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Faculty of Technology, Design and Environment
This paper presents the details of a Computational Fluid Dynamics methodology to accurately model the process of mixture preparation in modern Gasoline Direct Injection engines, with particular emphasis on liquid film as one of the main causes of Particulate Matter formation. The proposed modelling protocol, centred on the Bai-Onera approach of droplets-wall interaction and on multi-component surrogate fuel blend models, is validated against relevant published data and then applied to a modern small-capacity GDI engine, featuring centrally-mounted spray-guided injection system. The work covers a range of part-load, stoichiometric and theoretically-homogeneous operating conditions, for which experimental engine data and engine-out Particle Number measurements were available. The results, based on the parametric variation of start of injection timing and injection pressure, demonstrate how both fuel mal-distribution and liquid film retained at spark timing, may contribute to PN emissions, whilst their relative importance vary depending on operating conditions and engine control strategy. Control of PN emissions and compliance with future, more stringent regulations remain large challenges for the engine industry. Renewed and disruptive approaches, which also consider the sustainability of the sector, appear to be essential. This work, developed using Siemens Simcenter CFD software as part of the Ford-led APC6 DYNAMO project, aims to contribute to the development of a reliable and cost-effective digital toolset, which supports engine development and diagnostics through a more fundamental assessment of engine operation and emissions formation.
An experimental investigation was carried out to investigate Particulate Number (PN) emissions from a modern, small-capacity Gasoline Direct Injection (GDI) engine. The first part of the study focused on improving measurement repeatability using the Cambustion DMS-500 device. Results showed that sampling near the exhaust valve – while dampening the pressure oscillations in the sampling line – can significantly improve the repeatability. It was also found that uncontrolled phenomena such as deposition in the exhaust system from earlier engine operation can undermine the accuracy of measurements taken at tailpipe level. The second part of the work investigated PN emissions from three types of gasoline fuel, Pump-grade, Performance and Reference. Fuel chemical composition was found to have an appreciable impact on PN, but the magnitude of this effect differs in various operating points, being more pronounced at higher engine load. The Reference fuel was found to have the lowest PN emission tendency, conceivably because of its lower aromatics, olefins and heavy hydrocarbons content. A sweep of operating parameters showed that higher injection pressure reduces PN, but the extent of the reduction depends on fuel physical properties such as volatility.
The ability to model tyre dynamics precisely is often one of the most critical elements for realistic vehicle dynamics control and handling investigations. The industry-standard empirical models are able to predict the important tyre forces accurately over a short range of vehicle operating conditions, which is often restricted to the operating conditions experienced during the tyre testing process. In this paper, an alternative and practical method to model Formula SAE tyres has been proposed and studied in a series of possible running scenarios. A simple, analytically solved brush-type tyre model is considered for the physical part with the introduction of a novel approach for defining the contact length formulation that incorporates the influence of inflation pressure, camber angle and velocity, while a set of ordinary differential equations are employed to predict the thermal behaviour of the tyre model, which are mostly based on an already-existing method that has not been experimentally validated before. The resulting tyre models provide realistic and informative behaviour of the tyre, which has the ability to consider the majority of the typical operating conditions experienced on a Formula SAE vehicle. The performance of the proposed tyre models is compared against experimental tyre test data, which shows good agreement and indicates that the tyre models have the ability to give realistic predictions of the tyre forces and thermal behaviour in the case of thermal tyre model. Furthermore, the temperature-dependent tyre model has been incorporated into a two-track model of Oxford Brookes Racing’s Formula SAE vehicle to study the effectiveness of the tyre model during transient handling simulation. The resulting simulations suggest that the proposed tyre model has the ability to represent realistic operating conditions of tyres, and also that tyre temperatures influence the vehicle dynamic behaviour significantly during on-limit scenarios.
Electric vehicles (EVs) are increasingly regarded as the way forward to deliver a much-needed improvement in the transport sector's sustainability profile, and the UK is embarking on a major transition towards them. While previous studies focused mainly on greenhouse gas (GHG) emissions, this article assesses the extent to which EVs may contribute to reducing the UK's dependence on (mostly imported) non-renewable primary energy. The study combines a life-cycle model of a compact battery electric vehicle (BEV) with a prospective energy analysis of a range of electricity supply alternatives for the vehicle's use phase. The key metric analysed is the non-renewable cumulative energy demand (nr-CED). Results show that, already under current conditions, the nr-CED of a compact BEV in the UK is lower by approximately 34% with respect to that of an otherwise similar internal combustion engine vehicle (ICEV). Such reduction is then expected to improve further under all future scenarios, indicating that a transition to EVs is indeed a recommendable option to reduce the UK's demand for non-renewable energy, especially if this is accompanied by a shift to a more renewable electric grid.
