Standard driving cycles (DCs) and real driving emissions (RDE) legislation developed by the European Commission contains significant gaps with regard to quantifying local area vehicle emission levels and fuel consumption (FC). The aim of this paper was to review local DCs for estimating emission levels and FC under laboratory and real-world conditions. This review article has three sections. First, the detailed steps and methodologies applied during the development of these DCs are examined to highlight weaknesses. Next, a comparison is presented of various recent local DCs using the Worldwide Harmonized Light-Duty Test Cycle (WLTC) and FTP75 (Federal Test Procedure) in terms of the main characteristic parameters. Finally, the gap between RDE with laboratory-based and real-world emissions is discussed. The use of a large sample of real data to develop a typical DC for the local area could better reflect vehicle driving patterns on actual roads and offer a better estimation of emissions and consumed energy. The main issue found with most of the local DCs reviewed was a small data sample collected from a small number of vehicles during a short period of time, the lack of separate phases for driving conditions, and the shifting strategy adopted with the chassis dynamometer. On-road emissions measured by the portable emissions measurement system (PEMS) were higher than the laboratory-based measurements. Driving situation outside the boundary conditions of RDE shows higher emissions due to cold temperatures, road grade, similar shares of route, drivers’ dynamic driving conditions, and uncertainty within the PEMS and RDE analysis tools.
Diesel engines are widely used due to their higher thermal efficiency and lower Hydrocarbon (HC) emissions. The price fluctuation of petroleum fuel; the none-renewability and different hazardous emissions from petro-diesel, researchers are searching for a suitable renewable energy source for diesel engine. Ethanol is one of the promising alternative fuels that could be used to power diesel engine. Some of the techniques so far tried are ethanol fumigation, dual injection and blending. The former techniques need different engine modification to enable the additional systems to work on the existing engines. Blending is the best technique to substitute the existing diesel fuel as long as we prepare it as per the current diesel fuel minimum requirement. For this specific case micro emulsion of ethanol in diesel fuel with emulsifier is prepared by using magnetic stirrer and bath type ultrasonicator. Nickel Zinc Iron Oxide (NiZnFe2O4) nanoparticle is added in one of the selected emulsion which is having 10% ethanol in three different dose as additive to see the effect on the performance and emission variation of the emulsion compared with diesel fuel. The performance of the prepared sample fuels are tested on a test rig with single cylinder diesel engine. The emission is measured by using exhaust gas analyzer and smoke opacity meter. The specific fuel consumption, brake torque and brake power of E5 (95% diesel and 5% ethanol), E10 (90% diesel and 10% ethanol) and E15 (85% diesel and 15% ethanol) are evaluated and the result showed 27, 34 and 37% increment in fuel consumption; 15, 5 and 15% reduction in brake torque and the power reduction is 19, 7 and 12% respectively. E10 is selected for further test with addition of the nanoparticle with 25, 50 and 100ppm named as E103N25 (E10 with 25ppm NiZnFe2O4 nanoparticle), E103N50 (E10 with 50ppm NiZnFe2O4 nanoparticle) and E102N100 (E10 with 100 ppm NiZnFe2O4 nanoparticle). The result showed fuel consumption reduction by 16, 27 and 27% torque output increment of 1, 2 and 2% and power output increment of 5, 7 and 7% respectively compared with E10. The emission result revealed that the HC emission reduced by 50, 58 and 71% for E103N25, E103N50 and E103N100 fuel samples respectively, Carbon monoxide (CO) emission reduced by 67, 80 and 81% for E103N25, E103N50 and E103N100 fuel samples respectively. The reduction in smoke emission is reduced by 60, 69 and 61% for E103N25, E103N50 and E103N100 fuel samples respectively. Nitrogen oxide (NOX) and Carbon dioxide (CO2) emissions increased with the amount of nanoparticle added in to the fuel.
Searching for ultra-low emission engines particularly for automotive applications is still ongoing. Even though LTC combustion mode results a prominent advantages in terms of reducing both NOx and PM and also lowering the consumption of fuel, it mainly faces with the challenge of excess emissions of HC and CO. This study aimed to optimize the operating control factors for low emissions in PCCI-DI engine under LTC mode. Parameters include injection timing, EGR level, dieseline ratio and engine load. Computation of analyzing the grey relation with hybrid of Taguchi was applied. In designing of experiments and conducting tests Taguchi's L9 matrix was applied. Air-blast of methanol intake port supply and dieseline application instead of diesel was implemented aiming emission reductions. Optimum combinations were found using GRA and ANOVA. Following the optimization work; advanced injection timing of 25o before TDC, 25% EGR, dieseline 90:10 in % and load 75 % (A2B1C3D3) was found optimal combination level for the proposed aim of emission reductions. Key findings of the results following the experiment conducted using this optimal combination includes; reduction of 68.02% NOx and 62.37% in smoke comparing with the base-line conventional diesel combustion mode. Rankings and ANOVA indicated another findings that injection timing being most influential with a contribution of 69.35% followed by load, dieseline ratio and EGR level respectively. This study confirmed dieseline direct injection with methanol port injection is capable of reducing emissions and better NOx with HC and CO trade-offs in PCCI-DI engines.
