Operating cycle representations for road vehicles

This thesis discusses different ways to represent road transport operations mathematically. The intention is to make more realistic predictions of longitudinal performance measures for road vehicles, such as the CO2 emissions. It is argued that a driver and vehicle independent description of relevant transport operations increase the chance that a predicted measure later coincides with the actual measure from the vehicle in its real-world application. This allows for fair comparisons between vehicle designs and, by extension, effective product development. Three different levels of representation are introduced, each with its own purpose and application. The first representation, called the bird\u27s eye view, is a broad, high-level description with few details. It can be used to give a rough picture of the collection of all transport operations that a vehicle executes during its lifetime. It is primarily useful as a classification system to compare different applications and assess their similarity. The second representation, called the stochastic operating cycle (sOC) format, is a statistical, mid-level description with a moderate amount of detail. It can be used to give a comprehensive statistical picture of transport operations, either individually or as a collection. It is primarily useful to measure and reproduce variation in operating conditions, as it describes the physical properties of the road as stochastic processes subject to a hierarchical structure.The third representation, called the deterministic operating cycle (dOC) format, is a physical, low-level description with a great amount of detail. It describes individual operations and contains information about the road, the weather, the traffic and the mission. It is primarily useful as input to dynamic simulations of longitudinal vehicle dynamics.Furthermore, it is discussed how to build a modular, dynamic simulation model that can use data from the dOC format to predict energy usage. At the top level, the complete model has individual modules for the operating cycle, the driver and the vehicle. These share information only through the same interfaces as in reality but have no components in common otherwise and can therefore be modelled separately. Implementations are briefly presented for each module, after which the complete model is showcased in a numerical example.The thesis ends with a discussion, some conclusions, and an outlook on possible ways to continue

Intrinsic differences between backward and forward vehicle simulation models

Two common methods for predicting the energy usage in vehicles through mathematical\ua0simulation, the `backward\u27 and the `forward\u27 schemes, are discussed and compared in terms\ua0of what longitudinal vehicle behaviour they predict. In the backward scheme, the input driving\ua0cycle is initially assumed to be followed perfectly and therefore the vehicle speed is not a dynamic\ua0state. In the forward scheme, a driver model controls the vehicle in an attempt to follow the\ua0input driving cycle, and the vehicle speed is intrinsically a dynamic state. A theoretical study is\ua0made with a simple mathematical vehicle model, where it is shown that the two methods neither\ua0predict the same expected energy use nor energy variation. Next, the simulation model that isused for the CO2 rating of heavy-duty trucks in Europe, VECTO, is used as an example of the\ua0backward method, and an equivalent implementation in a forward scheme is attempted. Two\ua0numerical experiments are made with these models: a detailed study of the longitudinal vehicle\ua0behaviour on a reference mission; and a study of the predicted CO2 emissions on a family of\ua0stochastically generated missions. The conclusion is that the backward method is easier to use\ua0but the forward method has a greater potential to predict realistic behaviour

Contribution of dynamic capillary pressure to rainfall infiltration in thin homogeneous growth substrates

The use of green roofs to help mitigate storm water contributions to urban flooding has been gaining popularity but is hindered by the limited data on the performance of such roofs with regard to storm water runoff mitigation. The underlying issue stems from the inherent complexity of modeling subsurface multiphase flow. Modeling of this phenomena requires calculating the contributions of substrate microstructure characteristics, the influence of the wetting and non-wetting phases upon each other, and the effect of the microstructure on the wetting phase. Previously we have observed how the microstructure can affect detention, however the quantification of this relationship is still missing. In the present paper we present numerical simulations of wetting phase infiltration of a thin monodisperse packed bed in order to understand and quantify the impact of microstructure geometry on storm water infiltration of a green roof substrate. For a slightly hydrophilic case, (θ=82\ub0), we find that a dominant mechanism underlying this relationship is the microstructure-induced dynamic behavior of the capillary pressure. We determine that at larger packing ratios (ratio of packed bed depth to particle size), the influence of hydraulic head diminishes and behaves conversely for thinner layers, particularly when larger pores are present. Indeed, thin beds composed of large particles can exhibit high flow velocities that in turn affect the capillary pressure within the substrate. We observe that the capillary pressure can shift from negative values denoting capillary suction to positive ones which cause valve-like blocking effects on the flow; dependent upon the flow velocity as determined by the microstructure. In particular, we find that the capillary pressure depends on the value of the pore-scale gravity-induced flow velocity, quantified through a characteristic Capillary number. The provided quantification of this relationship can be invaluable from a design perspective to understand the behavior of capillary pressure of different substrates under a variety of flow rates prior to testing substrate candidates. In addition, a comparison of the behavior of the dynamic component of capillary pressure to other works is undertaken. Flow homogeneity is also found to be linked to the flow velocity, and consequently to the microstructure

