Abstract

At present it is very important to estimate the contribution of the vehicle fleet in the inventories of polluting emissions for the city of Quito due to its geographical characteristic that places it at a height above 2810 m. In this research, the emission factors en route of three fuels used mainly by light vehicles in Ecuador are evaluated; Super gasoline with 93 octane; Extra gasoline with 87 octanes; and Ecopaís gasoline (Extra gasoline and 5% bioethanol). A Chevrolet Aveo 1.6 L vehicle was used, instrumented with an on-board system to obtain information on pollutant emissions and total fuel consumption in a pre-determined route of 12 km, at an average speed of 40 km/h. The simplified combustion model was used to develop a mass balance with respect to the amount of carbon present in the fuel, and thus obtain the emission factors ( ) in grams of pollutant per kilometer traveled. The results obtained are: Extra gasoline: CO 3.194 g/km, HC 0.060 g/km and NOx 0.142 g/km; Gasoline 92 Super: CO 4.770 g/km, HC 0.099 g/km and NOx 0.281 g/km; and Ecopaís gasoline: CO 5.939 g/km, HC 0.082 g/km and NOx 0.279 g/km.

Abstract

The research was carried out by the Finnish Public Transport Association. Altogether seven vehicles were measured, two two-axle Euro 3 -class vehicles as references, three new two-axle Euro 4 -class vehicles and two new three-axle vehicles. The measurements were carried out on a chassis dynamometer, using three cycles describing actual driving. In addition to fuel consumption, exhaust emissions were also recorded for these vehicles. The differences in fuel consumption and operating expenses were after all smaller than first anticipated. In the case of the Euro 3 -class reference vehicles, the difference between the two vehicles was as high as 7-10%. For new two-axle vehicles the difference in fuel consumption, when simulating urban driving, is only 3-4%. Due to different technical solutions, the results were anticipated to be greater. In suburban driving although, the difference is at its most 11%. In the class of two-axle vehicles, lowest fuel consumption was measured for a SCR vehicle, whereas in the case of the two three-axle vehicles, EGR technology resulted in lowest fuel consumption. The measurements do not give an unambiguous answer to whether the EGR- or SCR-technology is preferable regarding fuel consumption. The contemplation is hindered by two factors. On one hand, the order of superiority depends on the driving cycle, on the other, the actual exhaust emissions do not match with expectations. The two EGR vehicles (same make) produced higher NOx -emissions than the manufacturer's Euro 3 -engine. The most fuel efficient SCR -engine is not truly Euro 4 -class what comes to NOx -emissions. Only two of the new vehicles, both with SCR technology, produce NOx -emissions genuinely matching their classes. Both fuel consumption and exhaust emissions have been observed in the study. In case exhaust emissions were completely disregarded, fleet decisions might be directed towards fuel efficient vehicles which after all do not reach the level of emission performance that reasonably could be expected.

Abstract

International audience; This paper presents a new challenge on the strategic 4D trajectory optimization problem with the evaluation of air traffic complexity by using the geometric-based intrinsic complexity measure called König metric. The demonstration of König metric shows the potential that the algorithm can capture the disorganized the disorganized traffic which represents the difficulty of maintaining situational awareness as expected by the air traffic controller. We reformulate the optimization problem with two trajectory separation approaches including delaying flight departure time and allocating the new flight level subject to limited delay time of departure, limited changes of flight levels and fuel consumption constraints. We propose our solution to solve daily traffic demands in the regional French airspace. The resolution process uses the distributed metaheuristic algorithm to optimize aircraft trajectories in 4D environment with the objective of finding the optimal air traffic complexity. The experimental results shows the reduction of maximum complexity more than 95 % with average delay of 2.69 minutes. The optimized trajectories can save fuel more than 80000 kg. The proposed algorithm not only reduces the air traffic complexity but also maintain its distribution in traffic. The research results represent further steps towards taking other trajectory separations methods and aircraft trajectory uncertainties into account, developing our approach at the continental scale as well as adapting it in the pre-tactical and tactical planning phase.

