A vehicle interacts with the road, other vehicles, and traffic control devices in real traffic conditions. The level of traffic influences driving patterns and, consequently, this can affect the ...vehicle´s fuel efficiency and emissions. This study aims to develop engine maps of fuel consumption and CO2 emissions for a light vehicle operating under real traffic conditions. A representative passenger vehicle of the Ecuadorian vehicle fleet, powered by gasoline, was selected for the experimental campaign that was developed on a test route designed according to real driving emission (RDE) regulation. An on-board diagnostic (OBD) device was used for recording in real-time engine and vehicle operating parameters. Moreover, CO2 emissions were estimated using the fuel rate registered from the OBD system of the vehicle This study proposed a novel methodology for developing two-dimensional contour engine maps based on OBD data. The result showed that the vehicle engine operated in real traffic conditions with a brake thermal efficiency (BTE) of 27%, a brake-specific fuel consumption (BSFC) of 275 g/kWh, and a carbon dioxide (CO2) energy-emission factor of 716 g/kWh. In terms of distance, the CO2 emission factor for the tested vehicle was approximately 190 g/km. Overall, this study demonstrates that the OBD approach is a potential method to be used to assess the fuel consumption and emissions of a vehicle operating under real-world traffic conditions, especially in Latin American countries, where portable emission measurement systems (PEMS) are not readily available.
•Real-world performance comparison between compressed natural gas and diesel buses.•Higher THC emissions for the compressed natural gas bus compared to the diesel bus.•Increase of 6–55% of fuel ...consumption with variations in the operating conditions.•Less NOx emissions for the natural gas bus at high congestion and road grade levels.•Vehicle specific power predicts CO2 and NOx emissions with good accuracy.
This study investigated the effects of passenger load, road grade, and congestion level on the fuel consumption and emissions from a Euro VI compressed natural gas (CNG) urban bus and a Euro V diesel urban bus. Testing was performed under real-traffic conditions in Madrid, Spain, using a portable emission measurement system (PEMS). The PEMS data also were combined with the vehicle specific power (VSP) methodology to analyse the differences between the performance of the two types of buses and develop an energy-based emission model. Between the empty and 4000 kg passenger load cases, the fuel consumption and CO2 emissions for the diesel bus showed a significant increase by approximately 25%. With an increase in the road grade, and congestion level, the fuel consumption and CO2 emissions of both types of buses increased, by 6–55%. Unlike in the case of the diesel bus, the NOx emissions of the CNG bus decreased by 40–50% as the level of road grade and congestion increased. At intervals of VSP ≥ 2 kW/t, NOx emission rates for the CNG bus were approximately 60% lower than those of the diesel bus. Finally, the proposed VSP-based model estimated the fuel consumption and the CO2 and NOx emission factors with relative total errors of less than 13%.
In recent years, the integration of traffic simulators and emission models has become the most preferred option for evaluating vehicle emissions in different traffic states. However, the definition ...of a ‘traffic condition’ is often subjective, as driving patterns can vary significantly with the spatial domain of study. Alternatively, the implementation of ‘Cooperative Intelligent Transport Systems’ has led to a growing variety of devices being installed, both on the road and in public transport vehicles for monitoring traffic-flow conditions and vehicle speeds in cities. This study purposed an original approach for integrating real-world emissions (as an micro-emission model), real-world driving profiles, and city traffic sensor data to assess the effects of traffic congestion at the route level on emissions from urban buses in Madrid (Spain). The definition of the traffic scenarios was based on a K-means clustering analysis by linking stationary (from city sensors) and dynamic (from bus driving profiles) congestion indicators. In parallel, a micro-emissions model based on vehicle-specific power (VSP) methodology was used to model second-by-second CO2 and NOx emissions from individual trips of the diesel and compressed natural gas (CNG) buses. Finally, the clustering and modelled emissions data were combined.
A comparison of the free flow and the severe congestion scenarios showed that the average speed of the route decreased by approximately 50 %, and the number of stops per kilometre increased by a multiple of 1.5; furthermore, the CO2 and NOx emissions from buses increased by approximately 50 % and 85 %, respectively. The diesel bus showed a lower sensitivity to variations in the congestion level at the route level, although the low-NOx emissions from the CNG buses were evident for all traffic scenarios. The results of this study, based on extensive real-world data, can be used to develop high-resolution vehicle emissions inventories.
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•An original approach to combine real-world emissions, open-access traffic, and GPS data.•Definition of real-world traffic scenarios using a K-means clustering analysis.•Mapping of bus emissions and congestion level with high-resolution route detail.•Increase by 30–85 % of CO2 and NOx emissions comparing free flow and severe congestion.•Less NOx emissions of CNG bus compared with diesel bus for all traffic scenarios.
