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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.

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.

Understanding and predicting in-cylinder flow structures that occur within compression-ignition engines is vital if further optimisation of combustion systems is to be achieved. To enable this prediction, fully validated computational models of the complex turbulent flow-fields generated during the intake and compression process are needed. However, generating, analysing and interpreting experimental data to achieve this validation remains a complex challenge due to the variability that occurs from cycle to cycle. The flow-velocity data gathered in this study, obtained from a single-cylinder CI engine with optical access using high-speed PIV, demonstrates that significantly different structures are generated over different cycles, resulting in the mean flow failing to adequately reflect the typical flow produced in-cylinder.

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.

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.

In-cylinder temperatures and their cyclic variations strongly influence many aspects of internal combustion engine operation, from chemical reaction rates determining the production of NOx and particulate matter to the tendency for auto-ignition leading to knock in spark ignition engines. Spatially resolved measurements of temperature can provide insights into such processes and enable validation of Computational Fluid Dynamics simulations used to model engine performance and guide engine design. This work uses a combination of Two-Colour Planar Laser Induced Fluorescence (TC-PLIF) and Laser Induced Grating Spectroscopy (LIGS) to measure the in-cylinder temperature distributions of a firing optically accessible spark ignition engine. TC-PLIF performs 2-D temperature measurements using fluorescence emission in two different wavelength bands but requires calibration under conditions of known temperature, pressure and composition.

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.

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.

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.

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.

Two identical commercial Thermo-Electric Modules (TEMs) were assembled on a plate type heat exchanger to form a Thermoelectric Generator (TEG) unit in this study. This unit was tested on the Exhaust Gas Recirculation (EGR) flow path of a test engine. The data collected from the test was used to develop and validate a steady state, zero dimensional numerical model of the TEG. Using this model and the EGR path flow conditions from a 30% torque Non-Road Transient Cycle (NRTC) engine test, an optimization of the number of TEM units in this TEG device was conducted. The reduction in fuel consumption during the transient test cycle was estimated based on the engine instantaneous Brake Specific Fuel Consumption (BSFC). The perfect conversion of TEG recovered electrical energy to engine shaft mechanical energy was assumed. Simulations were performed for a single TEG unit (i.e. 2 TEMs) to up to 50 TEG units (i.e. 100 TEMs).

An automotive engine can be more efficient if thermoelectric generators (TEG) are used to convert a portion of the exhaust gas enthalpy into electricity. Due to the relatively low cost of the incoming thermal energy, the efficiency of the TEG is not an overriding consideration. Instead, the maximum power output (MPO) is the first priority. The MPO of the TEG is closely related to not only the thermoelectric materials properties, but also the operating conditions. This study shows the development of a numerical TEG model integrated with a plate-fin heat exchanger, which is designed for automotive waste heat recovery (WHR) in the exhaust gas recirculation (EGR) path in a diesel engine. This model takes into account the following factors: the exhaust gas properties’ variation along the flow direction, temperature influence on the thermoelectric materials, thermal contact effect, and heat transfer leakage effect. Its accuracy has been checked using engine test data.

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.

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.

The automotive industry is subject to increasing pressure to reduce the CO2 emissions and improve fuel efficiency in internal combustion engines. Improvements may be achieved in a number of ways. The parasitic losses throughout the engine cycle emanate from friction in all engine contact conjunctions in addition to pumping losses. In particular one main contributory conjunction is the piston ring pack assembly. At low engine speeds, the contribution of friction to the total losses within the engine is increased significantly compared with the thermodynamic losses. Additionally, the sealing capability of the ring is crucial in determining the power output of the engine with any loss of sealing contributing to power loss, as well as blowby. Most reported studies on compression ring-cylinder conjunction do not take into account complex ring in-plane and out-of-plane elastodynamics.

In this paper, a direct correlation between transmission gear rattle experiments and numerical models is presented, particularly focusing on the noise levels (dB) measured from a single gear pair test rig. The rig is placed in a semi-anechoic chamber environment to aid the noise measurements and instrumented with laser vibrometers, accelerometers and free field microphones. The input torsional velocity is provided by an electric motor, which is controlled by a signal generator, aiming to introduce an alternating component onto the otherwise nominal speed; thus, emulating the engine orders found in an internal combustion engine. These harmonic irregularities are conceived to be the triggering factor for gear rattle to occur. Hence, the rig is capable of running under rattling and non-rattling conditions. The numerical model used accounts for the gear pair's torsional dynamics, lubricated impacts between meshing teeth and bearing friction.

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.

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.