车用柴油机NO_x形成及控制

相对汽油发动机污染物排放,柴油发动机CO和CH的排放较低,不到汽油机的10%,但NOX排放水平却高于汽油发动机。本文重点讨论柴油发动机排气污染物中NOx的成分及危害,分析了NO的生成机理及影响因素,提出了控制柴油机NO排放的技术和方法。     

Exhaust emissions generated under actual operating conditions from a hybrid vehicle and an electric one fitted with a range extender

The paper describes exhaust emission tests performed on a PHEV (Plug-in Hybrid Electric Vehicle) and a BEV (Battery Electric Vehicle), in which the combustion engine was used as a range extender. The measurements of the exhaust emissions were performed for CO₂/fuel consumption, CO, THC and NO_x. The RDE measurements were performed including the engine operating parameters and emissions analysis. This analysis shows that the engines of BEVs and PHEVs operate in a different parameter range when under actual operating conditions, which directly translates into the exhaust emission values. This is particularly the case for the emission of NO_x. The investigations were carried out for two routes differentiated by the length and share of the urban and extra-urban cycles. For both routes, the emission of THC and CO were lower for the PHEV engine – HC by 69% (22 mg/km, route 1) and 6% (15 mg/km, route 2), CO by 69% (0.12 mg/km, route 1) and 80% (0.1 mg/km, route 2). For route 1, characterized by a greater share of the urban cycle, the emission of NO_x was lower by 70% (2 mg/km) for the BEV engine, and (route 2) lower by 60% (8 mg/km) for the PHEV engine. Additionally, the curves of the exhaust emissions in time for individual exhaust components have been presented that indicate that in the motorway cycle the emission of THC and CO from the BEV vehicle increases significantly up to ten times compared to urban cycle.     

Correlation between automotive CO, HC, NO, and PM emission factors from on-road remote sensing: implications for inspection and maintenance programs

Carbon monoxide (CO), hydrocarbon (HC), and nitrogen oxide (NO) emission factors (EFs) are measured with a commercial vehicle emissions remote sensing system (VERSS) during a large-scale vehicle exhaust emissions study in Las Vegas. Particulate matter (PM) EFs are simultaneously measured for individual vehicles with a newly developed PM-VERSS based on ultraviolet backscatter light detection and ranging (Lidar). The effectiveness of CO and HC EFs as proxy for NO and PM EFs for spark-ignition vehicles is evaluated. Poor correlations were found between EFs for pollutants on an individual vehicle basis indicating that high EFs for one or more pollutants cannot be used as a predictor of high EFs for other pollutants. Stronger functional relationships became evident after averaging the EF data in bins based on rank-order of a single pollutant EF. Low overlap between the highest 10% emitters for CO, HC, NO, and PM was found. These results imply that for an effective reduction of the four pollutants, inspection and maintenance (I/M) programs, including clean screening, should measure all four pollutants individually. Fleet average CO and HC concentrations determined by gaseous VERSS were compared with fleet average CO and HC concentrations measured at low-idle and at high-idle during local I/M tests for spark-ignition vehicles. The fleet average CO concentrations measured by I/M tests at either idle were about half of those measured by remote sensing. The fleet average high-idle HC concentration measured by I/M tests was about half of that measured by VERSS while low-idle I/M and VERSS HC average concentrations were in better agreement. For a typical vehicle trip, most of the fuel is burned during non-idle conditions. I/M measurements collected during idling conditions may not be a good indicator of a vehicle’s potential to be a high emitter. VERSS measurements, when the vehicle is under a load, should more effectively identify high emitting vehicles that have a large contribution to the mobile emissions inventory.     

