基于传统动力源的重型商用车减碳技术

在全球能源危机和温室效应加剧的大环境下,中国向世界承诺减碳目标：2030年前力争实现碳达峰,2060年前力争实现碳中和。作为节能减排的重点,重型商用车的减碳成效是“双碳”征程中的关键。重点介绍基于传统动力源的重型商用车减碳技术,包括内燃机燃烧、低摩擦、智能变速、轻量化、混合动力等技术在内的动力总成领域,以及包括天然气、含氧燃料、氢氨燃料在内的先进燃料领域。通过不同领域的技术发展以及优势互补,更加高效、低碳、清洁的内燃机仍将在重型商用车领域持续发挥重要作用。     

基于高精地图的物流配送车路径规划与跟踪控制

为了解决园区等场景下无人车多途经点配送问题,提出了一种基于矢量化高精地图的车道级全局路径规划、生成和跟踪控制方法。考虑配送车往返途经点顺序对行驶路径总长度的影响,基于高精地图采用A*算法计算各配送点间的最优路径,在此基础上,利用动态规划算法求解经过多个配送点的全局最优路径。应用贝塞尔曲线对规划的路径进行平滑,并根据道路曲率设定不同路径处的参考行驶速度,进而生成车道级的可用于跟踪的目标轨迹。利用车辆二自由度模型设计模型预测控制器进行轨迹跟踪,实现低速物流配送车的自主控制。在 CarSim/Prescan/Simulink联合仿真平台和实车平台上对提出的规划控制方法进行了试验。结果表明,相比传统的依据最近配送点策略确定的路径,所提出的方法搜索出的路径长度平均缩短了 6.15%。所设计的轨迹跟踪控制器能确保配送试验车与目标轨迹的横向偏差在 0.25 m 以内,航向角偏差在5°以内。     

北京某地铁站台空气颗粒物的数量浓度和质量浓度以及粒径分布和元素组成

为了解地铁站台空气颗粒物的污染状况,对北京某地铁站台空气颗粒物的数量浓度和质量浓度,以及粒径分布情况进行了1 d的实地监测,同时采集了站台内外的总悬浮颗粒物样品,研究了颗粒物元素组成特征。结果表明,监测粒径为0.0060~9.8900μm范围内,地铁站台空气中颗粒物总数量浓度与粒径为0.0060~0.0170μm的颗粒息息相关,总质量浓度主要取决于粒径为0.6120~6.6700μm的颗粒;早晚乘车高峰时段内站台空气中颗粒物的数量浓度和质量浓度都显著增大,晚高峰时段颗粒物质量浓度高于早高峰时段;监测期间,PM 2.39(粒径为0.0060~2.3900μm颗粒)和PM 9.89(粒径为0.0060~9.8900μm颗粒)平均质量浓度超过了环境空气中PM 2.5和PM 10的标准限值。站台空气颗粒物中Fe含量最高,Fe、Cu、Mn、Cr、Mo的含量显著高于站外。     

含气率对多相混输泵内气液两相分布规律的影响

为了探究含气率对多相混输泵内气液两相分布规律的影响，本文基于标准的k-ε湍流模型和时均N-S方程，对不同含气率下混输泵内的流态进行数值计算，分析了混输泵内不同位置处的气液两相分布规律。结果表明：不同压缩级动叶轮进口截面到出口截面的气相体积分数从轮毂至轮缘逐渐变小，同时叶轮靠近轮毂处、轮毂至轮缘中间位置处以及轮缘处的最大气体体积分数位置将随着含气率的增加而增加。另外在离心力的作用下混输泵动叶轮内越靠近轮缘液相越集中，越靠近轮毂气相越集中。此研究结果为提高多相混输泵的混输性能和运行效率提供了参考。     

Optimization of Wiedemann and Fritzsche car-following models for emission estimation

Recent studies have provided that the vehicle trajectories generated by car-following models may not represent the real driving characteristics, thus leading to significant emission estimation errors. In this paper, two of the most widely used car-following models, Wiedemann and Fritzsche models, were selected and analyzed based on the massive field car-following trajectories in Beijing. A numerical simulation method was designed to generate the following car’s trajectories by using the field trajectories as the input. By comparing the simulated and the filed data, the representativeness of the simulated regime fractions and VSP distributions were evaluated. Then, the mechanism of car-following models was investigated from the aspects of regime determination and the acceleration rule in each regime. Further, the regime threshold parameters and acceleration model were optimized for emission estimations. This study found that the “Following” regime threshold of SDX and the maximum acceleration in “Free Driving” regime are critical parameters for Wiedemann model. The differences between the Wiedemann simulated VSP distribution and the field one can be reduced separately by applying the optimized SDX and maximum acceleration model individually. However, a much sharper reduction was observed by optimizing both parameters simultaneously, and the emission estimation errors were further reduced, which were less than 4% in the case studies. Fritzsche model generated more realistic VSP distributions and emissions, while the maximum accelerations could be further optimized for high speed conditions.     