A complete and fully consistent LCA-based comparison of a range of lightweighting options for compact passenger vehicles is presented and discussed, using advanced lightweight materials (Al, Mg and carbon fibre composites), and including all life cycle stages and a number of alternative end-of-life scenarios. Results underline the importance of expanding the analysis beyond the use phase, and point to maximum achievable reductions of environmental impact of approximately 7% in most impact categories. In particular, lightweighting strategies based on the use of aluminium were found to be the most robust and consistent in terms of reducing the environmental impacts (with the notable exception of a relatively high potential toxicity). The benefits of using magnesium instead appear to be less clear-cut, and strongly depend on achieving the complete phase-out of SF6 in the metal production process, as well as the establishment of a separate close-loop recycling scheme. Finally, the use of carbon fibre composites leads to similar environmental benefits to those achieved by using Al, albeit generally at a higher economic cost.
A reduced order model is developed for low frequency, fully coupled, undamped and constantly damped structural acoustic analysis of interior cavities, backed by flexible structural systems. The reduced order model is obtained by applying a Galerkin projection of the coupled system matrices, from a higher dimensional subspace to a lower dimensional subspace, whilst preserving some essential properties of the coupled system. The basis vectors for projection are computed efficiently using the Arnoldi algorithm, which generates an orthogonal basis for the Krylov subspace containing moments of the original higher dimensional system. A simply supported steel plate, backed by a rigid walled cavity is used as a computational test case , and the computational gains and the accuracy obtained via implicit moment matching are compared with the direct method in ANSYS. Further, a reciprocity check is performed on the coupled system by exciting the coupled system using unit structural and acoustic excitations. It is shown that the reduced order modelling technique results in a very significant reduction in simulation time, while maintaining the desired accuracy of the state variables (displacements and pressures) under investigation.
In this work, a reduced order multidisciplinary optimization procedure is developed to enable efficient, low frequency, undamped and damped, fully coupled, structural-acoustic optimization of interior cavities backed by flexible structural systems. This new method does not require the solution of traditional eigen value based problems to reduce computational time during optimization, but are instead based on computation of Arnoldi vectors belonging to the induced Krylov Subspaces. The key idea of constructing such a reduced order model is to remove the uncontrollable, unobservable and weakly controllable, observable parts without affecting the noise transfer function of the coupled system. In a unified approach, the validity of the optimization framework is demonstrated on a constrained composite plate/prism cavity coupled system. For the fully coupled, vibro-acoustic, unconstrained optimization problem, the design variables take the form of stacking sequences of a composite structure enclosing the acoustic cavity. The goal of the optimization is to reduce sound pressure levels at the driver" s ear location. It is shown that by incorporating the reduced order modelling procedure within the optimization framework, a significant reduction in computational time can be obtained, without any loss of accuracy-”when compared to the direct method. The method could prove as a valuable tool to analyze and optimize complex coupled structural-acoustic systems, where, in addition to fast analysis, a fine frequency resolution is often required.
Recent developments in measurement techniques enabled researchers to measure ultra-fine particulates of nano-scale range and provided more evidence that the smaller particulates typically emitted from gasoline engines may have more severe impacts on human respiratory system than the bigger particulates from diesel engines. The knowledge of the characteristics of particulates from gasoline engines, especially, the effect of fuel borne additives is sparse. This work presents the findings from a study into the effect of aftermarket additives on nano-scale particulates. Four commercially available fuel borne additives used in gasoline engines mainly by private vehicle owners in the United Kingdom were selected for this study. The combustion and emission performance of the additive fuels were compared against that of commercially available gasoline fuel using a 4-stroke, throttle body injected gasoline engine. The engine-out particulates in the range of 5 to 1000 nm were measured using a fast particle spectrometer along with the in-cylinder pressure trace. The work identified that the total particulate count for certain types of additives are two orders of magnitude greater than that of base fuel at the same engine operating condition. In contrast, other types of additives produce significantly lower levels of particulate when compared with the base fuel especially in the range of 10 nm size.