Performance and emission characteristics of a spark ignition engine fuelled with butanol isomer-gasoline blends

The heavy reliance on petroleum-derived fuels such as gasoline in the transportation sector is one of the major causes of environmental pollution. For this reason, there is a critical need to develop cleaner alternative fuels. Butanol is an alcohol with four different isomers that can be blended with gasoline to produce cleaner alternative fuels because of their favourable physicochemical properties compared to ethanol. This study examined the effect of butanol isomer-gasoline blends on the performance and emission characteristics of a spark ignition engine. The butanol isomers; n-butanol, sec-butanol, tert-butanol and isobutanol are mixed with pure gasoline at a volume fraction of 20 vol%, and the physicochemical properties of these blends are measured. Tests are conducted on a SI engine at full throttle condition within an engine speed range of 1000–5000 rpm. The results show that there is a significant increase in the engine torque, brake power, brake specific fuel consumption and CO₂ emissions with respect to those for pure gasoline. The butanol isomers-gasoline blends give slightly higher brake thermal efficiency and exhaust gas temperature than pure gasoline at higher engine speeds. The iBu20 blend (20 vol% of isobutanol in gasoline) gives the highest engine torque, brake power and brake thermal efficiency among all of the blends tested in this study. The isobutanol and n-butanol blend results in the lowest CO and HC emissions, respectively. In addition, all of the butanol isomer-gasoline blends yield lower NO emissions except for the isobutanol-gasoline blend.     

Real-world gaseous emission characteristics of Euro 6b light-duty gasoline- and diesel-fueled vehicles

To accurately investigate vehicle emissions that have become major contributors to global air pollutants and greenhouse gases, test conditions have been transferred from laboratory type approval test cycles to real-world driving conditions. In this study, the real-world driving emissions of carbon monoxide (CO), total hydrocarbons (THC), nitrogen oxides (NO_x), and carbon dioxide (CO₂) from one gasoline and two diesel Euro 6b light-duty passenger vehicles were investigated by a portable emission measurement system (PEMS) in Lyon, France. NO_x and CO₂ emission controls remain critical to addressing the real-world driving emissions of Euro 6b vehicles. Notably, the tested gasoline vehicle emitted higher CO₂ emissions than diesel vehicles on all types of roads, especially on the urban road with an excess of 29.3–48.3%. The highest emission factors of gaseous pollutants generally occurred on the motorway for the gasoline vehicle, while on the urban road for diesel vehicles. In particular, for high-speed driving conditions, the gasoline vehicle gaseous emissions, especially NO_x emissions, were more affected by acceleration than diesel vehicle emissions. In addition, the CO emissions, especially THC emissions, for the gasoline vehicle, were more influenced by warm-start, especially cold-start, than those for diesel vehicles.     

Influence of driving patterns on vehicle emissions: A case study for Latin American cities

On-board real-time emission experiments were conducted on 78 light-duty vehicles in Bogota. Direct emissions of carbon monoxide (CO), carbon dioxide (CO₂), nitrogen oxides (NO_x) and hydrocarbons (HC) were measured. The relationship between such emissions and vehicle specific power (VSP) was established. The experimental matrix included both gasoline-powered and retrofit dual fuel (gasoline–natural gas) vehicles. The results confirm that VSP is an appropriate metric to obtain correlations between driving patterns and air pollutant emissions. Ninety-five percent of the time vehicles in Bogota operate in a VSP between −15.2 and 17.7 kW ton⁻¹, and 50% of the time they operate between −2.9 and 1.2 kW ton⁻¹, representing low engine-load and near-idling conditions, respectively. When engines are subjected to higher loads, pollutant emissions increase significantly. This demonstrates the relevance of reviewing smog check programs and command-and-control measures in Latin America, which are widely based on static (i.e., idling) emissions testing. The effect of different driving patterns on the city’s emissions inventory was determined using VSP and numerical simulations. For example, improving vehicle flow and reducing sudden and frequent accelerations could curb annual emissions in Bogota by up to 12% for CO₂, 13% for CO and HC, and 24% for NO_x. This also represents possible fuel consumption savings of between 35 and 85 million gallons per year and total potential economic benefits of up to 1400 million dollars per year.     

