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The introduction of drive-by-wire systems into modern vehicles has generated new challenges for the designers of embedded systems. These systems, based primarily on microcontrollers, need to achieve very high levels of reliability and availability, but also have to satisfy the strict cost and packaging constraints of the automotive industry. Advances in VLSI technology have allowed the development of single-chip systems, but have also increased the rate of intermittent and transient faults that come as a result of the continuous shrinkage of the CMOS process feature size. This paper presents a low-cost, fault-tolerant system-on-chip architecture suitable for drive-by-wire and other safety-related applications, based on a triple-modular-redundancy configuration at the processor execution pipeline level.

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.

The COMponent Based Paradigm for AGile Automation (COMPAG) provides a component-based solution to engine production-line machine control systems. The traditional PLC system is replaced with a distributed control network containing intelligent nodes comprising locally controlled actuators and sensors. The Process Definition Environment provides support for the specification, configuration, and maintenance of the machine control application and facilitates both the initial design and maintenance stages of the lifecycle by describing the control logic as a set of consistent timing and state transition diagrams commonly used in the initial design stages.

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.

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.

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.

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.

Particulate number (PN) standards in the current ‘Euro 6’ European emissions standards pose a challenge for engine designers and calibrators during the warm-up phases of cold direct injection spark ignition (DISI) engines. To achieve catalyst light-off in the shortest time, engine strategies are often employed which inherently use more fuel to attain higher exhaust temperatures. This can lead to the generation of locally fuel-rich regions within the combustion chamber and the emission of particulates. This investigation analyses the combustion structures during the transient start-up phase of an optical DISI engine. High-speed, colour 9 kHz imaging was used to investigate five important operating points of an engine start-up strategy whilst simultaneously recording in-cylinder pressure.

Closed-loop electronic control is a proven and efficient way to optimize spark ignition engine performance and to control pollutant emissions. In-cylinder pressure sensors provide accurate information on the quality of combustion. The conductivity of combustion flames can alternatively be used as a measure of combustion quality through ion-current measurements. In this paper, combustion diagnostics through ion-current sensing are studied. A single cylinder research engine was used to investigate the effects of misfire, ignition timing, air to fuel ratio, compression ratio, speed and load on the ion-current signal. The ion-current signal was obtained via one, or both, of two additional, remote in-cylinder ion sensors (rather than by via the firing spark plug, as is usually the case). The ion-current signals obtained from a single remote sensor, and then the two remote sensors are compared.

Model-based calibration (MBC) is a systematic method to calibrate an engine control unit (ECU) system. Due to the working principle of MBC, it is only being used for steady-state systems (time independent models). This limits the use of MBC; because an ECU contains statistical and dynamical systems. Due to the limitations of MBC, dynamical systems require manual tuning which may be time-consuming. With the increasing popularity in hybrid and electrical vehicle systems, most of them rely on dynamical systems. Therefore, MBC is about to be superseded by manual parameterization methods. Remarkably, MBC is not limited to the steady state systems. It can be achieved by separating the time factor of a system and extracting the statistical data from a time series measurement. Typically, MBC model is conceived as the representation of a system plant (i.e.: air path, fuel path, mean value engine model). As a matter of fact, MBC model is not limited to identification of system plant.

Variable valve actuation in heavy duty diesel engines is not well documented, because of diesel engine feature, such as, unthrottled air handling, which gives little room to improve pumping loss; a very high compression ratio, which makes the clearance between the piston and valve small at the top dead center. In order to avoid strike the piston while maximizing the valve movement scope, different strategies are adopted in this paper: (1) While exhaust valve closing is fixed, exhaust valve opening is changed; (2) While exhaust valve closing is fixed, late exhaust valve opening: (3) While inlet valve opening is fixed, inlet valve closing is changed; (4) Delayed Inlet valve and exhaust valve openings and closings; (5) Changing exhaust valve timing; (6) changing inlet valve timing; (7) Changing both inlet and exhaust timing, will be used.

The goal of grid friendly charging is to avoid putting additional load on the electricity grid when it is heavily loaded already, and to reduce the cost of charging to the consumer. In a smart metering system, Day Ahead tariff (DA) prices are announced in advance for the next day. This information can be used for a simple optimization control, to select to charge at cheapest times. However, the balance of supply and demand is not fully known in advance and the Real-Time Prices (RTP) are therefore likely to be different at times. There is always a risk of a sudden price change, hence adding a stochastic element to the optimization in turn requiring dynamic control to achieve optimal time selection. A stochastic dynamic program (SDP) controller which takes this problem into account has been made and proven by simulation in a previous paper.

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).

