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Natural gas as an alternative fuel offers the potential of clean combustion and emits relatively low CO2 emissions. The main constitute of natural gas is methane. Historically, the slow burning speed of methane has been a major concern for automotive applications. Literature on experimental methane-gasoline Dual Fuel (DF) studies on research engines showed that the DF strategy is improving methane combustion, leading to an enhanced initial establishment of burning speed even compared to that of gasoline. The mechanism of such an effect remains unclear. In the present study, pure methane (representing natural gas) and PRF95 (representing gasoline) were supplied to a constant volume combustion vessel to produce a DF air mixture. Methane was added to PRF95 in three different energy ratios 25%, 50% and 75%. Experiments have been conducted at equivalence ratios of 0.8, 1, 1.2, initial pressures of 2.5, 5 and 10 bar and a temperature of 373K.

Particulate Matter (PM) emissions reduction is an imminent challenge for Direct Injection Spark Ignition (DISI) engine designers due to the introduction of Particulate Number (PN) standards in the proposed Euro 6 emissions legislation aimed at delivering the next phase of air quality improvements. An understanding of how the formation of combustion-derived nanoparticulates in engines is affected by the engine operating temperature is important for air quality improvement and will influence future engine design and control strategies. This investigation has examined the effect on combustion and PM formation when reducing the engine operating temperature to -7°C. A DISI single-cylinder optical research engine was modified to simulate a range of operating temperatures down to the proposed -7°C.

In this work, cyclic combustion simulations of a spark ignition engine were performed using the Large Eddy Simulation techniques. The KIVA-4 RANS code was modified to incorporate the LES capability. The flame surface density approach was implemented to model the combustion process. Ignition and flame kernel models were also developed to simulate the early stage of flame propagation. A dynamic procedure was formulated where all model coefficients were locally evaluated using the resolved and test filtered flow properties during the fully developed phase of combustion. A test filtering technique was adopted to use in wall bounded systems. The developed methodology was then applied to simulate the combustion and associated unsteady effects in a spark ignition engine. The implementation was validated using the experimental data taken from the same engine.

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.

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.

The deactivation of one or more cylinders in internal combustion engines has long been established in literature as a means of reducing engine pumping losses and thereby improving brake specific fuel consumption. As down-sizing and down-speeding of modern engines becomes more extreme, drivability issues associated with mode transition become more acute and need to be managed within a suitable calibration framework. This paper presents methodology by which a calibration may be deduced for optimal mode-transitioning in respect of minimising the torque disturbance as cylinders are deactivated and re-activated. At the outset of this study a physics based engine model is used to investigate the key parameters that influence the transition. Having understood these, experiments are designed to establish the level of mode transition disturbance using quantitative statistical indicators such that the cost function may be defined and an optimisation undertaken.

The injection timing of a Diesel internal combustion engine typically follows a prescribed sequence depending on the operating condition using open loop control. Due to advances in sensors and digital electronics it is now possible to implement closed loop control based on in cylinder pressure values. Typically this control action is slow, and it may take several cycles or at least one cycle (cycle-to-cycle control). Using high speed sensors, it becomes technically possible to measure pressure deviations and correct them within the same cycle (intra-cycle control). For example the in cylinder pressure after the pilot inject can be measured, and the timing of the main injection can be adjusted in timing and duration to compensate any deviations in pressure from the expected reference value. This level of control can significantly reduce the deviations between cycles and cylinders, and it can also improve the transient behavior of the engine.

Piston compression rings are thin, incomplete circular structures which are subject to complex motions during a typical 4-stroke internal combustion engine cycle. Ring dynamics comprises its inertial motion relative to the piston, within the confine of its seating groove. There are also elastodynamic modes, such as the ring in-plane motions. A number of modes can be excited, dependent on the net applied force. The latter includes the ring tension and cylinder pressure loading, both of which act outwards on the ring and conform it to the cylinder bore. There is also the radial inward force as the result of ring-bore conjunctional pressure (i.e. contact force). Under transient conditions, the inward and outward forces do not equilibrate, resulting in the small inertial radial motion of the ring.

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.

For diesel engines, fuel path control plays a key role in achieving optimal emissions and fuel economy performance. There are several fuel path parameters that strongly affect the engine performance by changing the combustion process, by modifying for example, start of injection and fuel rail pressure. This is a multi-input multi-output problem. Linear Model Predictive Control (MPC) is a good approach for such a system with optimal solution. However, fuel path has fast dynamics. On-line optimisation MPC is not the good choice to cope with such fast dynamics. Explicit MPC uses off-line optimisation, therefore, it can be used to control the system with fast dynamics.

Low temperature combustion (LTC) in diesel engines offers attractive benefits through simultaneous reduction of nitrogen oxides and soot. However, it is known that the in-cylinder conditions typical of LTC operation tend to produce high emissions of unburned hydrocarbons (UHC) and carbon monoxide (CO), reducing combustion efficiency. The present study develops from the hypothesis that this characteristic poor combustion efficiency is due to in-cylinder mixture preparation strategies that are non-optimally matched to the requirements of the LTC combustion mode. In this work, the effects of three key fuel path parameters - injection fuel quantity ratio, dwell and injection timing - on CO and HC emissions were examined using a Central Composite Design (CCD) Design of Experiments (DOE) method.