Diesel engine is the prime mover on land transportation industry and used in a variety of power generation applications due to their higher fuel efficiency. However, the engine research community faces a major hurdle rigorous restriction introduced in the Glob to reduce pollutant emissions from internal combustion engines. Different piston bowl shape designs allows more precise mixing before combustion to enhance in the optimization using computational calculations to reduce emissions. The investigation was to reduce the NOx and PM emissions using combustion simulation comparing with each piston of a single-cylinder engine at a CR of 24, 4-stroke, and water-cooled Engine. The four piston bowl shapes of DSEVL2 BMW M47T, Shallow Hesselman, Lombardini 15LD350, and DOOSANP158FE were analyzed by the Diesel-RK combustion simulation. After successful validating; the simulation model shows that the peak cylinder pressure of Piston-2 is 131bar and the peak cylinder pressure of Piston-4 is 113bar. The Maximum Cylinder Temperature of the Piston-2 is 2048.2k, and the lowest value of Cylinder Temperature of the Piston-4 is 1680.9k the cylinder temperature of Piston-2 is 18% higher than Cylinder Temperature of Piston-4. The simulation result indicates that the temperature is within the acceptable limit in between 1400-2000k except for the piston temperature of 2048.2k. The PHRR of the Piston-3 is 0.082 with great variation in between maximum and minimum due to the presence of pre-and post-injection, the HRR-P4 is 0.035 J/°CA with the single injections. The HRR of the Piston-3 is the highest while HRR of the Piston-4 lowest with 39%. The NOx in the exhaust gas is 25.62 in the NOx piston-1; 16 in NOx of Piston-2, 18.2 in NOx-P3, and NOx-P4 is 12.74 g/kWh respectively. The NOx of the NOx-P2 is lower than first and second piston due to the lower fuel fraction of NWF dilution outer the sleeve, low fuel fraction in core of the free spray, low fuel fraction in fronts of the free spray, low fuel fraction in the core of the fuel free spray. The Particulate Matter emission in PM-P1 is 0.35, and PM-P2 is 0.43 g/kWh which is higher than all the other. Although there is a substantial decrease in PM, a penalty in NOx is observed for PM-P1 but PM of the P2 is higher after the peak result of emission.
This study aimed to develop the Addis Ababa Driving Cycle (DC) using real-time data from passenger vehicles in Addis Ababa based on a neural network (NN) and principal component analysis (PCA) approach. Addis Ababa has no local DC for automobile emissions tests and standard DCs do not reflect the current scenario. During the DC’s development, the researchers determined the DC duration based on their experience and the literature. A k-means clustering method was also applied to cluster the dimensionally reduced data without identifying the best clustering method. First, a shape-preserving cubic interpolation technique was applied to remove outliers, followed by the Bayes wavelet signal denoising technique to smooth the data. Rules were then set for the extraction of trips and trip indicators before PCA was applied, and the machine learning classification was applied to identify the best clustering method. Finally, after training the NN using Bayesian regularization with a back propagation, the velocity for each route section was predicted and its performance had an overall R-value of 0.99. Compared with target data, the DCs developed by the NN and micro trip methods have a relative difference of 0.056 and 0.111, respectively, and resolve the issue of the DC duration decision in the micro trip method.
This work reports on the simulation of three-wheel vehicles in the event of a side pole crash. In this study, the dynamic characteristics of the three-wheeler vehicle during pole collision were studied using finite elements. The TWV model used here was created using CATIA v5 and simulated using LS-DYNA which is widely used by the automotive industry to analyze vehicle design and predict a cars behavior in a collision. Moreover, in this study, the finite element model of the side hybrid 5th percentile male dummy was developed for studying the driver and occupant responses in crash events of side pole. Based on the analysis results obtained from the existing model of TWV, modifications were made on the side structure by means of adding energy-absorbing components. Then, the modified TWV was analyzed under the same condition as the existing one. The result of the simulations shows that with the modification, 80mm more living space, 630N reduction of impact force, and 0.8kJ of additional absorbed energy were obtained. So with the modified model, the safety and crashworthiness of the TWV were greatly improved during side collision without affecting the appearance and weight of the existing models.