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•A new method uses VSP with load-rpm engine maps to estimate vehicle emissions.•Pareto optimization was applied for the sizing of emission maps.•Real-world VSP emission factor errors ...were reduced up to 63% (CO2) and 15% (NOx).•The method optimise urban/total sections and RMSE/emission factor errors at once.•Optimal binning and data points of engine maps were found for CI/SI engines.
Vehicle emission models are relevant for evaluating the performance of vehicle technologies and help in the definition of environmental policies. This paper presents an improved emissions modelling approach (named VSP+M) by combining the vehicle specific power (VSP) with load-regime engine maps for each VSP mode. The new modelling enabled to link tailpipe emissions to vehicle and engine operating conditions, obtained from real driving emission (RDE) tests and on-board diagnosis (OBD) data. The parameters for the sizing of engine maps were optimised by means of Pareto frontiers to solve the trade-off between the minimisation of RMSE and emission factor errors in urban sections and total RDE trips. The CO2 emission factors errors were reduced up to 63% and 45% for urban and RDE sections, respectively. The NOx emission factor errors were reduced up to 15%, maintaining the same RMSE levels. Optimal engine maps sizing was found for every tested vehicle and for each engine type to be applied in other vehicles. This study demonstrates the potential to address declinations of the conventional VSP model based on engine operation or proxies to those variables by using the proposed approach.
•PEMS and OBD systems were used to obtain data for engine maps.•A Euro V diesel engine operates with a brake thermal efficiency of 41%•The real-world NOx energy-emission factor was higher than Euro V ...Standard.•The passenger load does not produce difference in engine performance.•The grid engine maps model predicts CO2 emissions with good accuracy.
Until recently, heavy-duty vehicle (HDV) engines were subjected to pollutant emissions type-approval tests, which were developed on engine test benches under standardised driving cycles. However, these results do not reflect engine behaviour under real-world driving conditions. In this context, experimental measurements were conducted on a diesel Euro V bus under urban off-cycle conditions in Madrid (Spain). The main objective was to create efficiency and emissions engine maps by combining transient-state engine data obtained directly from portable emission measurement system (PEMS) and on-board diagnostic (OBD) data acquisition systems. The engine maps were used to evaluate engine performance in real-world conditions, and to create a model that allows for second-by-second prediction of the engine fuel consumption and emissions. Owing to the variability of transient-state engine data, this work proposed an engine map development method, consisting of grouping the measured data into grids by engine speed and torque ranges, and then averaging them to obtain a single value per grid.
The results showed that the Euro V diesel bus engine operates in urban off-cycle conditions with a brake thermal efficiency (BTE) of 41%, a brake-specific fuel consumption (BSFC) of 205 g/kWh, and a carbon dioxide (CO2) energy-emission factor of 637 g/kWh. The NOx energy-emission factor was 80% higher than the levels in the Euro V Standard.
This work demonstrated that the grid engine maps model has the potential to predict second-by-second fuel consumption and CO2 emissions, with a relative total error of less than 5%. Therefore, this approach could be useful for accurately simulating engine or vehicle performance for any operation scenarios at a microscopic level, provided engine torque and engine speed data from the bus are available.
El control auto-disparado produce secuencias de muestreo no periódico que varían dependiendo de factores de diseño relacionados con la estabilidad y el rendimiento del sistema a ser controlado. ...Dentro de este marco, recientemente han sido desarrollados dos enfoques dirigidos a minimizar un costo cuadrático, considerando un rendimiento óptimo y persiguiendo el mismo objetivo de control; cada una de ellos sigue una regla de muestreo diferente. Un enfoque se basa en mantener el valor de control actual tanto tiempo como sea posible, mientras que un umbral de rendimiento óptimo no se traspase. El otro enfoque se basa en la generación de una señal de control a trozos que se aproxima a una señal de control óptima continua, sujeta a determinadas limitaciones. Este artículo presenta un estudio comparativo entre los dos enfoques, proporcionando una percepción útil para la realización de futuras investigaciones. Como métricas de interés, el rendimiento de control y la utilización de recursos fueron considerados, y para evaluarlos, se hizo uso del intervalo de muestreo promedio y del costo normalizado. Se demostró que el diferente espacio de búsqueda de cada enfoque plantea un desafío para diseñar un marco de comparación equitativo, y que ambos enfoques superan al muestreo periódico.