Abstract

In a world where the population and many economies are expanding rapidly the demand for freight transport keeps rising accordingly. As more goods are transported by a growing number of freight vehicles, in particular trucks and sea vessels, their already considerable negative environmental impact also rises. Technology advances, but demand growth (partially) counteracts its positive impact on fuel consumption and emissions. In road transport, CO2-emissions keep rising, while emissions of NOx and PM10 have been reduced, at least in those countries where the most advanced engine technologies are used, although locally serious problems may remain. In areas where such technologies are not available, more freight transport means higher emissions and negative health effects. Sea shipping sees increasing emission levels overall. Maritime transport and trucking dominate intercontinental freight transport. Modernisation of railways and roads offers opportunities to reduce emissions by using rail for part of the journey. In a market setting, this means that transport providers have to redesign transport chains. Some have done this already, while others are increasingly interested. To assess the potential, the following main research question was addressed: Is it possible to reduce emissions of CO2, NOx and PM10 by replacing the maritime leg of a transport service by road and/or rail transport in the corridor Antwerp (Belgium) – Shanghai (China) without logistic penalties? Various combinations of trucking, sea and rail transport were fed into a simulation model to estimate the accompanying emissions and trip times. The"br/"new services offer a complex range of positive and negative impacts; hence governments should carefully consider their support. In a simulation study only a very stylised representation of these services can be modelled. This leads to an advice for a more in-depth study to include additional (technical, service and cost) data.

Abstract

Traffic source emission inventories for the rapidly growing West African urban cities are necessary for better characterization of local vehicle emissions released into the atmosphere of these cities. This study is based on local field measurements in Yopougon (Abidjan, Cô te d&rsquo Ivoire) in 2016 a site representative of anthropogenic activities in West African cities. The measurements provided data on vehicle type and age, traveling time, fuel type, and estimated amount of fuel consumption. The data revealed high traffic flow of personal cars on highways, boulevards, and backstreets, whereas high flows of intra-communal sedan taxis were observed on main and secondary roads. In addition, the highest daily fuel consumption value of 56 L· day&minus 1 was recorded for heavy vehicles, while the lowest value of 15 L· 1 was recorded for personal cars using gasoline. This study is important for the improvement of uncertainties related to the different databases used to estimate emissions either in national or international reports. This work provides useful information for future studies on urban air quality, climate, and health impact assessments in African cities. It may also be useful for policy makers to support implementation of emission reduction policies in West African cities. Document type: Article

Abstract

A two-motor power-split dedicated hybrid transmission (DHT) with two planetary gears is proposed for the applications of a hybrid electric vehicle (HEV) and plug-in HEV (PHEV). The proposed DHT can provide electronically controlled continuous variable transmission (eCVT) with two different gear ratios. One of two electric motors is employed to act as a speeder for splitting the input power of internal combustion engine (ICE) and the other acts as a torquer to assist ICE for boosting. Assisted by an electric motor, ICE can always be enhanced to operate at its efficient area for the benefits of fuel economy improvement. The maximum ICE torque is viable to be mechanically transmitted to vehicle wheels from standstill with two different gear ratios. This feature can help reduce the traction motor torque and power sizing significantly. The paper presents detailed theoretical analyses of the proposed eCVT. Comprehensive simulation demonstrations for a pickup truck HEV application are given to address that the vehicle fuel consumption can be considerably reduced without compromising acceleration performance. Document type: Article

Abstract

A deep neural network-based approach of energy demand modeling of electric vehicles (EV) is proposed in this paper. The model-based prediction of energy demand is based on driving cycle time series used as a model input, which is properly preprocessed and transformed into 1D or 2D static maps to serve as a static input to the neural network. Several deep feedforward neural network architectures are considered for this application along with different model input formats. Two energy demand models are derived, where the first one predicts the battery state-of-charge and fuel consumption at destination for an extended range electric vehicle, and the second one predicts the vehicle all-electric range. The models are validated based on a separate test dataset when compared to the one used in neural network training, and they are compared with the traditional response surface approach to illustrate effectiveness of the method proposed. Document type: Article