Investigation of tailpipe and evaporative emissions from China IV and Tier 2 passenger vehicles with different gasolines

The limited understanding of vehicular emissions in China, especially evaporative emissions, is one obstacle to establishing tighter standards. To evaluate tailpipe and evaporative emissions, two typical China IV vehicles and one Tier 2 vehicle with an onboard refuelling vapour recovery (ORVR) system were selected and tested. One of the China IV vehicles was fuelled with gasoline, E10 and M15, respectively, to investigate the effect of fuel properties on vehicular emissions. For each vehicle, cold-start tailpipe emission tests were conducted first, followed by an evaporation test. Based on the emission factors and real-world vehicle activity data, the annual tailpipe and evaporative hydrocarbon (HC) emissions of each vehicle were calculated and compared. The results show that E10 and M15 significantly reduced the tailpipe CO and particle number (PN) emissions but seriously aggravated the NOx emissions, especially for M15. The hot soak losses (HSLs) and diurnal breathing losses (DBLs) were slightly impacted by the fuel properties. The annual evaporative emissions with E10 and M15 were higher than that with gasoline. The ORVR system effectively controlled the evaporative emissions, especially for DBLs. Evaporative emissions from the China IV vehicles were 1.1–1.4 times the tailpipe HC emissions. Additionally, the evaporative emission factors of the China IV vehicles were almost 50% lower than the standard (2.0 g/test), whereas their annual evaporative emissions were almost 1.8–2.8 times higher than those from the Tier 2 vehicle. Therefore, controlling evaporative emissions currently remains a great need in China, and the ORVR might be a recommended evaporative control technology.     

An assessment of gasoline motorcycle emissions performance and understanding their contribution to Tehran air pollution

Motorcycles are the third most common means of transportation in the megacity of Tehran. Hence, measurements of emission factors are essential for Tehran motorcycle fleets. In this study, 60 carburetor motorcycles of various mileages and engine displacement volumes were tested in a chassis dynamometer laboratory according to cold start Euro-3 emissions certification test procedures. For almost all of the tested samples, the average carbon monoxide (CO) emission factors were about seven times higher than the limits for Euro-3 certification. No motorcycle fell within the Euro-3 certification limit on CO emissions. 125 cc engine displacement volume motorcycles, which are dominant in Tehran, have the most total unburned hydrocarbons and CO emission rates, and they have less nitrous oxides (NO_X) emission rates and fuel consumption compared to those of larger engine volume motorcycles. Calculation of fuel-based emission factors and moles of combustion products shows that about 40% of fuel consumed by 125 cc engine volume motorcycles burns to incomplete combustion products. This proportion is lower for larger engine volume motorcycles. Approximation of relative air–fuel ratio results shows very rich combustion in selected motorcycles. Using a carburetor fuel supply system, low engine compression ratio, aging, and no catalyst could be reasons for high emission rates. These reasons could possibly result in high ultrafine particles emission rates from motorcycles. Comparison of total motorcycle pollutant emissions to that of passenger cars from previous studies in Tehran shows that motorcycles contribute to pollutant much higher than their contribution to the total fleet or total travels.     

基于李群理论的汽油发动机尾气分析模型匹配算法研究

为了准确对发动机尾气排放状态和规律进行分析,本文提出了一种基于李群理论的汽油发动机尾气分析模型。该模型针对尾气排放量的非线性变化特征,利用李代数和李群之间的指数映射关系建立李群仿射模型,然后在流行拓扑空间上对尾气中主要污染物的含量进行建模。通过模型匹配算法实现对尾气排放状态的正常与否进行分析。该方法利用数据的流行拓扑信息,有效提高了非线性建模和匹配的准确性和效率。在福特蒙迪欧牌轿车上的实验结果表明,该模型能够以较高精度对汽油机尾气排放状况进行建模和状态匹配。     

Analysis of fuel consumption and pollutant emissions of regulated and alternative driving cycles based on real-world measurements

