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With the electrification of the automotive industry, electric motors have emerged as pivotal components. A profound understanding of their vibrational behaviour stands as a cornerstone for guaranteeing not only the optimal performance and reliability of vehicles in terms of noise, vibration, and harshness (NVH), but also the overall driving experience. The use of conventional finite element analysis (FEA) techniques for identification of the natural frequencies characteristics of electric motors often imposes significant computational loads, particularly when accurate material and geometrical properties and wider frequency ranges are considered. On the other hand, traditional reduced order vibroacoustic methodologies utilising simplified 2D representations, introduce several assumptions regarding boundary conditions and properties, leading to sacrifices in the accuracy of the results.

The primary function of automotive windscreen wipers is to remove excess water and debris to secure a clear view for the driver. Their successful operation is imperative to vehicle occupants’ safety. To avoid reliance on experimental testing there is a need to develop physics-based models that can quantify the effects of design-based decisions on automotive wipers. This work presents a suite of evaluative tools that can provide quantitative data on the effects of design decisions. We analyse the complex non-linear contact interaction between the wiper blade and the automotive screen using finite element analysis, assessing the impact of blade geometry on the contact distribution. The influence of the evolution of normal applied load by the wiper arm is also investigated as to how it impacts the contact distribution evolution. The dynamics of the blade are subsequently analysed using a multiple connected mass spring damper system.

GTDI engines are becoming more efficient, whether individually or part of a HEV (Hybrid Electric Vehicle) powertrain. For the latter, this efficiency manifests itself as increase in zero emissions vehicle mileage. An ideal device for energy recovery is a turbogenerator (TG), and, when placed downstream the conventional turbine, it has minimal impact on catalyst light-off and can be used as a bolt-on aftermarket device. A Ricardo WAVE model of a representative GTDI engine was adapted to include a TG (Turbogenerator) and TBV (Turbine Bypass Valve) with the TG in a mechanical turbocompounding configuration, calibrated using steady state mapping data. This was integrated into a co-simulation environment with a SISO (Single-Input, Single-Output) dynamic controller developed in SIMULINK for the actuator control (with BMEP, manifold air pressure and TG pressure ratio as the controlled variables).

In modern powertrains systems, sensors are critical elements for advanced control. The identification of sensing requirements for such highly nonlinear systems is technically challenging. To support the sensor selection process, this paper proposes a methodology to quantify the information gained from sensors used to control nonlinear dynamic systems using a dynamic probabilistic framework. This builds on previous work to design a Bayesian observer to deal with nonlinear systems. This was applied to a bimodal model of the SCR aftertreatment system. Despite correctly observing the bimodal distribution of the internal Ammonia-NOx Ratio (ANR) state, it could not distinguish which state is the true state. This causes issues for a control engineer who is less interested in how precise a measurement is and more interested in the location within control parameter space. Information regarding the dynamics of the systems is required to resolve the bimodality.

Considerations of surface contamination and airborne spray are becoming increasingly significant throughout the automotive design process. Advanced driver assistance systems, such as autonomous cruise control, are growing in popularity. These systems rely on external sensors, the performance of which may be impaired by both direct obstruction and spray. Existing experimental methods of assessing front-end surface contamination and wiper performance have typically utilised fixed spray-grids positioned upstream of the vehicle. The resulting spray is largely steady in nature, in contrast to the unsteady flow-field and tyre spray that would be produced by preceding vehicles. This paper presents the numerical analysis of the spray ejected downstream of a simplified automotive body. The continuous phase (air) is solved using a DDES-based approach coupled with a Lagrangian representation of the dispersed phase (water).

The replacement of the ICE engine with an electric motor has led to a significant reduction in vibration and noise. The characteristics of the electric motor as part of the powertrain still need consideration from an NVH perspective, as there are still two highly tonal components generating noise to the cabin, albeit at higher frequencies. The radial electromagnetic force causes a structural vibration on the casing which changes with motor speed and can be used to indicate vehicle speed. The current excitation causes a primarily tangential force on the poles of the motor at a specific frequency, but both are narrow band and can cause annoyance. The traditional approach to predicting the sound radiation of electric motors is usually based on finite element analysis (FEA). While this method has the capability to estimate the time response, it is computationally too demanding and does not allow for early investigations at systems level.