Carbon dioxide emissions from port container distribution: Spatial characteristics and driving factors

Port carbon dioxide (CO₂) emissions in China have become an ever-increasing public concern due to their significant impacts on human health and the environment. However, existing studies focus mainly on CO₂ emissions from vessels calling at the ports and cargo handling within the ports, paying little attention to the inland distribution networks. To fill this gap, this paper proposes an easily implemented method for calculating CO₂ emissions from port container distribution (PCD) and investigates their spatial characteristics and driving factors. By analyzing 30 container ports in China, the main findings are as follows. First, road transportation is the major contributor of CO₂ emissions from PCD due to the lack of rail and inland water transportation. Second, PCD carbon emissions exhibit significant local spatial clustering. That is, ports with similar geographical locations tend to present a similar pattern of PCD carbon emissions. Third, as suggested by the spatial Durbin model, PCD carbon emissions are negatively determined by local gross domestic product, number of port berths, but are positively determined by local tertiary industry value and highway freight volume, and waterway freight volume in both local and neighboring ports. These results provide empirical insights into cross-port collaboration in reducing PCD carbon emissions.     

Adapting the shipping sector to stricter emissions regulations: Fuel switching or installing a scrubber?

This paper examines how the existing fleet in the shipping industry can be adapted to the new emission regulations through the two main techniques that currently exist: (a) the use of low-sulphur marine diesels; and (b) the installation of scrubbers. A method is presented here for drawing up an economic assessment of both these techniques under uncertainty. It enables the best option to be selected at any given time taking into account fuel prices (spot and futures), scrubber installation costs, the time that the vessel operates in an Emission Control Area (ECA) and the remaining useful lifetime of the vessel. The paper also considers the possibility of an unexpected change from a non-ECA navigation area to an ECA. The assessment is carried out in a manner consistent with marine diesel and crude oil spot and futures market quotes. Our results show the net present value of investing in the installation of scrubbers and investing in changing fuel types for different assumptions on how vessels are operated. We also analyse increases in fuel consumption and CO₂ emissions as a consequence of using scrubbers and how they affects the financial analysis if such incremental emissions must be paid under a CO₂ pricing mechanism.     

Urban road traffic noise spatiotemporal distribution mapping using multisource data

Many residents are disturbed by road traffic noise which needs to be controlled and managed. The noise map is a helpful and important tool for noise management and acoustical planning in urban areas. However, the static noise map is not sufficient for evaluating noise annoyance at different temporal periods. It is necessary to develop the dynamic noise map or the noise spatiotemporal distribution. In this study, a method about urban road traffic noise spatiotemporal distribution mapping is proposed to obtain the representative road traffic noise maps of different periods. This method relies on the proposed noise spatiotemporal distribution model with two time-dependent variables - traffic density and traffic speed, and the spatiotemporal characteristics derived from multisource data. There are three steps in the method. First, the urban road traffic noise spatiotemporal distribution model is derived from the law of sound propagation. Then, the temporal characteristics are extracted from traffic flow detecting data and E-map road segment speed data by the outlier detection analysis. Finally, the noise distributions corresponding to different periods are calculated by an efficient algorithm which can save 90% above of the computing time. Moreover, a validation experiment was conducted to evaluate the accuracy of the proposed method. There is only 2.26-dB[A] mean absolute error that is within an acceptable range, which shows that the method is effective.     

AERMOD for near-road pollutant dispersion: Evaluation of model performance with different emission source representations and low wind options

The performance of the regulatory dispersion model AERMOD in simulating vehicle-emitted pollutant concentrations near-roadway using area or volume source representation of emissions and with different low wind options was assessed using the SF₆ tracer data from the General Motors (GM) Sulfur Dispersion Experiment. At downwind receptor locations, AERMOD, using either area or volume source emissions, can reasonably predict the tracer concentrations near the surface (0.5 m) but the model performance decreases at higher elevations (3.5m and 9.5m above the surface). For upwind receptors, using an area source representation leads to significant under-predictions due to AERMOD’s lack of treatment of lateral plume meander, but using volume source representation leads to over-predictions of upwind concentrations regardless of the low wind options for plume meander. Among the three low wind options currently available in AERMOD, best model performance is obtained with low wind option 3, which treats plume meander with a higher minimal standard deviation of the horizontal crosswind component (σ_v,min = 0.3 m s⁻¹), eliminates upwind component of dispersion and uses an effective lateral dispersion parameter (σ_y) to replicate centerline concentration. The optional adjustment of the surface friction velocity in the meteorological preprocessor AERMET does not lead to obvious improvements in predicted near-road concentrations for this application.     

Development a new power management strategy for power split hybrid electric vehicles

Reduction of greenhouse gas emission and fuel consumption as one of the main goals of automotive industry leading to the development hybrid vehicles. The objective of this paper is to investigate the energy management system and control strategies effect on fuel consumption, air pollution and performance of hybrid vehicles in various driving cycles. In order to simulate the hybrid vehicle, the combined feedback–feedforward architecture of the power-split hybrid electric vehicle based on Toyota Prius configuration is modeled, together with necessary dynamic features of subsystem or components in ADVISOR. Multi input fuzzy logic controller developed for energy management controller to improve the fuel economy of a power-split hybrid electric vehicle with contrast to conventional Toyota Prius Hybrid rule-based controller. Then, effects of battery’s initial state of charge, driving cycles and road grade investigated on hybrid vehicle performance to evaluate fuel consumption and pollution emissions. The simulation results represent the effectiveness and applicability of the proposed control strategy. Also, results indicate that proposed controller is reduced fuel consumption in real and modal driving cycles about 21% and 6% respectively.