On the impact of porous media microstructure on rainfall infiltration of thin homogeneous green roof growth substrates

Green roofs are considered an attractive alternative to standard storm water management methods; however one of the primary issues hindering their proliferation is the lack of data regarding their ability to retain and reduce storm water under a variety of climatic conditions. This lack of data is partly due to the complexity of physical processes involved, namely the heterogeneous microscopic behavior that characterize flows in unsaturated porous media. Such an anomalous behavior is difficult to predict a priori, especially in the presence of layered structures. This paper examines water infiltration of a green roof at the pore-scale with the aim to evaluate the effect of the porous microstructure in thin substrate layers. In such layers, the thickness of the medium and the particle size are within the same order of magnitude and the effect of the packing arrangement on the flow dynamics can be pronounced. In this study, three packing arrangements and two different hydraulic heads, analogous to extreme rainfall events typical of Scandinavia, are investigated by means of direct numerical simulations based on the lattice Boltzmann method. The results show that a wider variability of pore sizes in a thin medium can be linked directly to flow pathing preference and consequently less homogenized flow in the primary flow direction. This situation corresponds to intermittent flow behavior at the pore-scale level and reduced macroscopic infiltration rates. This observation unveils the possibility of designing innovative green roof growth substrates: by tuning the particle size and thickness of the layers composing the medium the desired green roof detention time can be attained

On Numerical Descriptions of Road Transport Missions

This thesis addresses some issues of current interest in energy consumption prediction through simulation. First, we review the situation for rating, regulation and legislation of CO$_2$-emissions for cars and heavy vehicles. We explain some of the problems with the current description (or lack thereof) of the road and surroundings for such tests, called driving cycles. With that in mind, two main research questions are formulated. The first we call the `representation problem\u27: what to include in a numerical description of a transport mission, and how to represent it mathematically? In answer, a proposal for a format is derived; the operating cycle-format. It is a physical description of the transport mission that consists of four parts: road, weather, traffic and mission, with the important property that it is independent of both driver and vehicle. Furthermore, it is explained how to build a simulation model capable of using the new mission description. Next, this is applied in a case-study of a real-world cargo transport, and the simulation results are used in a product development situation to improve energy consumption. In this specific case, a fuel consumption improvement of 16\% is achieved.The second question we call the `classification problem\u27: how should a mission executed in a specific region be labelled (i.e. described on a high level) depending on its characteristics? In answer, two classification methods are discussed: the Global Transport Application (GTA) and stochastic models. The basic structure of GTA is explained, and it is applied to the same log file that was used in the case-study. The principles of classification through stochastic models is described by explicit construction of such a model for topography. An example of how the methods can be applied in sales-to-order is made, by investigating how to best choose buffer size for a hybrid truck.Finally, a process for both efficient product development and sales-to-order is outlined, that combines the format proposal and the two classification methods. If the output of the process is used in an optimisation process, the result is a vehicle configuration tailored for the transport mission in question

Influence of hill-length on energy consumption for hybridized heavy transports in long-haul transports

