Search Results

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.

A large contribution to the aerodynamic drag of a vehicle (30%(1) or more depending on vehicle shape) arises from the low base pressure in the wake region, especially on square-back configurations. A degree of base pressure recovery can be achieved through careful shape optimization, but the flow structures and mechanisms within the wake that cause these base pressure changes are not well understood. A more complete understanding of these mechanisms may provide opportunities for further drag reductions from both passive shape changes and in the future through the use of active flow control technologies. In this work surprisingly large changes in drag and lift coefficients of a square-back style vehicle have been measured as a result of physically small passive modifications. Tests were performed at quarter scale using a simplified vehicle model (Windsor Model) and at full scale using an MPV. The full scale vehicle was tested with and without a flat floor.

Traditionally, university research in engine technology has been focused on fundamental engine phenomena. Increasingly however, research topics are developing in the form of systems issues. Examples include air and exhaust gas recirculation (EGR) management, after-treatment systems, engine cooling, hybrid systems and energy recovery. This trend leads to the need for engine research to be conducted using currently available products and components that are re-configured or incrementally improved to support a particular research investigation. A production engine will include an electronic control unit (ECU) that must be understood and utilised or simply removed and circumvented. In general the intellectual property (IP) limitations places on ECUs by their suppliers mean that they cannot be used. The supplier of the ECU is usually unable to reveal any detail of the implementation. As a consequence any research using production hardware is seriously disadvantaged from the beginning.

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.

This paper presents a control system design strategy for a novel fuel cell - internal combustion engine hybrid power system. Dynamic control oriented models of the system components are developed. The transient behavior of the system components is investigated in order to determine control parameters and set-points. The analysis presented here is the first step towards development of a controller for this complex system. The results indicate various possibilities for control design and development. A control strategy is discussed to achieve system performance optimization.

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.

A multi-zone Controlled Auto Ignition (CAI) model for simulating the combustion and emissions has been developed and reported in this paper. The model takes into account the effects of the boundary layer, crevice volume, and blowby. In order to investigate the influences of in-cylinder inhomogeneity, the main cylinder chamber has been divided into multiple core zones with varying temperature and composition. Mass and energy transfer between neighbouring zones were modeled. A reduced chemical kinetic mechanism was implemented in each zone to simulate the CAI combustion chemistry and emission formation. An in-house code, the LUCKS (Loughborough University Chemical Kinetics Simulation), was employed to solve the coupled differential equations of the system. The model was validated against experimental results at various Internal Exhaust Gas Recirculation (IEGR) levels and was then used to analyze the thermal and chemical effect of the IEGR on the CAI combustion.

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.

This paper reports on an investigation into the potential for a thermoelectric generator (TEG) to improve the fuel economy of a mild hybrid vehicle. A simulation model of a parallel hybrid vehicle equipped with a TEG in the exhaust system is presented. This model is made up by three sub-models: a parallel hybrid vehicle model, an exhaust model and a TEG model. The model is based on a quasi-static approach, which runs a fast and simple estimation of the fuel consumption and CO2 emissions. The model is validated against both experimental and published data. Using this model, the annual fuel saving, CO2 reduction and net present value (NPV) of the TEG’s life time fuel saving are all investigated. The model is also used as a flexible tool for analysis of the sensitivity of vehicle fuel consumption to the TEG design parameters. The analysis results give an effective basis for optimization of the TEG design.

The application of state-of-art thermoelectric generator (TEG) in automotive engine has potential to reduce more than 2% fuel consumption and hence the CO2 emissions. This figure is expected to be increased to 5%~10% in the near future when new thermoelectric material with higher properties is fabricated. However, in order to maximize the TEG output power, there are a few issues need to be considered in the design stage such as the number of modules, the connection of modules, the geometry of the thermoelectric module, the DC-DC converter circuit, the geometry of the heat exchanger especially the hot side heat exchanger etc. These issues can only be investigated via a proper TEG model. The authors introduced four ways of TEG modelling which in the increasing complexity order are MATLB function based model, MATLAB Simscape based Simulink model, GT-power TEG model and CFD STAR-CCM+ model. Both Simscape model and GT-Power model have intrinsic dynamic model performance.