Sensor selection for the control of modern powertrains is a recognised technical challenge. The key question is which set of sensors is best suited for an effective control strategy? This paper addresses the question through probabilistic modelling and Bayesian analysis. By quantifying uncertainties in the model, the propagation of sensor information throughout the model can be observed. The specific example is an abstract model of the slip behaviour of Selective Catalytic Reduction (SCR) DeNOx aftertreatment systems. Due to the ambiguity of the sensor reading, linearization-based approaches including the Extended Kalman Filter, or the Unscented Kalman Filter are not successful in resolving this problem. The stochastic literature suggests approximating these nonlinear distributions using methods such as Markov Chain Monte Carlo (MCMC), which is able in principle to resolve bimodal or multimodal results.

Full hybrid electric vehicles are usually defined by their capability to drive in a fully electric mode, offering the advantage that they do not produce any emissions at the point of use. This is particularly important in built up areas, where localized emissions in the form of NOx and particulate matter may worsen health issues such as respiratory disease. However, high degrees of electrification also mean that waste heat from the internal combustion engine is often not available for heating the cabin and for maintaining the temperature of the powertrain and emissions control system. If not managed properly, this can result in increased fuel consumption, exhaust emissions, and reduced electric-only range at moderately high or low ambient temperatures negating many of the benefits of the electrification. This paper describes the development of a holistic, modular vehicle model designed for development of an integrated thermal energy management strategy.

Predicting Exterior Water Management is important for developing vehicles that meet customer expectations in adverse weather. Fluid film methods, with Lagrangian tracking, can provide spray and surface water simulations for complex vehicle geometries in on-road conditions. To cope with this complexity and provide practical engineering simulations, such methods rely on empirical sub-models to predict phenomena such as the film stripping from the surface. Experimental data to develop and validate such models is difficult to obtain therefore here a high-fidelity Coupled Level-set Volume of Fluid (CLSVOF) simulation is carried out. CLSVOF resolves the interface of the liquid in three dimensions; allowing direct simulation of film behaviour and interaction with the surrounding air. This is used to simulate a simplified wing-mirror, with air flow, on which water is introduced.

Multi-element front wings are essential in numerous motorsport series, such as Formula 1, for the generation of downforce and control of the onset flows to other surfaces and cooling systems. Rubber tyre debris from the soft compounds used in such series can become attached to the wing, reducing downforce, increasing drag and altering the wake characteristics of the wing. This work studies, through force balance and Particle Image Velocimetry (PIV) measurements, the effect a piece of debris has on an inverted double element wing in ground effect. The debris is modelled using a hard-setting putty and is located at different span and chord-wise positions around the wing. The sensitivity to location is studied and the effect on the wake analysed using PIV measurements. The largest effect on downforce was observed when the debris was located on the underside of the wing towards the endplates.

Modern control strategies for internal combustion engines use increasingly complex networks of sensors and actuators to measure different physical parameters. Often indirect measurements and estimation of variables, based off sensor data, are used in the closed loop control of the engine and its subsystems. Thus, sensor fusion techniques and virtual instrumentation have become more significant to the control strategy. With the large volumes of data produced by the increasing number of sensors, the analysis of sensor networks has become more important. Understanding the value of the information they contain and how well it is extracted through uncertainty quantification will also become essential to the development of control architecture. This paper proposes a methodology to quantify how valuable a sensor is relative to the architecture. By modelling the sensor network as a Bayesian network, Bayesian analysis and control metrics were used to assess the value of the sensor.

Lightly damped non-linear systems such as vehicular drivelines undergo a plethora of Noise, Vibration and Harshness (NVH) problems. The clonk phenomenon is one concern which occurs as the result of impulsive torque input in the form of sudden clutch actuation or throttle tip-in and back-out. The resulting impact of meshing gear pairs propagate structural waves down the driveline. With lightly damped thin-walled tubes having high modal density, elasto-acoustic coupling occurs. High frequency noise emission is of metallic nature and quite disconcerting to vehicle occupants as well as passers-by. It is perceived as structural failure and/or poor-quality build. Therefore, the occurrence of the phenomenon is a concern to vehicle manufacturers and progressively constitutes a warranty concern. This paper investigates the clonk phenomenon through use of a long-wheel base rear drive light truck test rig.

Surface contamination, or soiling, of the exterior of road vehicles can be unsightly, can reduce visibility and customer satisfaction, and, with the increasing application of surface-mounted sensors, can degrade the performance of advanced driver-assistance systems. Experimental methods of evaluating surface contamination are increasingly used in the product development process, but the results are generally subjective. The use of computational methods for predicting contamination makes objective measures possible, but comparable data from experiment is an important validation requirement. This article describes the development of an objective measure of surface contamination arising during experiments. A series of controlled experiments using ultraviolet (UV) dye-doped water are conducted to develop a robust methodology. This process is then applied to a simplified contamination test.