Las ciudades de Latinoamérica tienen problemas de contaminación y tráfico por la falta de investigación y planificación del sector de transporte. En Ecuador, las características de las flotas de ...transporte y su cinemática en la ciudad no se han determinado. El presente estudio analiza detalladamente las características cinemáticas de cada ruta de transporte público de la ciudad de Ibarra-Ecuador mediante el uso de equipos de georreferenciación GPS para cada segundo de recorrido. Se monitoreó 22 rutas de autobuses urbanos, evaluando 186 autobuses en 832 viajes, en los que se determinó que la velocidad promedio, la aceleración y desaceleración dependen, principalmente, de tres factores: ruta, sector de la ciudad y modelo de vehículo. Otros factores como operadora, edad de conductor, tiempos de viaje y la franja horaria no presentaron mayor significancia en la influencia a las variables cinemáticas en estudio, por lo que no se consideran dentro del estudio de investigación.
La Inteligencia Artificial en el campo educativo ha generado varias herramientas de ayuda a estudiantes y docentes, este innovador material cuenta con beneficios y desafíos. El objetivo de este ...estudio fue analizar el uso de la Inteligencia Artificial en el proceso de enseñanza aprendizaje, con la finalidad de describir sus ventajas y desventajas, a partir de diferentes enfoques y aportes investigativos. La metodología que se utilizó se fundamentó en una línea teórica, mediante la técnica revisión bibliográfica, con un análisis de tipo descriptivo y exploratorio. Los hallazgos indican que la existe ventajas al utilizar la inteligencia artificial en el ámbito educativo, como la mejora de la calidad educativa porque asegura aprendizajes significativos, retroalimentación efectiva; la disminución de la carga docente, contextualización de las planificaciones y evaluaciones simplificadas y prácticas; entre sus desventajas se puede determinar que no deja de ser un elemento artificial programado, por ello no puede solventar la interacción social sobre todo la afectividad. Finalmente se concluye que la inteligencia Artificial ha emergido como una herramienta valiosa en la educación, permitiendo la personalización del aprendizaje, mejorando la calidad educativa y brindando apoyo tanto académico como emocional a los estudiantes.
Electric vehicles are promoted to reduce the environmental impacts and energy demand of transport. Lithium-ion batteries (LIBs) are critical elements for the operation of electric vehicles, but their ...production and final disposal cause environmental pollution. This work analyzed the entire life cycle of the electric motorcycle's LIBs, focusing on real-world use. The real-world autonomy and battery capacity were evaluated in urban, rural, and motorway routes of Ibarra, Ecuador. The LCA was computed in GaBi and Ecoinvent, while 12 midpoint impacts were assessed using the ReCiPe 2016 methodology. Results showed that most of the impacts are primarily produced in the production stage (China); in particular, climate change in production is significantly higher than in other stages. Human toxicity is primarily produced at the disposal stage, where usually the vehicle is used. Ozone depletion and particle matter formation resulted significative in production and transportation stages. The impact caused by the use of the vehicle was, in general, low because about 90 % of electricity in Ecuador is produced from alternative energy sources. This comprehensive analysis can be used by policymakers to implement taxes and incentives to change the vehicle's market and to promote the recycling and reuse of the LIBs.
Automatic cattle activity recognition on grazing systems Ramirez Agudelo, John Fredy; Bedoya Mazo, Sebastian; Posada Ochoa, Sandra Lucia ...
Biotecnologia en el sector agropecuario y agroindustrial,
07/2022, Letnik:
20, Številka:
2
Journal Article
Recenzirano
Odprti dostop
The use of collars, pedometers or activity tags is expensive to record cattle's behavior in short periods (e.g. 24h). Under this particular situation, the development of low-cost and easy-to-use ...technologies is relevant. Similar to smartphone apps for human activity recognition, which analyzes data from embedded triaxial accelerometer sensors, we develop an Android app to record activity in cattle. Four main steps were followed: a) data acquisition for model training, b) model training, c) app deploy, and d) app utilization. For data acquisition, we developed a system in which three components were used: two smartphones and a Google Firebase account for data storage. For model training, the generated database was used to train a recurrent neural network. The performance of training was assessed by the confusion matrix. For all actual activities, the trained model provided a high prediction (> 96 %). The trained model was used to deploy an Android app by using the TensorFlow API. Finally, three cell phones (LG gm730) were used to test the app and record the activity of six Holstein cows (3 lactating and 3 non-lactating). Direct and non-systematic observations of the animals were made to contrast the activities recorded by the device. Our results show consistency between the direct observations and the activity recorded by our Android app.
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