Assessing the effects of ethanol additive and driving behaviors on fuel economy, particle number, and gaseous emissions of a GDI vehicle under real driving conditions

Nozzle hydraulic flow rate is a critical parameter that affects the combustion process and plays a vital role in the production of emissions from a diesel engine. In this study, injection characteristics, such as normalized injection rate and spray tip penetration, were analyzed for different hydraulic flow rate injectors with the help of spray experiments. To further investigate the effects of hydraulic flow rate on engine-out particulate and gaseous emissions, engine experiments were performed for different values of hydraulic flow rate in multiple injectors. Various operating conditions and loading configurations were examined, and the effects of varying start of injection and exhaust gas recirculation rates for different hydraulic flow rates were analyzed. A separate Pegasor Particle Sensor (PPS-M) sensor was used to measure and collect data on the particle number, and an analysis was conducted to investigate the relation of particle number with hydraulic flow rate, injection timing, and exhaust gas recirculation rate. Results of the spray experiment exhibited a decreasing injection duration and increasing spray tip penetration with increasing hydraulic flow rate. Effect of hydraulic flow rate on combustion and emission characteristics were analyzed from engine experiment results. Least ignition delay was achieved using a smaller hole diameter, retarded injection timing, and lowest EGR%. Higher hydraulic flow rate with retarded injection timing and higher EGR% helped in reduction of NOx emissions and brake-specific fuel consumption, but particulate emissions were increased. Best particulate matter–NOx trade-off was achieved with lowest hydraulic flow rate.

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Black carbon, particle number concentration and nitrogen oxide emission factors of random in-use vehicles measured with the on-road chasing method

Atmospheric Chemistry and Physics ◽

10.5194/acp-15-11011-2015 ◽

2015 ◽

Vol 15 (19) ◽

pp. 11011-11026 ◽

Cited By ~ 21

Author(s):

I. Ježek ◽

T. Katrašnik ◽

D. Westerdahl ◽

G. Močnik

Keyword(s):

Black Carbon ◽

Particle Number ◽

Measurement Techniques ◽

Carbon Particle ◽

Emission Factors ◽

Passenger Cars ◽

Vehicle Fleet ◽

Driving Conditions ◽

Black Carbon Particle ◽

Good Agreement

Abstract. The chasing method was used in an on-road measurement campaign, and emission factors (EF) of black carbon (BC), particle number (PN) and nitrogen oxides (NOx) were determined for 139 individual vehicles of different types encountered on the roads. The aggregated results provide EFs for BC, NOx and PN for three vehicle categories: goods vehicles, gasoline and diesel passenger cars. This is the first on-road measurement study where BC EFs of numerous individual diesel cars were determined in real-world driving conditions. We found good agreement between EFs of goods vehicles determined in this campaign and the results of previous studies that used either chasing or remote-sensing measurement techniques. The composition of the sampled car fleet determined from the national vehicle registry information is reflective of Eurostat statistical data on the Slovenian and European vehicle fleet. The median BC EF of diesel and gasoline cars that were in use for less than 5 years decreased by 60 and 47 % from those in use for 5–10 years, respectively; the median NOx and PN EFs of goods vehicles that were in use for less than 5 years decreased from those in use for 5–10 years by 52 and 67 %, respectively. Surprisingly, we found an increase of BC EFs in the newer goods vehicle fleet compared to the 5–10-year old one. The influence of engine maximum power of the measured EFs showed an increase in NOx EF from least to more powerful vehicles with diesel engines. Finally, a disproportionate contribution of high emitters to the total emissions of the measured fleet was found; the top 25 % of emitting diesel cars contributed 63, 47 and 61 % of BC, NOx and PN emissions respectively. With the combination of relatively simple on-road measurements and sophisticated post processing, individual vehicle EF can be determined and useful information about the fleet emissions can be obtained by exactly representing vehicles which contribute disproportionally to vehicle fleet emissions; and monitor how the numerous emission reduction approaches are reflected in on-road driving conditions.

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UPDATING EMISSION FACTORS FOR IN-USE MOTORCYCLES FUELED BY GASOLINE, E5 AND E10 IN VIETNAM

ASEAN Engineering Journal ◽

10.11113/aej.v11.17055 ◽

2021 ◽

Vol 11 (3) ◽

pp. 199-206

Author(s):

Pham Huu Tuyen ◽

Pham Minh Tuan ◽

Kazuhiro Yamamoto ◽

Preechar Karin

Keyword(s):

Particle Number ◽

Combustion Engine ◽

Low Cost ◽

Emission Factors ◽

Exhaust Gas ◽

Gaseous Emissions ◽

Chassis Dynamometer ◽

Sampling System ◽

Particulate Matter Emission ◽

Long Time

Motorcycle is the most popular transportation means in Vietnam due to its low cost and flexibility. However, motorcycles emit substantial quantities of hydrocarbons, carbon monoxide, nitrogen oxides and some amount of particulate matter. Emission factors for in-use motorcycles in Vietnam were studied and established quite a long time ago. The objective of this study is to update the emission factors, not only gaseous emissions but also particle number, for in-use motorcycles in Vietnam. Ten carbureted and electronic fuel injected motorcycles representative for in-use motorcycles were selected for investigation. Each motorcycle was fueled by conventional gasoline, E5 and E10 in turn, and was tested on a chassis dynamometer according to ECE R40 driving cycle. The gaseous emissions were sampled and determined by standard methods, while the particle number in exhaust gas was sampled by using the sampling system developed by Laboratory of Internal Combustion Engine, Hanoi University of Science and Technology, Vietnam. The updated emission factors were then provided for carbureted motorcycles, EFI motorcycles and average motorcycle fleet in case of gasoline, E5 and E10 fueling.