Discrepancies between real-world use of vehicles and certification cycles are a known issue. This paper presents an analysis of vehicle fuel consumption and pollutant emissions of the European certification cycle (NEDC) and the proposed worldwide harmonized light vehicles test procedure (WLTP) Class 3 cycle using data collected on-road. Sixteen light duty vehicles equipped with different propulsion technologies (spark-ignition engine, compression-ignition engine, parallel hybrid and full hybrid) were monitored using a portable emission measurement system under real-world driving conditions. The on-road data obtained, combined with the Vehicle Specific Power (VSP) methodology, was used to recreate the dynamic conditions of the NEDC and WLTP Class 3 cycle. Individual vehicle certification values of fuel consumption, CO₂, HC and NO_x emissions were compared with test cycle estimates based on road measurements. The fuel consumption calculated from on-road data is, on average, 23.9% and 16.3% higher than certification values for the recreated NEDC and WLTP Class 3 cycle, respectively. Estimated HC emissions are lower in gasoline and hybrid vehicles than certification values. Diesel vehicles present higher estimated NO_x emissions compared to current certification values (322% and 326% higher for NO_x and 244% and 247% higher for HC + NO_x for NEDC and WLTP Class 3 cycle, respectively).     

The impact of marine engine operation and maintenance on emissions

This paper examines the role of marine engine maintenance in reducing pollution. It tests four marine diesel engines, one constructed prior to January 1, 2000 and three after 2000. This paper explains how the condition of an engine’s nozzles and faulty injection pressure significantly influence NO_x and CO emissions and describes both bench and onboard ship tests, on engines fitted with new or worn nozzles at different injection pressures. The tests showed that, when the engine constructed prior to 2000 operates under normal in-service conditions, the emissions are within limits, but, with a small fault in injection timing, the NO_x emissions exceed the limits. For the engines constructed after 2000, a fault in the maintenance of the nozzles increases the CO emissions to a high level.     

Relationships between characteristics of motorcycles and hydrocarbon emissions in Taiwan: A note

Taiwan’s inspection and maintenance (I/M) programs identifies high-emission motorcycles but, although these help reduce air pollution, they have been criticized for being cost-ineffective. This study examines the relationship between characteristics of motorcycles and hydrocarbon emissions in the Central Air Quality Basin of Taiwan. It is shown that engine size and type, age and manufacturer of a motorcycle significantly affect HC emissions. Larger-size engines emit smaller amounts of HCs; whereas older motorcycles emitted greater amounts. In addition, two-stroke-engine machines produced significantly higher HC emission levels than four-strokes. Variations in HC emissions testing are a result of various I/M testing locations and efficiency may be improved by modifying these.     

Analysis of real driving gaseous emissions from light-duty diesel vehicles

Increasingly strict emissions standards are providing a major impetus to vehicle manufactures for developing advanced powertrain and after-treatment systems that can significantly reduce real driving emissions. The knowledge of the gaseous emissions from diesel engines under steady-state operation and under transient operation provides substantial information to analyze real driving emissions of diesel vehicles. While there are noteworthy advances in the assessment of road vehicle emissions from real driving and laboratory measurements, detailed information on real driving gaseous emissions are required in order to predict effectively the real-time gaseous emissions from a diesel vehicle under realistic driving conditions. In this work, experiments were performed to characterize the behavior of NOx, unburned HC, CO, and CO₂ emitted from light-duty diesel vehicles that comply with Euro 6 emissions standards. The driving route fully reflected various real-world driving conditions such as urban, rural, and highway. The real-time emission measurements were conducted with a Portable Emissions Measurement System (PEMS) including a Global Positioning System (GPS). To investigate the gaseous emission characteristics, authors determined the road load coefficients of vehicle specific power (VSP) and regression coefficient between fuel use rate and VSP. Furthermore, this work revealed the correlation between the rates of average fuel use and each gaseous emission.     

