基于ADVISOR的纯电动汽车动力系统匹配及仿真

纯电动汽车作为新能源汽车行业发展的主要方向,在发展其核心技术中,动力系统的匹配对于发展纯电动汽车具有重要的意义,合理的动力系统匹配影响着汽车的动力性和续航里程等因素。根据纯电动汽车的整车参数和性能指标,计算选择动力系统的基本参数,并利用ADVISOR仿真软件进行仿真分析,为改进技术提供依据,验证了设计的有效性。     

重型道路交通事故模块化智能综合救援车的研制

针对拥堵及狭窄道路环境、多种等级路面以及灾害破损路面条件下的交通事故快速抢通救援需求,研发设计具有作业系统模块化设计组合及集成匹配技术、适用于多路况的专用底盘技术、智能化多传感辅助操作及安全监控技术等多种技术融合的重型道路交通事故模块化智能综合救援车,使得道路交通应急救援技术装备更加专业化、高效化。     

Electric vehicle charging station locations: Elastic demand,station congestion,and network equilibrium

Battery-only electric vehicles (BEVs) generally offer better air quality through lowered emissions, along with energy savings and security. The issue of long-duration battery charging makes charging-station placement and design key for BEV adoption rates. This work uses genetic algorithms to identify profit-maximizing station placement and design details, with applications that reflect the costs of installing, operating, and maintaining service equipment, including land acquisition. Fast electric vehicle charging stations (EVCSs) are placed across a congested city's network subject to stochastic demand for charging under a user-equilibrium traffic assignment. BEV users’ station choices consider endogenously determined travel times and on-site charging queues. The model allows for congested-travel and congested-station feedback into travelers’ route choices under elastic demand and BEV owners’ station choices, as well as charging price elasticity for BEV charging users.Boston-network results suggest that EVCSs should locate mostly along major highways, which may be a common finding for other metro settings. If 10% of current EV owners seek to charge en route, a user fee of $6 for a 30-min charging session is not enough for station profitability under a 5-year time horizon in this region. However, $10 per BEV charging delivers a 5-year profit of $0.82 million, and 11 cords across 3 stations are enough to accommodate a near-term charging demand in this Boston-area application. Shorter charging sessions, higher fees, and/or allowing for more cords per site also increase profits generally, everything else constant. Power-grid and station upgrades should keep pace with demand, to maximize profits over time, and avoid on-site congestion.     

PHEV发动机驱动工况效率耦合分析与优化控制

单轴并联式混合动力系统（Parallel Hybrid Electric Vehicle,PHEV）包括电池、驱动电机、发动机、自动变速器等多个关键部件。各部件效率特性存在相互耦合的关系,要实现系统整体效率最优,需要辨明影响系统效率的控制参数,并对系统整体效率最优的控制参数进行优化。以装备无级变速器（Continuously Variable Transmission,CVT）的PHEV为研究对象,首先对系统各关键部件的效率特性进行分析,建立各关键部件效率模型,明确各部件效率与控制参数、状态参数之间的关系。在此基础上,对发动机单独驱动模式下动力传递路径中不同部件的效率耦合关系进行分析,推导出系统燃油消耗量与动力系统各状态参数、控制参数之间的函数关系。根据分析结果,选取车辆需求功率及车速为状态参数,变速器速比及发动机转矩为控制参数,以系统燃油消耗量最小为目标建立优化目标函数和约束条件,对系统优化问题进行定义。根据优化问题的特点,设计基于模拟退火的优化算法对优化问题进行求解,获取系统燃油消耗率最小时变速器目标速比和发动机目标转矩随状态参数的变化关系。建立系统仿真模型对所述优化算法进行仿真分析,并搭建混合动力试验台对优化结果进行试验验证。结果表明：无级变速器效率对系统整体效率影响较大,采用优化控制规律使发动机效率有所降低,但无级变速器效率升高更大,系统整体效率升高;在功率需求一定的循环工况下,优化控制算法比传统上仅以发动机效率最高为目标的控制算法节油1%~2%。     