Abstract

n eco-driving prototype, named EcoNav, is developed with the aim of optimizing a vessel speed in order to reduce fuel consumption for a given itinerary. EcoNav is organized in several modules : - a 2D hydraulic model simulating the flow conditions (current speed and water depth) along the itinerary; - a ship resistance model calculating the thrust necessary to counteract the hydrodynamic forces ; - a fuel consumption model calculating the fuel consumption corresponding to the thrust input; - a non linear optimization algorithm calculating the optimal speed profile. In order to evaluate the fuel consumption of an inland vessel, a ship resistance numerical model is developed in the first part of this PhD. This 3D numerical model simulates the flow around an inland self-propelled vessel and evaluates the hydrodynamic forces acting on the hull. A RANS solver is coupled with a quasi-Newton approach to find the equilibrium position and calculate ship sinkage. This method is validated by comparing the results of numerical simulations to towing tank tests. The numerical results with and without sinkage are also compared to study the influence of sinkage on ship resistance and on the accuracy of the method. Additionally, some empirical models are investigated and compared with the accuracy of the numerical method. Finally, the numerical model is used to determine if channel with and water depth restriction contribute to the same amount of ship resistance increase for the same level of restriction. The results of that investigation give insight to whether channel restriction can be characterized by a unique parameter (for instance the blockage ratio) or two parameters to distinguish water depth and channel with effects. In the second part of this PhD, the numerical methods used in the speed optimization model are described and validated. The speed optimization model is then used to simulate a real case: the itinerary of the self-propelled ship Oural on river Seine, between Chatou and Poses (153 km). The optimized fuel consumption is compared with the non-optimized fuel consumption, based on AIS speed profile retrieved on this itinerary. The effects of the ship trajectory and travel duration on fuel consumption are also investigated. The results of those investigations showed that optimizing the ship speed lead to an average fuel saving of 8 % and that using an optimal track and including real time information such as lock availability and river traffic can lead to additional fuel savings.; Les travaux de cette thèse ont pour but de développer un prototype d’éco-pilote, nommé EcoNav, permettant d’optimiser la vitesse d’un bateau afin de réduire sa consommation de carburant. EcoNav est composé de plusieurs modules dont : un modèle hydraulique 2D simulant l’écoulement hydrodynamique (vitesse du courant et hauteur d’eau) le long du trajet du bateau; - un modèle de résistance à l’avancement servant à alimenter un modèle de prédiction de la consommation de carburant; - un algorithme d’optimisation permettant de trouver le profil optimal de vitesse. Afin de pouvoir estimer la consommation de carburant, un modèle numérique de la résistance à l’avancement en milieu confiné a été développé durant la première partie de cette thèse. Ce modèle numérique 3D simule l’écoulement du fluide autour du bateau et permet de calculer les forces agissant sur sa coque. La résolution des équations RANS est couplée avec un algorithme de quasi-Newton afin de trouver la position d’équilibre du bateau et calculer son enfoncement. Cette méthode est validée en comparant les résultats numériques avec des résultats expérimentaux issus d’essais en bassin de traction. L’influence de l’enfoncement sur la résistance à l’avancement et la précision de la méthode est étudiée en comparant les résultats numériques obtenus avec et sans enfoncement. La précision des modèles empiriques de prédiction de la résistance à l’avancement est également comparée à celle du modèle numérique. Enfin, le modèle numérique est utilisé afin de déterminer si le confinement en largeur ou en profondeur ont une influence identique sur l’augmentation de résistance à l’avancement. Les résultats de cette étude permettent d’établir si le confinement de la voie d’eau peut être caractérisé à l’aide d’un paramètre unique (coefficient de blocage par exemple) ou bien deux paramètres permettant de distinguer le confinement latéral et vertical. Dans la seconde partie de cette thèse, les méthodes numériques utilisées pour le modèle d’éco-pilote sont décrites et comparées afin de sélectionner celles qui sont le plus adaptées à chaque module. EcoNav est ensuite utilisé afin de modéliser un cas réel : celui du bateau automoteur Oural navigant sur la Seine entre Chatou et Poses (153 km). La consommation optimisée est comparée à la consommation non optimisée, calculée à partir des vitesses AIS observées sur le tronçon étudié. L’influence de la trajectoire du bateau et de son temps de parcours sur sa consommation sont également étudiés. Les résultats de ces investigations ont montré qu’optimiser la vitesse du bateau permet d’obtenir une réduction de la consommation de carburant de l’ordre de 8 % et qu’optimiser la trajectoire du bateau ainsi que prendre en compte des informations en temps réel (disponibilité des écluses, trafic sur le fleuve) peuvent permettre de réaliser des économies de carburant supplémentaires.