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In-cylinder spray imaging by Mie scattering has been taken with frame rates up to 27,000 fps, along with high speed video photography of chemiluminescence and soot thermal radiation. Spectroscopic measurements have confirmed the presence of OH*, CH* and C2* emissions lines, and their magnitude relative compared to soot radiation. Filtering for CH* has been used with both the high speed video and a Photo-Multiplier Tube (PMT). The PMT signals have been found to correlate with the rate of heat release derived from in-cylinder pressure measurements. A high power photographic strobe has been used to illuminate the fuel spray. Images show that the fuel spray can strike the ground strap of the spark plug, break up, and a fuel cloud then drifts over and under the strap through the spark plug gap. Tests have conducted at two different spark plug orientations using a single spark strategy.

Particulate emissions from gasoline direct injection (GDI) engines continue to be a topic of substantial research interest. Forthcoming regulation both in the USA and the EU will further reduce their emission and drive innovation. Substantial research effort is spent undertaking experiments to understand, characterize, and research particle number (PN) emissions from engines and vehicles. Recent advances in computing power, data storage, and understanding of artificial intelligence algorithms now mean that these are becoming an important tool in engine research. In this work a random forest (RF) algorithm is used for the prediction of PN emissions from a highly boosted (up to 32 bar BMEP) GDI engine. Particle size, concentration, and the accumulation mode geometric standard deviation (GSD) are all predicted by the model. The results are analysed and an in depth study on parameter importance is carried out.

Driving cycles are typically used for estimation of vehicle fuel/energy consumption and CO2 emissions. In most of applications only the vehicle velocity vs. time profile is considered as a driving cycle, while a road slope is typically omitted. Since the road slope significantly impacts the fuel consumption, it should be included into realistic driving cycles for hilly roads. As a part of wider research of multidimensional driving cycle synthesis, this paper focuses on analysis of a broad city bus driving cycle dataset recorded in the city of Dubrovnik. The analysis is aimed at revealing the impact of road slope on velocity and acceleration distributions, and clustering the recorded data into several groups reflecting various driving and traffic congestion characteristics. Finally, the Markov chain method is employed to synthesize 3D driving cycles for the selected data clusters, where the Markov chain states include vehicle velocity, vehicle acceleration, and road slope.

Modern automotive heating, ventilation, and air-conditioning (HVAC) systems have multiple and often redundant actuators. Design of a control system that optimally synthesizes multiple control actions while satisfying control set points and system hardware-related constraints is necessary to maximize HVAC efficiency. To this end, an optimization approach to control system design is proposed in this paper and demonstrated for a generic air-conditioning (A/C) system. The paper first outlines a nonlinear 12th-order A/C dynamics model based on the moving-boundary method. Then, the A/C control system is defined, which combines feedback controllers commanding the compressor speed and expansion valve opening, and open-loop actions of condenser and blower fans. Next, a three-stage, multi-objective genetic algorithm-based approach of control system optimization is proposed.

This paper presents a newly developed quasi-dimensional multi-zone dual fuel combustion model, which has been integrated within the commercial engine system simulation framework. Model is based on the modified Multi-Zone Combustion Model and Fractal Combustion Model. Modified Multi-Zone Combustion Model handles the part of the combustion process that is governed by the mixing-controlled combustion, while the modified Fractal Combustion Model handles the part that is governed by the flame propagation through the combustion chamber. The developed quasi-dimensional dual fuel combustion model features phenomenological description of spray processes, i.e. liquid spray break-up, fresh charge entrainment, droplet heat-up and evaporation process. In order to capture the chemical effects on the ignition delay, special ignition delay table has been made.

The introduction of transient test cycles and the focus on real world driving emissions has increased the importance of ensuring the NOx and soot emissions are controlled during transient manoeuvres. At the same time, there is a drive to reduce the number of calibration variables used by engine control strategies to reduce development effort and costs. In this paper, a control orientated combustion model, [1], and model predictive control strategy, [2], that were developed in simulation and reported in earlier papers, are applied to a Diesel engine and demonstrated in a test vehicle. The paper describes how the control approach developed in simulation was implemented in embedded hardware, using an FPGA to accelerate the emissions calculations. The development of the predictive controller includes the application of a simplified optimisation algorithm to enable a real-time calculation in the test vehicle.