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Improving Vehicle Fleet Fuel Economy via Learning Fuel-Efficient Driving Behaviors

2012 5th International Conference on Human System Interactions ◽

10.1109/hsi.2012.28 ◽

2012 ◽

Cited By ~ 2

Author(s):

Ondrej Linda ◽

Milos Manic

Keyword(s):

Fuel Economy ◽

Driving Behaviors ◽

Vehicle Fleet

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Hierarchical Model Predictive Control for Hydraulic Hybrid Powertrain of a Construction Vehicle

Applied Sciences ◽

10.3390/app10030745 ◽

2020 ◽

Vol 10 (3) ◽

pp. 745

Author(s):

Zhong Wang ◽

Xiaohong Jiao

Keyword(s):

Energy Management ◽

Predictive Control ◽

Fuel Economy ◽

Optimization Problem ◽

Lower Layer ◽

Hybrid Powertrain ◽

Construction Machinery ◽

Stochastic Optimization Problem ◽

Driving Conditions ◽

Disturbance Estimator

Hybrid hydraulic technology has the advantages of high-power density and low price and shows good adaptability in construction machinery. A complex hybrid powertrain architecture requires optimization and management of power demand distribution and an accurate response to desired power distribution of the power source subsystems in order to achieve target performances in terms of fuel consumption, drivability, component lifetime, and exhaust emissions. For hybrid hydraulic vehicles (HHVs) that are used in construction machinery, the challenge is to design an appropriate control scheme to actually achieve fuel economy improvement taking into consideration the relatively low energy density of the hydraulic accumulator and frequent load changes, the randomness of the driving conditions, and the uncertainty of the engine dynamics. To improve fuel economy and adaptability of various driving conditions to online energy management and to enhance the response performance of an engine to a desired torque, a hierarchical model predictive control (MPC) scheme is presented in this paper using the example of a spray-painting construction vehicle. The upper layer is a stochastic MPC (SMPC) based energy management control strategy (EMS) and the lower layer is an MPC-based tracking controller with disturbance estimator of the diesel engine. In the SMPC-EMS of the upper-layer management, a Markov model is built using driving condition data of the actual construction vehicle to predict future torque demands over a finite receding horizon to deal with the randomness of the driving conditions. A multistage stochastic optimization problem is formulated, and a scenario-based enumeration approach is used to solve the stochastic optimization problem for online implementation. In the lower-layer tracking controller, a disturbance estimator is designed to handle the uncertainty of the engine, and the MPC is introduced to ensure the tracking performance of the output torque of the engine for the distributed torque from the upper-layer SMPC-EMS, and therefore really achieve high efficiency of the diesel engine. The proposed strategy is evaluated using both simulation MATLAB/Simulink and the experimental test platform through a comparison with several existing strategies in two real driving conditions. The results demonstrate that the proposed strategy (SMPC+MPC) improves miles per gallon an average by 7.3% and 5.9% as compared with the control strategy (RB+PID) consisting of a rule-based (RB) management strategy and proportional-integral-derivative (PID) controller of the engine in simulation and experiment, respectively.

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Effect of Extreme Temperatures and Driving Conditions on Gaseous Pollutants of a Euro 6d-Temp Gasoline Vehicle

Atmosphere ◽

10.3390/atmos12081011 ◽

2021 ◽

Vol 12 (8) ◽

pp. 1011

Author(s):

Barouch Giechaskiel ◽

Victor Valverde ◽

Anastasios Kontses ◽

Ricardo Suarez-Bertoa ◽

Tommaso Selleri ◽

...

Keyword(s):

Heavy Traffic ◽

Direct Injection ◽

Urban Environments ◽

Gasoline Direct Injection ◽

Particulate Filter ◽

Gaseous Emissions ◽

Ambient Temperatures ◽

Driving Conditions ◽

On The Road ◽

Cold Starts

Gaseous emissions of modern Euro 6d vehicles, when tested within real driving emissions (RDE) boundaries, are, in most cases, at low levels. There are concerns, though, about their emission performance when tested at or above the boundaries of ambient and driving conditions requirements of RDE regulations. In this study, a Euro 6d-Temp gasoline direct injection (GDI) vehicle with three-way catalyst and gasoline particulate filter was tested on the road and in a laboratory at temperatures ranging between −30 °C and 50 °C, with cycles simulating urban congested traffic, uphill driving while towing a trailer at 85% of the vehicle’s maximum payload, and dynamic driving. The vehicle respected the Euro 6 emission limits, even though they were not applicable to the specific cycles, which were outside of the RDE environmental and trip boundary conditions. Most of the emissions were produced during cold starts and at low ambient temperatures. Heavy traffic, dynamic driving, and high payload were found to increase emissions depending on the pollutant. Even though this car was one of the lowest emitting cars found in the literature, the proposed future Euro 7 limits will require a further decrease in cold start emissions in order to ensure low emission levels under most ambient and driving conditions, particularly in urban environments. Nevertheless, motorway emissions will also have to be controlled well.

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