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Item type:Publication, Fuel consumption and emissions analysis of a light vehicle fuelled with two ethanol–gasoline blends in urban driving conditions of Lima Metropolitana(MDPI AG, 2021-09-01)We present a comparative study of fuel consumption, emissions factors, and vehicle-specific power of a light vehicle operating with two gasoline–ethanol blends as fuel: commercial gasohol (E7.8) and an alternative mix with 10% v/v of ethanol (E10). For this purpose, a vehicle in the city’s fleet was equipped with a central system of data acquisition, whose main function was to capture second-by-second data of the air intake of the engine, the emissions concentration levels in the exhaust, the distance traveled, vehicle speed, and environmental conditions during testing. The measuring campaign was carried out in the city of Lima Metropolitana. Fuel consumption was calculated indirectly, using air intake measurements. The vehicle’s engine emissions were analysed using the mass flow rates of CO2, CO, HC, and NOx, as well as the vehicle-specific power. The results show that, in traffic conditions, the change in fuels does not affect the consumption. On the other hand, a correlation was found between the vehicle-specific power and the emissions mass flow. During the comparison between fuels, the results showed an increase in the mass flow standard deviation when using E10. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Experimental characterization of chalcopyrite ball mill grinding processes in batch and continuous flow processing modes to reduce energy consumption(Elsevier, 2021-11-01)A mineralogy, rheology, and energy consumption-based experimental characterization of chalcopyrite ball mill grinding processes, in both batch and continuous flow processing modes, is carried out in this work. Accordingly, chalcopyrite ore samples are initially characterized in terms of mineralogical composition, particle size distribution, grindability characteristics, and work index. Next, a rheological characterization of actual and lab-created chalcopyrite mineral-slurries is performed. Finally, an energy consumption-based characterization of several chalcopyrite ball mill grinding processes is performed. The results from the initial mineralogical characterization indicate ore samples featuring 5% chalcopyrite. These results also highlight that 80% of the particles present in the chalcopyrite head ore have a diameter smaller than 1386 μm. In addition, they indicate that the Bond ball mill work index is equal to 15.3 kWh/ton, which corresponds to a mineral with the presence of chalcopyrite. The rheological characterization related results indicate that all actual and lab-created mineral-slurries exhibit a shear thinning rheological behavior. These results also show that, because of the higher number of particle interactions, the slurries’ apparent viscosity increases with the increase in their solids content. Finally, the energy consumption-based characterization results emphasize that energy consumption is more significantly affected by mill speed than by slurry solids content. Indeed, for the same percentage of mass passing through a 200 mesh, it is found that the specific grinding energy decreases with both the increase in slurry solids concentration and the decrease in mill speed. The results obtained in this work are consistent with findings made in previous studies. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, In-cylinder pressure statistical analysis and digital signal processing methods for studying the combustion of a natural gas/diesel heavy-duty engine at low load conditions(Elsevier Ltd, 2022-10-01)In-cylinder pressure analysis is one of the most important tools for combustion diagnosis. The dual-fuel compression ignition engines present a different in-cylinder pressure evolution for consecutive cycles due to the high cyclic variability. One source of the cyclic variability is a long ignition delay caused by a low-temperature combustion chamber (at low load conditions) and this effect led to lower efficiency, higher emissions, and driveability problems. In the present study, a six-cylinder turbocharged heavy-duty diesel engine (6.7 L) was used to acquire the in-cylinder pressure signal at low-load operating conditions. Then a statistical methodology is proposed to process the experimental pressure signal for a combustion diagnosis approach obtained at different loads for diesel mode and dual fuel mode. First, a representative sample number of consecutive thermodynamic cycles is determined, and then the cut-off frequencies for in-cylinder pressure signal digital filtering are selected by the analysis of the Fourier Transform spectrum for the test engine using only diesel fuel and natural gas/diesel mode. The results show an effective high-frequency noise diminish (related to the resonance combustion chamber) on the filtered pressure signals. Therefore, a high-quality curve of the heat release rate can be reached, which allows identifying the combustion process at low-loads operating conditions. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Development and Validation of a Methodology for Predicting Fuel Consumption and Emissions Generated by Light Vehicles Based on Clustering of Instantaneous and Cumulative Vehicle Power(Multidisciplinary Digital Publishing Institute (MDPI), 2025-03-01)In the global context, transportation contributes 26% of the total CO2 emissions, with land transport responsible for 92% of the emissions within the sector. Given this significant contribution to climate change, it is crucial to quantify vehicular impacts to implement effective mitigation strategies. This study introduces an innovative method for predicting fuel consumption and emissions of carbon monoxide, hydrocarbons, and nitrogen oxides in vehicles, based on instantaneous vehicle-specific power (VSP) and mean accumulated power. VSP is a parameter that measures a vehicle's power in relation to its mass, providing an indicator of the efficiency with which the vehicle converts fuel into motion. This indicator is particularly useful for assessing how vehicles utilize their energy under different driving conditions and how this affects their fuel consumption and emissions. Using data collected from 10 vehicles over 2000 h and covering altitudes from 0 to 4000 m above sea level in Ecuador, the method not only improved the accuracy of consumption predictions, reducing the margin of error by up to 10% at high altitudes, but also provided a detailed understanding of how altitude affects both consumption and emissions. The precision of the new method was notable, with a standard deviation of only 0.25 L per 100 km, allowing for reliable estimates under various operational conditions. Interestingly, the study revealed an average increase in fuel consumption of 0.43 L per 1000 m of altitude gain, while CO2 emissions showed a significant reduction from 260.93 g/km to 215.90 g/km when ascending from 500 m to 4000 m. These findings underscore the relevance of considering altitude in route planning, especially in mountainous terrains, to optimize performance and environmental sustainability. However, the study also indicated an increase in CO and NOx emissions with altitude, a challenge that highlights the need for integrated strategies addressing both fuel consumption and air quality. Collectively, the results emphasized the complex interplay between altitude, energy efficiency, and vehicular emissions, underscoring the importance of a holistic approach to transportation management, to minimize adverse environmental impacts and promote sustainability.1