Energy use and emissions of two stroke-powered tricycles in Metro Manila

CO, CO₂, NO_x and HC emissions of two stroke-powered tricycles in Metro Manila are examined using an instantaneous emissions model. Results show that fuel consumption and HC emissions in middle class residential areas and main roads are similar but lower than levels in low income residential areas. On the average, tricycles in Metro Manila consume 24.41 km/l of fuel and produces 9.5, 9.7, 40.5 and 0.07 g/km of HC, CO, CO₂ and NO_x, respectively. They fail to satisfy HC, CO and NO_x emission limits set by reference standards in the Philippines and other Asian countries. They produce greater HC and CO emissions than gasoline fueled private cars and diesel powered public jeepneys, taxis and buses on a per passenger-km basis but significantly lower NO_x emissions. Tricycles account for 15.4% of the total HC emissions from mobile sources in the metropolis while their contributions to CO, CO₂ and NO_x are minimal.     

Congestion and emissions mitigation: A comparison of capacity,demand, and vehicle based strategies

Capacity, demand, and vehicle based emissions reduction strategies are compared for several pollutants employing aggregate US congestion and vehicle fleet condition data. We find that congestion mitigation does not inevitably lead to reduced emissions; the net effect of mitigation depends on the balance of induced travel demand and increased vehicle efficiency that in turn depend on the pollutant, congestion level, and fleet composition. In the long run, capacity-based congestion improvements within certain speed intervals can reasonably be expected to increase emissions of CO₂e, CO, and NO_x through increased vehicle travel volume. Better opportunities for emissions reductions exist for HC and PM_2.5 emissions, and on more heavily congested arterials. Advanced-efficiency vehicles with emissions rates that are less sensitive to congestion than conventional vehicles generate less emissions co-benefits from congestion mitigation.     

Modal analysis of real-time,real world vehicular exhaust emissions under heterogeneous traffic conditions

This study presents the characteristics of real world, real time, on-road vehicular exhaust emission namely, carbon monoxide (CO), nitric oxide (NO), hydrocarbons (HC), and carbon dioxide (CO₂) emitted under heterogeneous traffic conditions. Field experiments were performed on major category of vehicles in developing countries, i.e. two-wheelers, auto-rickshaws, cars and buses. The on-board monitoring was carried out on different corridors with varying road geometry. Results revealed that the driving cycle was dependent on the road geometry, with two lane mixed flow corridor having lot of short term events compared to that of arterial road. Vehicular emissions during idling and cruising were generally low compared to emissions during acceleration. It was also found that emissions were significantly dependent on short term events such as rapid acceleration and braking during a trip. Also, the standard emission models like COPERT and CMEM under predicted the real world emissions by 30–200% depending upon different driving modes. The on-road emissions measurements were able to capture the emission characteristics during the micro events of real world driving scenarios which were not represented by standard vehicle emission measured at laboratory conditions.     

Thermodynamic,environmental and economic analysis of absorption air conditioning unit for emissions reduction onboard passenger ships

In this paper, the waste heat of exhaust gases and jacket cooling water in marine diesel engines are analyzed to operate the absorption refrigeration unit (ARU). Thermo-economic and environmental analysis of the absorption refrigeration cycle operated with the two heat sources that use lithium bromide as an absorbent is carried out. The analysis is performed using Engineering Equation Solver (EES) software package where the thermodynamic properties of the steam and the LiBr-water mixtures are provided. The used EES code is verified by published experimental data. As a case study, high speed passenger vessel operating in the Red Sea area has been investigated. The results show that a considerable specific economic benefit could be achieved from ARU jacket cooling water operated over that gained from main engine exhaust gases. Environmentally, applying ARU machine during cruise will reduce the annual fuel consumption for the diesel generators by 156 ton with a reduction percentage of 23%. This will reduce the exhaust gas emissions by 6.3% from the applied main engine emissions. In addition, this will result in reducing NO_x, SO_x, and CO₂ emissions with cost-effectiveness of 4.99 $/kg, 13.18 $/kg, and 0.08 $/kg, respectively.     