The paper presents a measurement methodology which combines a fine-wire thermocouple with input reconstruction in order to measure crank angle resolved temperature in an engine air-intake system. Thermocouples that are of practical use in engine experiments tend to have a large time constant which affects measurement accuracy during rapid temperature transients. Input reconstruction methods have previously been applied to thermocouples but have not been specifically used in combination with an ultra-thin uninsulated wire thermocouple to investigate cyclic intake temperature behavior. Accurate measurement results are of interest to improve the validity of many crank-angle resolved engine models. An unshielded thermocouple sensor has been developed which is rigid enough to withstand the aerodynamic forces of the intake air.

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.

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.

This literature review considers the problem of finding a suitable configuration of sensors and actuators for the control of an internal combustion engine. It takes a look at the methods, algorithms, processes, metrics, applications, research groups and patents relevant for this topic. Several formal metric have been proposed, but practical use remains limited. Maximal information criteria are theoretically optimal for selecting sensors, but hard to apply to a system as complex and nonlinear as an engine. Thus, we reviewed methods applied to neighboring fields including nonlinear systems and non-minimal phase systems. Furthermore, the closed loop nature of control means that information is not the only consideration, and speed, stability and robustness have to be considered. The optimal use of sensor information also requires the use of models, observers, state estimators or virtual sensors, and practical acceptance of these remains limited.

Thermoelectric generator has very quickly become a hot research topic in the last five years because its broad application area and very attractive features such as no moving parts, low maintenance, variety of thermoelectric materials that total together cover a wide temperature range. The biggest disadvantage of the thermoelectric generator is its low conversion efficiency. So that when design and manufacture a thermoelectric generator for exhaust waste heat recovery from an automotive engine, the benefit of fuel consumption from applying a thermoelectric generator would be very sensitive to the weight, the dimensions, the cost and the practical conversion efficiency. Additionally, the exhaust gas conditions vary with the change of engine operating point. This creates a big challenge for the design of the hot side heat exchanger in terms of optimizing the electrical output of the thermoelectric generator during an engine transient cycle.

This research introduces a new, novel approach to reverse flow particulate filter regeneration enabled by rapidly pulsed electric discharges. The discharges physically dislodge particulate matter (PM) from the filter substrate and allow a very low reverse air flow to transport it to a soot handling system. The system is operable independent of filter temperature, does not expose the filter to high thermal stresses or temperatures, has no apparent upper limit for filter PM-mass level (regeneration of a filter up to 17 g/L has been demonstrated), and does not require any catalyst. The system is inherently scalable allowing application to monolithic filters of any size or shape and can be tailored to suit specific application requirements such as limits on maximum regeneration time or power consumption. For example a light duty application would require as little as 200-500W electrical power to regenerate a filter in less than ten minutes (i.e. passenger car GPF or DPF).

Models of hybrid powertrains are used to establish the best combination of conventional engine power and electric motor power for the current driving situation. The model is characteristic for having two control inputs and one output constraint: the total torque should be equal to the torque requested by the driver. To eliminate the constraint, several alternative formulations are used, considering engine power or motor power or even the ratio between them as a single control input. From this input and the constraint, both power levels can be deduced. There are different popular choices for this one control input. This paper presents a novel model based on an input linearizing transformation. It is demonstrably superior to alternative model forms, in that the core dynamics of the model (battery state of energy) are linear, and the non-linearities of the model are pushed into the inputs and outputs in a Wiener/Hammerstein form.

Hybrid technologies enable the reduction of noxious tailpipe emissions and conformance with ever-decreasing allowable homologation limits. The complexity of the hybrid powertrain technology leads to an energy management problem with multiple energy sinks and sources comprising the system resulting in a high-dimensional time dependent problem for which many solutions have been proposed. Methods that rely on accurate predictions of potential vehicle operations are demonstrably more optimal when compared to rule-based methodology [1]. In this paper, a previously proposed energy management strategy based on an offline optimization using dynamic programming is investigated. This is then coupled with an online model predictive control strategy to follow the predetermined optimal battery state of charge trajectory prescribed by the dynamic program.

Vehicle emissions and fuel economy in real-world driving conditions are currently under considerable scrutiny. Key to achieving optimum performance for a given hardware set and control scheme is a calibration that optimizes controller gains such that inputs are scheduled over the operating space to minimize emissions and maximize fuel economy. Generating a suitable calibration requires data that is both precise and accurate, this data is used to generate models that are deployed as part of the calibration optimization process. This paper evaluates the repeatability of typical steady-state measurements used for calibration of engine controllers that will ultimately determine vehicle level emissions for homologation include Real Driving Emissions (RDE). Stabilization requirements as indicated by three different measurements are evaluated and shown to be different within the same experiment, depending on the metric used.