基于LSTM网络的驾驶意图识别及车辆轨迹预测

自动驾驶汽车需具备预测周围车辆轨迹的能力,以便做出合理的决策规划,提高行驶安全性和乘坐舒适性。运用深度学习方法,设计了一种基于长短时记忆（LSTM）网络的驾驶意图识别及车辆轨迹预测模型,该模型由意图识别模块和轨迹输出模块组成。意图识别模块负责识别驾驶意图,其利用Softmax函数计算出驾驶意图分别为向左换道、直线行驶、向右换道的概率;轨迹输出模块由编码器-解码器结构和混合密度网络（MDN）层组成,其中的编码器将历史轨迹信息编码为上下文向量,解码器结合上下文向量和已识别的驾驶意图信息预测未来轨迹;引入MDN层的目的是利用概率分布来表示车辆未来位置,而非仅仅预测一条确定的轨迹,以提高预测结果的可靠性和模型的鲁棒性。此外,将被预测车辆及其周围车辆组成的整体视为研究对象,使模型能够理解车-车间的交互式行为,响应交通环境的变化,动态地预测车辆位置。使用基于真实路况信息的NGSIM（Next Generation SIMulation）数据集对模型进行训练、验证与测试。研究结果表明：与传统的基于模型的方法相比,基于LSTM网络的轨迹预测方法在预测长时域轨迹上具有明显的优势,考虑交互式信息的意图识别模块具备更高的预判性和准确率,且基于意图识别的轨迹预测能降低预测轨迹与真实轨迹间的均方根误差,显著提高轨迹预测精度。     

The Alternative Motor Fuels Act, alternative-fuel vehicles, and greenhouse gas emissions

The corporate average fuel economy (CAFE) standard is the major policy tool to improve the fleet average miles per gallon of automobile manufacturers in the US. The Alternative Motor Fuels Act (AMFA) provides special treatment in calculating the fuel economy of alternative-fuel vehicles to give manufacturers CAFE incentives to produce more alternative-fuel vehicles. AMFA has as its goals an increase in the production of alternative-fuel vehicles and a decrease in gasoline consumption and greenhouse gas emissions. This paper examines theoretically the effects of the program set up under AMFA. It finds that, under some conditions, this program may actually increase the production of fuel-inefficient gasoline vehicles, gasoline consumption and greenhouse gas emissions.     

管道内防腐层补口技术研究进展

管道内衬或内防腐涂层现场施焊时,焊缝两侧的防腐层会由于高温作用而破坏,使环焊缝处不能得到有效的保护,内补口技术也成为影响管道质量的主要瓶颈。文中介绍了国内外主要的内补口技术,如内补口机法、内衬保护套（管）焊接法、不锈钢接头法、机械连接法等,并指出各方法的特点。文中还就内补口技术的质量控制和研究方向等提出了建议。     

考虑螺旋桨体积力的水下机器人水动力特性仿真

为在初步设计时预测ROV的水动力性能,使用CFD技术进行分析,以ROV模型为例,最大程度地保留ROV内部的构件,使模型更加接近真实状况。分别计算ROV在不同工况下的阻力、不同漂角下的横向力和转艏力矩以及添加体积力模型之后的螺旋桨流场状况,很好地模拟出ROV周围的流场,并与已有的试验数据进行对比。结果验证了CFD水动力仿真的可行性和准确性,并还可预测ROV在螺旋桨作用下的进速等,对ROV设计具有实际的参考价值和指导意义。     

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.     

Electric vehicles for greenhouse gas reduction in China: A cost-effectiveness analysis

There have been ongoing debates over whether battery electric vehicles contribute to reducing greenhouse gas emissions in China’s context, and if yes, whether the greenhouse gas emissions reduction compensates the cost increment. This study informs such debate by examining the life-cycle cost and greenhouse gas emissions of conventional vehicles, hybrid electric vehicles and battery electric vehicles, and comparing their cost-effectiveness for reducing greenhouse gas emissions. The results indicate that under a wide range of vehicle and driving configurations (range capacity, vehicle use intensity, etc.), battery electric vehicles contribute to reducing greenhouse gas emissions compared with conventional vehicles, although their current cost-effectiveness is not comparable with hybrid electric vehicles. Driven by grid mix optimization, power generation efficiency improvement, and battery cost reduction, the cost-effectiveness of battery electric vehicles is expected to improve significantly over the coming decade and surpass hybrid electric vehicles. However, considerable uncertainty exists due to the potential impacts from factors such as gasoline price. Based on the analysis, it is recommended that the deployment of battery electric vehicles should be prioritized in intensively-used fleets such as taxis to realize high cost-effectiveness. Technology improvements both in terms of power generation and vehicle electrification are essential in improving the cost-effectiveness of battery electric vehicles.