To save money or to save time: Intelligent routing design for plug-in hybrid electric vehicle

Electric vehicles (EVs) are promising alternative to conventional vehicles, due to their low fuel cost and low emissions. As a subset of EVs, plug-in hybrid electric vehicles (PHEVs) backup batteries with combustion engines, and thus have a longer traveling range than battery electric vehicles (BEVs). However, the energy cost of a PHEV is higher than a BEV because the gasoline price is higher than the electricity price. Hence, choosing a route with more charging opportunities may result in less fuel cost than the shortest route. Different with the traditional shortest-path and shortest-time routing methods, we propose a new routing choice with the lowest fuel cost for PHEV drivers. Existing algorithms for gasoline vehicles cannot be applied because they never considered the regenerative braking which may result in negative energy consumption on some road segments. Existing algorithms for BEVs are not competent too because PHEVs have two power sources. Thus, even if along the same route, different options of power source will lead to different energy consumption. This paper proposes a cost-optimal algorithm (COA) to deal with the challenges. The proposed algorithm is evaluated using real-world maps and data. The results show that there is a trade-off between traveling cost and time consumed when driving PHEVs. It is also observed that the average detour rate caused by COA is less than 14%. Significantly, the algorithm averagely saves more than 48% energy cost compared to the shortest-time routing.     

Statistical model for gas turbine engines exhaust emissions

A statistical analysis has been developed from the ICAO databank to predict aero-engines exhaust emissions during a landing and take-off cycle (LTO). The ICAO databank contains updated emission indices for a vast number of turbojet and turbofan engines only, with thrust ratings greater than 26.7 kN. Correlations are developed and proposed for turboprop and turboshaft engines to overcome the difficulty of assessing exhaust emissions from these engines in absence of industry data. LTO emissions are predicted for a turbofan-powered commuter airplane (Embraer E195) using the surrogate model. It is demonstrated that the predictions are closer to the values extracted from the flight data recorder than to the emissions calculated with the ICAO method. Thus, approximate emissions indices applied to actual flight procedures are a better choice than a standard ICAO LTO emission estimate from the databank. The correlations are then applied to the prediction of LTO emissions of a turboprop airplane (Bombardier Q400).     

A statistical model for estimating oxides of nitrogen emissions from light duty motor vehicles

Motor vehicle emission rate models for predicting oxides of nitrogen (NOx) emissions are insensitive to vehicle modes of operation such as cruise, acceleration, deceleration, and idle, because they are based on average trip speed. Research has shown that NOx emissions are sensitive to engine load; hence, load-based variables need to be included in emissions models. Ongoing studies attempting to incorporate these `modal' variables have experienced difficulties with: (1) incomplete and/or non-representative data sets of emissions test data vis-a-vis the modal operating profiles of the tested vehicles; (2) lack of information for predicting on-road operating parameters of vehicles; and (3) non-representative vehicles recruited for emissions tests.The objective of this research was to develop a statistical model for predicting NOx emissions from light-duty gasoline motor vehicles. The primary end use of this model is forecasting, rather than explanation of the factors that affect NOx emissions, which brings to bear different requirements from the statistical model. The three challenges noted above are addressed by: (1) analyzing a data set of more than 13 000 hot-stabilized laboratory treadmill tests on 19 driving cycles (specific speed versus time testing conditions), and 114 variables describing vehicle, engine and test cycle characteristics; (2) making the models compatible with empirical data on how vehicles are being operated in-use; and (3) developing statistical weights to account for the differences in model year distributions between the emissions testing database and the current national on-road fleets.The NOx emissions model is estimated using ordinary least-squares regression techniques, with transformed response variable and regression weights. Tree regression is employed as a tool for mining relationships among variables in the data, with particular focus on identifying useful interactions among discrete variables. Details of the model development process are presented, as well as results for the final model showing the predicted emissions algorithm for the current motor vehicle fleet in Atlanta, GA metropolitan region.