Cars in several motor sports series, such as Formula 1, make use of multi-element front wings to provide downforce. These wings also provide onset flows to other surfaces that generate downforce. These elements are highly loaded to maximise their performance and are generally operating close to stall. Rubber debris, often known as marbles, created from the high slip experienced by the soft compound tyres can become lodged in the multiple elements of a front wing. This will lead to a reduction in the effectiveness of the wing over the course of a race. This work will study the effect of such debris, both experimentally and numerically, on an inverted double element wing in ground effect at representative Reynolds numbers. The wing was mounted at two different ride heights above a fixed false-floor in the Loughborough University wind tunnel and the effect of debris blockage modelled by closing sections of the gap between elements with tape.

Sports Utility Vehicles (SUVs) typically have a blunt rear end shape (for design and practicality), however this is not beneficial for aerodynamic drag. Drag can be reduced by a number of passive and active methods such as tapering and blowing into the base. In an effort to combine these effects and to reduce the drag of a visually square geometry slots have been introduced in the upper side and roof trailing edges of a squareback geometry, to take air from the freestream and passively injects it into the base of the vehicle to effectively create a tapered body. This investigation has been conducted in the Loughborough University’s Large Wind Tunnel with the ¼ scale generic SUV model. The basic aerodynamic effect of a range of body tapers and straight slots have been assessed for 0° yaw. This includes force and pressure measurements for most configurations.

Efficiency and durability are key areas of research and development in modern racing drivetrains. Stringent regulations necessitate the need for components capable of operating under highly loaded conditions whilst being efficient and reliable. Downsizing, increasing the power-to-weight ratio and modification of gear teeth geometry to reduce friction are some of the actions undertaken to achieve these objectives. These approaches can however result in reduced structural integrity and component durability. Achieving a balance between system reliability and optimal efficiency requires detailed integrated multidisciplinary analyses, with the consideration of system dynamics, contact mechanics/tribology and stress analysis/structural integrity. This paper presents an analytical model to predict quasi-static contact power losses in lubricated spur gear sets operating under the Elastohydrodynamic regime of lubrication.

The TC48 project is developing a state-of-the-art, exceptionally low cost, 48V Plug-in hybrid electric (PHEV) demonstration drivetrain suitable for electrically powered urban driving, hybrid operation, and internal combustion engine powered high speed motoring. This paper explains the motivation for the project, and presents the layout options considered and the rationale by which these were reduced. The vehicle simulation model used to evaluate the layout options is described and discussed. The modelling work was used in order to support and justify the design choices made. The design of the vehicle's control systems is discussed, presenting simulation results. The physical embodiment of the design is not reported in this paper. The paper describes analysis of small vehicles in the marketplace, including aspects of range and cost, leading to the justification for the specification of the TC48 system.

This paper presents the findings from a numerical study of a gasoline direct injection engine flow using the Large Eddy Simulation (LES) modelling technique. The study is carried out over 30 successive engine cycles. The study illustrates how the more simple but robust Smagorinsky LES sub-grid scale turbulence model can be applied to a complex engine geometry with realistic engineering mesh size and computational expense whilst still meeting the filter width requirements to resolve the majority of large scale turbulent structures. Detailed description is provided here for the computational setup, including the initialisation strategy. The mesh is evaluated using a turbulence resolution parameter and shows the solution to generally resolve upwards of 80% of the turbulence kinetic energy.

This paper focuses on methods used to model vehicle surface contamination arising as a result of rear wake aerodynamics. Besides being unsightly, contamination, such as self-soiling from rear tyre spray, can degrade the performance of lighting, rear view cameras and obstruct visibility through windows. In order to accurately predict likely contamination patterns, it is necessary to consider the aerodynamics and multiphase spray processes together. This paper presents an experimental and numerical (CFD) investigation of the phenomenon. The experimental study investigates contamination with controlled conditions in a wind tunnel using a generic bluff body (the Windsor model.) Contamination is represented by a water spray located beneath the rear of the vehicle.

Side force has an influence on the behaviour of passenger cars in windy conditions. It increases approximately linearly with yaw angle over a significant range of yaw for almost all cars and the side force derivative, (the gradient of side force coefficient with yaw angle), is similar for vehicles of a given category and size. The shape factors and components which affect side force for different vehicle types are discussed. The dominant influence on side force, for most cars, however, is shown to be the vehicle height which is consistent with slender wing theory if the car and its mirror image are considered. This simple theory is shown to apply to 1-box and 2- box shapes, covering most MPVs, hatchbacks and SUVs, but does not adequately represent the side forces on notchback and fastback car shapes. Data from simple bodies is used to develop a modification to the basic theory, which is applied to these vehicle types.