生物柴油应用试验研究

利用B100(纯生物柴油)、B50(50%体积生物柴油和柴油混合)、B20(20%体积生物柴油和柴油混合)等燃料分别对2辆配置了增压中冷车用直喷式柴油机的大客车进行了发动机排放特性试验和整车道路试验。试验结果表明,B100、B50和B20燃料均可以有效降低HC、CO、PM和烟度排放,但动力性下降、油耗率上升、NOx排放有明显增加;燃用B20燃料可以保证在降低排放的同时动力性、耗油率变化不大,因此该种掺烧方式比较适宜。     

混合燃料的含氧量对改善柴油机排放的试验研究

在一台S1100A2型单缸柴油机上,通过在柴油中添加乙醇、甲缩醛(DMM)、碳酸二甲脂(DMC)等3种含氧添加剂,研究了在常用工况下混合燃料的含氧量对柴油机排放特性的影响。试验结果表明,含氧混合燃料可以有效改善柴油机的烟度和CO排放,在大负荷下尤为明显,而对NOx和HC的排放影响较小。     

生命周期评价及其在汽车排放领域的应用

介绍了生命周期评价(LCA)的定义、评估对象、范围、评价思路、步骤及其体系框架,说明了汽车排放分析中存在的两种循环(燃料循环和车辆循环)。通过分析汽车生命周期排放模型及其在CATCH(Clean A ccessible Transport for Community Health)研究中的一个实际应用案例,进一步阐明了生命周期评价在对各种燃料进行排放分析过程中的实际应用价值,最后介绍了生命周期评价在国外汽车企业中的研究发展情况、实际产品以及应用前景。     

加严的排放标准需要更高品质的燃油

阐述了保护环境、降低排放和发展清洁汽车是我国汽车工业可持续发展的基本战略。分析了车用燃油品质对车辆排放的影响,指出先进的排放技术需要更高品质的燃油为前提。加速研制和生产更高品质的燃油对于我国实施国Ⅲ排放标准是当务之急。     

汽油车车载诊断系统(OBD)基本原理及其应用

对OBD法规和试验项目做适当介绍,并分析发动机失火、氧传感器失效模拟、催化器劣化监督模式,最后给出了在一辆低排放汽车上进行的实际OBD演示试验排放结果,指出OBD是控制在用车排放的有效手段。     

利用广安博之模型对柴油机高原运行性能和排放特性的模拟研究

为研究柴油机高原运行的动力性、经济性和排放特性,使用广安博之燃烧模型对一台增压中冷的重型柴油机进行了模拟分析。模拟计算的结果显示,随着海拔高度的增加,柴油机的动力性下降,油耗上升,排放物中的氮氧化物有所减少,而碳烟排放增加。     

Thermodynamic,environmental and economic effects of diesel and biodiesel fuels on exhaust emissions and nano-particles of a diesel engine

In this study, diesel (JIS#2) and various biodiesel fuels (BDF20, BDF50, BDF100) are used to operate the diesel engine at 100 Nm, 200 Nm and full load; while the engine speed is 1800 rpm. The system is experimentally studied, and the energy, exergy, sustainability, thermoeconomic and exergoeconomic analyses are performed to the system. The Engine Exhaust Particle Sizer is used to measure the size distribution of engine exhaust particle emissions. Also, the data of the exhaust emissions, soot, particle numbers, fuel consumptions, etc. are measured. It is found that (i) most of the exhaust emissions (except NO_x) are directly proportional to the engine load, (ii) maximum CO₂ and NO_x emissions rates are generally determined for the BDF100 biodiesel fuel; while the minimum ones are calculated for the JIS#2 diesel fuel. On the other hand, the maximum CO and HC emissions rates are generally computed for the JIS#2 diesel fuel; while the minimum ones are found for the BDF100 biodiesel fuel, (iii) fuel consumptions from maximum to minimum are BDF100 > BDF50 > BDF20 > JIS#2 at all of the engine loads, (iv) particle concentration of the JIS#2 diesel fuel is higher than the biodiesel fuels, (v) soot concentrations of the JIS#2, BDF20 and BDF50 fuels are directly proportional to the engine load; while the BDF100 is inversely proportional, (vi) system has better energy and exergy efficiency when the engine is operated with the biodiesel fuels (vii) sustainability of the fuels are BDF100 > BDF50 > BDF20 > JIS#2, (viii) thermoeconomic and exergoeconomic parameters rates from maximum to minimum are JIS#2 > BDF20 > BDF50 > BDF100.     

