纯电动物流车电动空气压缩机布置方案研究

电动空气压缩机为纯电动物流车提供压缩气源,以供整车制动及辅助用气装置的使用.文章基于整车性能的受影响程度进行电动空气压缩机布置的多方案分析,从多个维度进行客观评价,选取适合于整车的最优方案.此方法亦可用作其他关键件的布置校核.     

基于效率最优的四驱纯电动转矩分配仿真分析

文章针对前、后双电机动力分布式纯电动汽车,以优化能量消耗为目标,如何合理的动态分配前、后轴转矩的问题进行了研究。首先依照制动法规、驱动电机动态响应和车辆纵向平顺性等要求,提出切实可行的分配计算与优化方法,并且区分驱动和制动两种工况。之后采用循环工况仿真验证的方法,进行能耗分析。通过与固定分配方法结果的对比,验证了所提分配方法有效性。     

纯电骡子车开发及试制新方法应用

通过对比燃油汽车与纯电动汽车整车架构,分析燃油车改制纯电动骡子车的可行性。利用现有车型完成纯电动骡子车改制,不仅可以节省开发成本,还可以加快新产品升级换代。同时基于两种车型的差异性,制定相应的车型改制方案。阐述常见的改制内容与创新方法应用,为后续同平台新车型开发提供参考。     

纯电动物流车用PMSM降开关损耗控制

物流车是城市内部运送货物的重要交通工具,具有运行距离短、启停频率高、运行时间长的特点。城市内部物流车都逐步采用纯电动物流车代替传统的燃油车。针对物流车运行特点,文章对电动物流车电机控制算法进行优化,在考虑不同工况下使用不同的开关频率,降低开关损耗,减少控制器发热。通过对降低开关损耗控制方法与传统控制方法在不同车辆运行工况下对比,电机控制器发热均有所降低,同时电机控制器效率有所增加。     

电辅助驱动技术研究

文章提供一种第二轴采用传统驱动桥作为主驱动、第三轴采用电驱动桥作为辅助驱动的驱动力复合并联混合动力三轴车型方案,结合提升轴空气悬架控制技术,该方案在运营经济性方面比传统双后轴驱动车型更优。     

Shared autonomous electric vehicle (SAEV) operations across the Austin,Texas network with charging infrastructure decisions

Shared autonomous vehicles, or SAVs, have attracted significant public and private interest because of their opportunity to simplify vehicle access, avoid parking costs, reduce fleet size, and, ultimately, save many travelers time and money. One way to extend these benefits is through an electric vehicle (EV) fleet. EVs are especially suited for this heavy usage due to their lower energy costs and reduced maintenance needs. As the price of EV batteries continues to fall, charging facilities become more convenient, and renewable energy sources grow in market share, EVs will become more economically and environmentally competitive with conventionally fueled vehicles. EVs are limited by their distance range and charge times, so these are important factors when considering operations of a large, electric SAV (SAEV) fleet.This study simulated performance characteristics of SAEV fleets serving travelers across the Austin, Texas 6-county region. The simulation works in sync with the agent-based simulator MATSim, with SAEV modeling as a new mode. Charging stations are placed, as needed, to serve all trips requested (under 75 km or 47 miles in length) over 30 days of initial model runs. Simulation of distinctive fleet sizes requiring different charge times and exhibiting different ranges, suggests that the number of station locations depends almost wholly on vehicle range. Reducing charge times does lower fleet response times (to trip requests), but increasing fleet size improves response times the most. Increasing range above 175 km (109 miles) does not appear to improve response times for this region and trips originating in the urban core are served the quickest. Unoccupied travel accounted for 19.6% of SAEV mileage on average, with driving to charging stations accounting for 31.5% of this empty-vehicle mileage. This study found that there appears to be a limit on how much response time can be improved through decreasing charge times or increasing vehicle range.     

考虑电动自行车骑行的非机动车道最大纵坡探讨

现行规范要求非机动车道的最大纵坡不超过3.5%,但要在山地城市、跨江桥梁两岸慢行系统衔接等场景下满足该要求存在工程占地大、造价高、可实施性差等问题,考虑到电动自行车在非机动车出行方式中占比越来越高的实际情况,以《电动自行车安全技术规范》（GB 17761—2018）规定的国标电动自行车为研究对象对骑行过程进行受力分析,提出了可满足电动自行车骑行要求的非机动车道最大纵坡参考值,可供电动车骑行占比高的类似项目参考。     

基于USB接口的电力机车能耗记录与分析系统

以C8051F单片机作为中央处理器,采集电参数计量模块和TAX2型机车安全综合监测装置的信息,生成并存储电量消耗记录;通过USB盘转储数据到地面进行处理和分析。系统整体设计具有模块化、准确可靠的特点,对电力机车节能降耗措施提供合理的依据。     

Evolution of the household vehicle fleet: Anticipating fleet composition, PHEV adoption and GHG emissions in Austin, Texas

In today’s world of volatile fuel prices and climate concerns, there is little study on the relationship between vehicle ownership patterns and attitudes toward vehicle cost (including fuel prices and feebates) and vehicle technologies. This work provides new data on ownership decisions and owner preferences under various scenarios, coupled with calibrated models to microsimulate Austin’s personal-fleet evolution.Opinion survey results suggest that most Austinites (63%, population-corrected share) support a feebate policy to favor more fuel efficient vehicles. Top purchase criteria are price, type/class, and fuel economy. Most (56%) respondents also indicated that they would consider purchasing a Plug-in Hybrid Electric Vehicle (PHEV) if it were to cost $6000 more than its conventional, gasoline-powered counterpart. And many respond strongly to signals on the external (health and climate) costs of a vehicle’s emissions, more strongly than they respond to information on fuel cost savings.Twenty five-year simulations of Austin’s household vehicle fleet suggest that, under all scenarios modeled, Austin’s vehicle usage levels (measured in total vehicle miles traveled or VMT) are predicted to increase overall, along with average vehicle ownership levels (both per household and per capita). Under a feebate, HEVs, PHEVs and Smart Cars are estimated to represent 25% of the fleet’s VMT by simulation year 25; this scenario is predicted to raise total regional VMT slightly (just 2.32%, by simulation year 25), relative to the trend scenario, while reducing CO₂ emissions only slightly (by 5.62%, relative to trend). Doubling the trend-case gas price to $5/gallon is simulated to reduce the year-25 vehicle use levels by 24% and CO₂ emissions by 30% (relative to trend).Two- and three-vehicle households are simulated to be the highest adopters of HEVs and PHEVs across all scenarios. The combined share of vans, pickup trucks, sport utility vehicles (SUVs), and cross-over utility vehicles (CUVs) is lowest under the feebate scenario, at 35% (versus 47% in Austin’s current household fleet). Feebate-policy receipts are forecasted to exceed rebates in each simulation year.In the longer term, gas price dynamics, tax incentives, feebates and purchase prices along with new technologies, government-industry partnerships, and more accurate information on range and recharging times (which increase customer confidence in EV technologies) should have added effects on energy dependence and greenhouse gas emissions.     

基于卡尔曼滤波的4WD电动车辆寄生功率的测量技术

根据串励直流电动机工作特性,利用车辆行驶过程中较易测得的驱动电机工作电流及驱动轮转速,运用MATLAB/SIMULINK软件,建立基于卡尔曼滤波的驱动轮滑转率模型和寄生功率模型并进行仿真;通过道路试验对电动机工作电流和驱动轮转速的检测,实时预测驱动轮的滑转率与产生的寄生功率。结果表明,驱动轮滑转率和寄生功率的仿真结果与试验结果非常接近。