The control of Homogeneous Charge Compression Ignition (HCCI) (also known as Controlled Auto Ignition (CAI)) has been a major research topic recently, since this type of combustion has the potential to be highly efficient and to produce low NOx and particulate matter emissions. Ion current has proven itself as a closed loop control feedback for SI engines. Based on previous work by the authors, ion current was acquired through HCCI operation too, with promising results. However, for best utilization of this feedback signal, advanced interpretation techniques such as artificial neural networks can be used. In this paper the use of these advanced techniques on experimental data is explored and discussed. The experiments are performed on a single cylinder cam-less (equipped with a Fully Variable Valve Timing (FVVT) system) research engine fueled with commercially available gasoline (95 ON).

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.

There is a great deal of interest in new technologies to assist in reducing the CO2 output of passenger vehicles, as part of the drive to meet the limits agreed by the EU and the European Automobile Manufacturer's Association ACEA, itself a result of the Kyoto Protocol. For the internal combustion engine, the most promising of these include gasoline direct injection, downsizing and fully variable valve trains. While new types of spray-guided gasoline direct injection (GDI) combustion systems are finally set to yield the level of fuel consumption improvement which was originally promised for the so-called ‘first generation’ wall- and air-guided types of GDI, injectors for spray-guided combustion systems are not yet in production to help justify the added complication and cost of the NOx trap necessary with a stratified combustion concept.

Homogeneous charge compression ignition (HCCI), combustion has the potential to be highly efficient and to produce low NOx, carbon dioxide and particulate matter emissions, but experiences problems with cold start, running at idle and producing high power density. A solution to these is to operate the engine in a ‘hybrid mode’, where the engine operates in spark ignition mode at cold start, idle and high loads and HCCI mode elsewhere during the drive cycle, demanding a seamless transition between the two modes of combustion through spark assisted controlled auto ignition. Moreover; HCCI requires considerable control to maintain consistent start of combustion and heat release rate, which has thus far limited HCCI's practical application. In order to provide a suitable control method, a feedback signal is required.

The process of engine mapping in the automotive industry identifies steady-state engine responses by running an engine at a given operating point (speed and load) until its output has settled. While the time simulating this process with a computational model for one set of parameters is relatively short, the cumulative time to map all possible combinations becomes computationally inefficient. This work presents an alternative method for mapping out the steady-state response of an engine in simulation by applying bifurcation theory. The bifurcation approach used in this work allows the engine’s steady-state response to be traced through the model’s state-parameter space under the simultaneous variation of one or more model parameters. To demonstrate this approach, a bifurcation analysis of a simplified nonlinear engine model is presented.

Many modern I.C. engines rely on some form of active control of injection, timing and/or ignition timing to help combat tailpipe out emissions, increase the fuel economy and improve engine drivability. However, development of these strategies is often optimised to suit the average cycle at each condition; an assumption that can lead to sub-optimal performance, especially an increase in particulate (PN) emissions as I.C. engine operation, and in-particular its charge motion is subject to cycle-to-cycle variation (CCV). Literature shows that the locations of otherwise repeatable large-scale flow structures may vary by as much 25% of the bore dimension; this could have an impact on fuel break-up and distribution and therefore subsequent combustion performance and emissions.

This paper presents an investigation of Cylinder De-Activation (CDA) technology on the performance of big end bearings. A multi-physics approach is used in order to take into account more realistic dynamic loading effects on the tribological behavior. The power loss, minimum film thickness and maximum temperature of big end bearings have been calculated during maneuver pertaining to the New European Driving Cycle (NEDC). Results show that bearing efficiency runs contrary to efficiency gained through combustion and pumping losses. Under CDA mode, the power loss of big end bearings is more than the power loss under engine normal mode. The problem is predominant at higher engine speeds and higher Brake mean Effective Pressures (BMEP) in active cylinders. It is also observed that the minimum film thickness is reduced under the CDA mode. This can affect wear performance. In addition, same behavior is noted for the maximum temperature rise which is higher under CDA.

Low temperature combustion (LTC) of diesel fuel offers a path to low engine emissions of nitrogen oxides (NOx) and particulate matter (PM), especially at low loads. Borescopic optical imaging offers insight into key aspects of the combustion process without significantly disrupting the engine geometry. To assess LTC combustion, two-colour pyrometry can be used to quantify local temperatures and soot concentrations (KL factor). High sensitivity photo-multiplier tubes (PMTs) can resolve natural luminosity down to low temperatures with adequate signal-to-noise ratios. In this work the authors present the calibration and implementation of a borescope-based system for evaluating low luminosity LTC using spatially resolved visible flame imaging and high-sensitivity PMT data to quantify the luminous-area average temperature and soot concentration for temperatures from 1350-2600 K.