Goods transports are big producers of CO2, i.e. consumers of energy. The conventional transport vehicles such as tractor-semitrailers can be replaced by long combination vehicles (LCVs). By doing so, fuel consumption will be reduced drastically, with up to 30%, mainly thanks to the reduced aerodynamic resistance per pay load mass and/or volume. Further reduction of CO2 improvements can be made by hybridization, if the road topography demands variable propulsion power due to up- and downhills. This gain is emphasized for heavier vehicles. So, hybridized LCVs are of special interest.When developing vehicles, or selecting vehicle for a certain transport, one needs to assume an operating cycle. To describe the operating cycle correctly is very important for this purpose. Traditionally, the magnitude of road grades is the only topography measure used to characterise the road. In this paper it is studied how an additional measure, hill length, influences these heavy hybridized LCVs. Together one can see these two measures as amplitude and wavelength.It is shown how energy saving varies for different types of roads (combinations of grade magnitude and hill-length) and different energy buffer sizes. Road topography is statistically generated for a good coverage of road types, but also examples of real roads are marked within these synthetic roads. The result can be combined with estimates of hybridization costs and conclusions can be drawn when it is beneficial to hybridize and with how large buffer. The main takeaways from the paper are that the potential energy savings for heavy LVCs due to hybridization are significant and that the hill-length is an important characteristic measure to include in operating cycle definitions

Influence of hill-length on energy consumption for hybridized heavy transports in long-haul transports

Goods transports are big producers of CO2, i.e. consumers of energy. The conventional transport vehicles such as tractor-semitrailers can be replaced by long combination vehicles (LCVs). By doing so, fuel consumption will be reduced drastically, with up to 30%, mainly thanks to the reduced aerodynamic resistance per pay load mass and/or volume. Further reduction of CO2 improvements can be made by hybridization, if the road topography demands variable propulsion power due to up- and downhills. This gain is emphasized for heavier vehicles. So, hybridized LCVs are of special interest.When developing vehicles, or selecting vehicle for a certain transport, one needs to assume an operating cycle. To describe the operating cycle correctly is very important for this purpose. Traditionally, the magnitude of road grades is the only topography measure used to characterise the road. In this paper it is studied how an additional measure, hill length, influences these heavy hybridized LCVs. Together one can see these two measures as amplitude and wavelength.It is shown how energy saving varies for different types of roads (combinations of grade magnitude and hill-length) and different energy buffer sizes. Road topography is statistically generated for a good coverage of road types, but also examples of real roads are marked within these synthetic roads. The result can be combined with estimates of hybridization costs and conclusions can be drawn when it is beneficial to hybridize and with how large buffer. The main takeaways from the paper are that the potential energy savings for heavy LVCs due to hybridization are significant and that the hill-length is an important characteristic measure to include in operating cycle definitions

En introduktion till dagvattenfl\uf6desmodellering i gr\uf6na tak

Gr\uf6na tak ses idag som ett alternativ f\uf6r dagvattenhantering i urbana omr\ue5den d\ue4r det lokala ledningsn\ue4tet inte har kapacitet nog att hantera framtidens regnm\ue4ngder. I detta projekt utvecklas modeller som syftar till att optimera och validera gr\uf6na tak s\ue5 att deras funktion kan anv\ue4ndas p\ue5 b\ue4sta s\ue4tt med st\uf6rst effekt. M\ue5let \ue4r att utveckla verktyg och riktlinjer f\uf6r hur gr\uf6na tak kan anv\ue4ndas

A statistical operating cycle description for prediction of road vehicles\u27 energy consumption

We propose a novel statistical description of the physical properties of road transport operations by using stochastic models arranged in a hierarchical structure. The description includes speed signs, stops, speed bumps, curvature, topography, road roughness and ground type, with a road type introduced at the top of the hierarchy to group characteristics that are often connected. Methods are described how to generate data on a form (the operating cycle format) that can be used in dynamic simulations to estimate energy usage and CO2 emissions. To showcase the behaviour of the description, two examples are presented using a modular vehicle model for a heavy-duty truck: a sensitivity study on impacts from changes in the environment, and a comparison study on a real goods transport operation with respect to energy usage. It is found that the stop intensity and topography amplitude have the greatest impact in the sensitivity study (8.3% and 9.5% respectively), and the comparison study implies that the statistical description is capable of capturing properties of the road that are significant for vehicular energy usage. Moreover, it is discussed how the statistical description can be used in a vehicle design process, and how the mean CO2 emissions and its variation can be estimated for a vehicle specification