Modeling the impacts of alternative emission trading schemes on international shipping

Various market-based measures have been proposed to reduce CO₂ emissions from international shipping. One promising mechanism under consideration is the Emission Trading Scheme (ETS). This study analyzes and benchmarks the economic implications of two alternative ETS mechanisms, namely, an open ETS compared to a Maritime only ETS (METS). The analytical solutions and model calibration results allow us to quantify the impacts of alternative ETS schemes on the container shipping sector and the dry bulk shipping sector. It is found that an ETS, whether open or maritime only, will decrease shipping speed, carrier outputs and fuel consumption for both the container and dry bulk sectors, even in the presence of a “wind-fall” profit to shipping companies. Under an open ETS, the dry bulk sector will suffer from a higher proportional reduction in output than the container sector, and will thus sell more emission permits or purchase fewer permits. Under an METS, container carriers will buy emission permits from the dry bulk side. In addition, under an METS the degree of competition within one sector will have spill-over effects on the other sector. Specifically, when the sector that sells (buys) permits is more collusive (competitive), the equilibrium permit price will rise. This study provides a framework for identifying the moderating effects of market structure and competition between firms on emission reduction schemes, and emphasizes the importance of understanding the differential impacts of ETS schemes on individual sectors within an industry when considering alternative policies.     

Development of simulated driving cycles for light,medium, and heavy duty trucks: Case of the Toronto Waterfront Area

Driving cycles are an important input for state-of-the-art vehicle emission models. Development of a driving cycle requires second-by-second vehicle speed for a representative set of vehicles. Current standard driving cycles cannot reflect or forecast changes in traffic conditions. This paper introduces a method to develop representative driving cycles using simulated data from a calibrated microscopic traffic simulation model of the Toronto Waterfront Area. The simulation model is calibrated to reflect road counts, link speeds, and accelerations using a multi-objective genetic algorithm. The simulation is validated by comparing simulated vs. observed passenger freeway cycles. The simulation method is applied to develop AM peak hour driving cycles for light, medium and heavy duty trucks. The demonstration reveals differences in speed, acceleration, and driver aggressiveness between driving cycles for different vehicle types. These driving cycles are compared against a range of available driving cycles, showing different traffic conditions and driving behaviors, and suggesting a need for city-specific driving cycles. Emissions from the simulated driving cycles are also compared with EPA’s Heavy Duty Urban Dynamometer Driving Schedule showing higher emission factors for the Toronto Waterfront cycles.     

Second-order models and traffic data from mobile sensors

Mobile sensing enabled by GPS or smart phones has become an increasingly important source of traffic data. For sufficient coverage of the traffic stream, it is important to maintain a reasonable penetration rate of probe vehicles. From the standpoint of capturing higher-order traffic quantities such as acceleration/deceleration, emission and fuel consumption rates, it is desirable to examine the impact on the estimation accuracy of sampling frequency on vehicle position. Of the two issues raised above, the latter is rarely studied in the literature. This paper addresses the impact of both sampling frequency and penetration rate on mobile sensing of highway traffic. To capture inhomogeneous driving conditions and deviation of traffic from the equilibrium state, we employ the second-order phase transition model (PTM). Several data fusion schemes that incorporate vehicle trajectory data into the PTM are proposed. And, a case study of the NGSIM dataset is presented which shows the estimation results of various Eulerian and Lagrangian traffic quantities. The findings show that while first-order traffic quantities can be accurately estimated even with a low sampling frequency, higher-order traffic quantities, such as acceleration, deviation, and emission rate, tend to be misinterpreted due to insufficiently sampled vehicle locations. We also show that a correction factor approach has the potential to reduce the sensing error arising from low sampling frequency and penetration rate, making the estimation of higher-order quantities more robust against insufficient data coverage of the highway traffic.