For a spark-ignition engine, the parasitic loss suffered as a result of conventional throttling has long been recognised as a major reason for poor part-load fuel efficiency. While lean, stratified charge, operation addresses this issue, exhaust gas aftertreatment is more challenging compared with homogeneous operation and three-way catalyst after-treatment. This paper adopts a different approach: homogeneous charge direct injection (DI) operation with variable valve actuations which reduce throttling losses. In particular, low-lift and early inlet valve closing (EIVC) strategies are investigated. Results from a thermodynamic single cylinder engine are presented that quantify the effect of two low-lift camshafts and one standard high-lift camshaft operating EIVC strategies at four engine running conditions; both, two- and single-inlet valve operation were investigated. Tests were conducted for both port and DI fuelling, under stoichiometric conditions.

Energy management of battery electric vehicle (BEV) is a very important and complex multi-system optimisation problem. The thermal energy management of a BEV plays a crucial role in consistent efficiency and performance of vehicle in all weather conditions. But in order to manage the thermal management, it requires a significant number of temperature sensors throughout the car including high voltage batteries, thus increasing the cost, complexity and weight of the car. Virtual sensors can replace physical sensors with a data-driven, physical relation-driven or machine learning-based prediction approach. This paper presents a framework for the development of a neural network virtual sensor using a thermal system hardware-in-the-loop test rig as the target system. The various neural network topologies, including RNN, LSTM, GRU, and CNN, are evaluated to determine the most effective approach.

Engine electrification is a critical technology in the promotion of engine fuel efficiency, among which the electrified turbocharger is regarded as the promising solution in engine downsizing. By installing electrical devices on the turbocharger, the excess energy can be captured, stored, and re-used. The electrified turbocharger consists of a variable geometry turbocharger (VGT) and an electric motor (EM) within the turbocharger bearing housing, where the EM is capable in bi-directional power transfer. The VGT, EM, and exhaust gas recirculation (EGR) valve all impact the dynamics of air path. In this paper, the dynamics in an electrified turbocharged diesel engine (ETDE), especially the couplings between different loops in the air path is analyzed. Furthermore, an explicit principle in selecting control variables is proposed. Based on the analysis, a model-based multi-input multi-output (MIMO) decoupling controller is designed to regulate the air path dynamics.

The motivation for this paper is to predict the flow of water over exterior surfaces of road vehicles. We present simulations of liquid flows on solid surfaces under the influence of gravity with and without the addition of aerodynamic forces on the liquid. This is done using an implementation of a Coupled Level Set Volume of Fluid method (CLSVOF) multiphase approach implemented in the open source OpenFOAM CFD code. This is a high fidelity interface-resolving method that solves for the velocity field in both phases without restrictions on the flow regime. In the current paper the suitability of the approach to Exterior Water Management (EWM) is demonstrated using the representative test cases of a continuous liquid rivulet flowing along an inclined surface with a channel located downstream perpendicular to the oncoming flow.

Proton exchange membrane fuel cell (PEMFC) provides a promising future low carbon automotive powertrain solution. The catalyst layer (CL) is its core component which directly influences the output performance. PEMFC performance can be greatly improved by the effective optimization of CL composition. This work demonstrates a deep optimization of CL composition for improving the PEMFC performance, including the platinum (Pt) loading, Pt percentage of carbon-supported Pt and ionomer to carbon ratio of the anode and the cathode,. The simulation results by a PEMFC three-dimensional (3D) computation fluid dynamics (CFD) model coupled with the CL agglomerate model is used to train the artificial neural network (ANN) which can efficiently predict the current density under different CL composition. Squared correlation coefficient (R-square) and mean percentage error in the training set and validation set are 0.9867, 0.2635% and 0.9543, 1.1275%, respectively.

Fuel cell hybrid systems have emerged rapidly in efforts to reduce emissions. The success of these systems mainly depends on implementation of suitable control architectures. This paper presents a control system design for a novel fuel cell - IC Engine hybrid power system. Control oriented models of the system components are developed and integrated. Based on the simulation results of the system model, the control variables are identified. The main objective for the control design is to manage fuel, air and exhaust flows in a way to deliver the required load on the system within local constraints. The controller developed for regulating flows in the system is based on model predictive control theory. The performance of the overall control system is assessed through simulations on a nonlinear dynamic model.

Exhaust Gas Recirculation (EGR) is one of several technologies that are being investigated to deliver future legislative emissions targets for diesel engines. Its application requires a detailed understanding of the thermo-fluidic processes within the engine's air system. A validated Computational Fluid Dynamics (CFD) process is one way of providing this understanding. This paper describes a CFD process to analyse unsteady manifold flows and mixing fields in the presence of realistic levels of EGR. The validation methodology was drawn from the American Institute of Aeronautics and Astronautics (AIAA) and divides the problem into smaller elemental problems. Detailed knowledge about these elemental problems is easily attainable, reducing the requirement for a large number of complex validation runs. The final validated process was compared to flow visualization and particle image velocimetry (PIV) data collected from a motored engine.