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.

In this work, wire cut electrical discharge machining (WEDM) is used for the material removing processes; it is utilized for machining conductive parts where it is required to produce complicated shapes, new profiles, new geometry, new product development, and high-accuracy components. This machining process is best suitable for high-end applications such as aerospace, automations, automobile, and medical devices. At present, most of the industrial sectors choose the WEDM process because it is used to develop products in a very short development cycle and at a better economic rate. In this paper, the selected complex geometry of the metal sample was eroded away from the wire during the WEDM process, which eliminates mechanical tensions during machining. The effect of different WEDM operation variables set as wire speed, wire tension, discharge current, dielectric flow rate, and pulse on and off time on the parameter, stainless steel 304 material removing rate (MRR) using RSM, has been studied. The MRR will be maximized if the optimum sets of operational variations are used and also achieve a superior surface finish.

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 (NO_X) and Carbon dioxide (CO₂) emissions increased with the amount of nanoparticle added in to the fuel.

In machining processes, cutting tools play a dominant role in producing quality products. The quality of finished goods is directly related to the cutting tool condition. Several types of research have been carried out in cutting tool condition monitoring. On the other hand, the manufacturing industries should be aware of the cutting tool selection, operating conditions, and performance of cutting tools. This article emphasizes the performance of coated cutting tools and tool materials for various machining operations. Nowadays, the nanocoating of CNC tool inserts increases the wear resistance, vibration emissions, metal removal rate, etc. These coating techniques influence the manufacturing industry to increase the productivity and quality of the finished goods and reduce the machining cost. The performance of thin film multilayered coatings such as TiN, TiAlN, AlTiN, Ti, and TiCN on plain silicon carbide tool inserts is revealed by the researchers to guide the manufacturing industry for proper tool selection and standard machining inputs for metal removal operation. The influence of coating material such as TiBN, TiN, TiAlN, and CrAlSiN in cutting tools leads to increase the life time of the cutting tools, which decreases the material sticking and cutting forces. Titanium carbo nitride is wear-resistant and corrosion-resistant. Compared to TiCN, TiAlN is harder due to the higher hardness of 32 GPa. This article concludes the material selection based on the work piece material which yields good metal removal with less cutting forces. The article concludes the cutting material selection based on the work piece for machining operations.

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 NO_x 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 25^o 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% NO_x 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 NO_x with HC and CO trade-offs in PCCI-DI engines.

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.