顆粒物質量濃度99%分布在0.091～9.83μm。ELPI計算和顆粒測試系統測量的結果都證明,氣道噴射汽油車在EUDC循環下顆粒物質量排放比ECE循環高。試驗結果也發現,ELPI計算的顆粒物質量與法規測試系統測量的顆粒物質量之間存在差異。     

机动车颗粒物排放控制策略研究

颗粒物已经成为造成环境污染和影响人体健康的主要污染物之一,而机动车颗粒物排放占污染物的60%以上。目前中国对机动车颗粒物排放的研究较少,没有系统提出相应的控制策略。文章首先分析了机动车颗粒物的生成机理及影响因素;根据《中国机动车污染防治年报》统计数据,使用MATLAB建立了汽车、低速汽车及机动车数量与颗粒物排放量之间的数学模型,预测未来5a内的机动车颗粒物的排放总量。结果表明机动车颗粒物排放逐年增加,2015年将达到1.032 2×106 t;而低速汽车数的PM排放量会逐年缓慢降低,这主要受国家政策影响。最后,根据分析预测结果,提出了机动车颗粒物排放控制策略。     

需求侧规模化电动汽车的充电负荷优化调控策略

针对电力需求侧电动汽车(electric vehicles, EV)用户充电行为的不确定性,分析电动汽车充电负荷调度与控制技术,构建电动汽车充电负荷调控优化模型,提出考虑分时电价与削峰填谷的分层多目标电动汽车充电策略,并对某区域内的1 000辆电动汽车的充电场景进行调控仿真试验。结果表明,本研究提出的优化充电策略能够有效降低充电费用和充电功率峰值,验证了所提出的优化调控策略的有效性。     

重型柴油车实际道路排放颗粒物的粒度分布

利用车载颗粒物测试系统对在实际道路上运行的重型柴油车的颗粒物排放用市内公交车测试循环进行了试验研究。粒度范围为0.007~10μm的颗粒物排放的粒度分布用一台低压电冲击器进行测量。结果表明:对于粒度为0.3μm以下的排放颗粒物数量,达到国Ⅲ排放限值的车(国Ⅲ车)比达到国Ⅱ排放限值的车(国Ⅱ车)平均高出23.8%;对于粒度为0.3μm以上的排放颗粒物数量,国Ⅲ车比国Ⅱ车平均降低27.4%,而在此粒度区间,国Ⅲ车颗粒物排放质量比国Ⅱ车的平均降低65.4%。     

并联混合动力汽车参数优化及仿真

利用ADVISOR软件进行二次开发,将原车型改成并联混合动力汽车,并设计动力系统各参数,对所匹配车辆的动力性及其在循环工况下的燃油经济性进行了仿真,并与原车型的燃油消耗进行了对比分析。实验结果表明,改装后的混合动力汽车燃油经济性有很大改善,废气排放量降低,汽车动力性能也得到提高。     

纳米三氧化二铝在柴油尾气净化中的活性评价

柴油车尾气排放的碳烟颗粒会产生了严重的环境污染问题,柴油车尾气碳烟颗粒的低温燃烧离不开高活性的催化剂。将用水热法制备出来的耐高温、中性无毒、高分散的异性纳米Al2O3颗粒直接添加在柴油中。分析评定其作为添加剂的助燃催化活性及对降低可吸入污染物尾气排放的功效。并控制粒径及形貌使助燃后的纳米Al2O3有效沉积在"后处理"装置上进一步净化尾气中微细杂质,避免PM2.5污染物流入大气,危害人体健康。项目研究中克服以往单纯依靠"后处理"装置尾气净化效果的局限性,开创使用纳米颗粒从源头上防治PM2.5产生的先例。     

电动汽车接入对光储电站电压质量的影响

电动汽车具有负荷和移动储能的双重特性,合理利用电动汽车的移动储能特性可以改善电压质量,减少电网储能装置的配置,提高能源的利用率。首先,建立了基于光储电站的微电网系统;然后,以光储电站母线电压为控制对象,提出了电动汽车的控制策略;最后,用MATLAB/Simulink对电动汽车接入电网改善电压质量的可行性进行了分析和验证。     

基于Radau伪谱法和MPC的智能电动车辆生态驾驶

为优化智能电动车能源消耗,提出了基于Radau伪谱法和模型预测控制算法的智能电动车辆生态驾驶的方案。建立生态驾驶控制模型和能耗模型,结合边界约束和路径约束,构建生态驾驶能耗优化的最优控制问题。通过能耗优化得到最优车速轨迹,将此轨迹作为期望输入,基于模型预测控制( MPC)算法完成生态驾驶控制。实验结果表明：以纯电动车和实际规划路径为例,以最优车速自动行驶的能源消耗少于人工驾驶的能源消耗,验证了文中策略的有效性。     

搭载无级变速器纯电动汽车动力性

纯电动汽车是以蓄电池为能量来源,以电动机作为驱动系统的新能源汽车。在研发阶段设计选择动力系统的参数,充分的利用和协调各部分的性能就显得十分重要。介绍了在已知电动汽车整车参数的情况下,根据电动汽车性能要求,计算选择电动机,并根据整车性能和电动机的参数设计FGR的传动比和EMCVT的传动比,比较FGR和EMCVT的最高车速、加速时间和爬坡能力方面的性能,为电动汽车与变速器的匹配奠定理论基础。     

基于制动强度的能量回收控制方法

针对高效利用电动车能量的问题,提出了一种基于制动强度的电动汽车能量回收控制方法.基于车辆制动的理想曲线和ECE曲线,结合制动强度将制动情况分成四种类型并给出了每种类型所需制动力.基于模糊控制理论提出了机械制动力和电机制动力分配比例的模糊控制模型,建立了再生制动比例与车辆行驶速度、制动力和电池电荷量三个指标之间的模糊模型.在NEDC工况上进行了实验,结果表明,本文方法在回收能量数量、能量回收率和能量效率等方面都具有更好的性能,能够使电动汽车制动策略更加科学节能.