In-cylinder temperature measurements are vital for the validation of gasoline engine modelling and useful in their own right for explaining differences in engine performance. The underlying chemical reactions in combustion are highly sensitive to temperature and affect emissions of both NOx and particulate matter. The two techniques described here are complementary, and can be used for insights into the quality of mixture preparation by measurement of the in-cylinder temperature distribution during the compression stroke. The influence of fuel composition on in-cylinder mixture temperatures can also be resolved. Laser Induced Grating Spectroscopy (LIGS) provides point temperature measurements with a pressure dependent precision in the range 0.1 to 1.0 % when the gas composition is well characterized and homogeneous; as the pressure increases the precision improves.

In this study, the role of turbulence-chemistry interaction in diesel spray auto-ignition, flame stabilization and end of injection phenomena is investigated under engine relevant “Spray A” conditions. A recently developed diesel spray combustion modeling approach, Conditional Source-term Estimation (CSE-FGM), is coupled with Reynolds-averaged Navier-Stokes simulation (RANS) framework to study the details of spray combustion. The detailed chemistry mechanism is included through the Flamelet Generated Manifold (FGM) method. Both unsteady and steady flamelet solutions are included in the manifold to account for the auto-ignition process and the subsequent flame propagation in a diesel spray. Conditionally averaged chemical source terms are closed by the conditional scalars obtained in the CSE routine. Both non-reacting and reacting spray jets are computed over a wide range of Engine Combustion Network (ECN) diesel. “Spray A” conditions.

This study looked into the application of active thermal coatings on the surfaces of the combustion chamber as a method of improving the thermal efficiency of internal combustion engines. The active thermal coating was applied to a production aluminium piston and its performance was compared against a reference aluminium piston on a single-cylinder diesel engine. The two pistons were tested over a wide range of speed/load conditions and the effects of EGR and combustion phasing on engine performance and tailpipe emissions were also investigated. A detailed energy balance approach was employed to study the thermal behaviour of the active thermal coating. In general, improvements in indicated specific fuel consumption were not statistically significant for the coated piston over the whole test matrix. Mean exhaust temperature showed a marginal increase with the coated piston of up to 6 °C.

A step-ratio automatic transmission alters torque paths for gearshifting through engagement and disengagement of clutches. It enables torque sources to run efficiently while meeting driver demand. Yet, clutch thermal energy during gearshifting is one of the contributors to the overall fuel loss. In order to optimize drivetrain control strategy, including the frequency of shifts, it is important to understand the cost of shift itself. In a power-on upshift, clutch thermal energy is primarily dissipated during inertia phase. The interaction between multiple clutches, coupled with input torque truncation, makes the decomposition of overall energy loss less obvious. This paper systematically presents the mathematical analysis of clutch thermal energy during the inertia phase of a typical single-transition gearshift. In practice, a quicker shift is generally favored, partly because the amount of energy loss is considered smaller.

The paper presents the estimator design procedures for automotive power train systems based on the adaptive Kalman filter. The Kalman filter adaptation is based on a simple and robust algorithm that detects sudden changes of power train variables. The adaptive Kalman filter has been used to estimate the SI engine load torque and air mass flow, and also the tire traction force and road condition. The presented experimental results indicate that proposed estimators are characterized by favorable response speeds and good noise suppression abilities.

This paper presents an adaptive extended Kalman filter (EKF)-based sideslip angle estimator, which utilizes a sensor fusion concept that combines the high-rate inertial sensors measurements with the low-rate GPS velocity measurements. The sideslip angle estimation is based on a vehicle kinematic model relying on the lateral accelerometer and yaw rate gyro measurements. The vehicle velocity measurements from low-cost, single antenna GPS receiver are used for compensation of potentially large drift-like estimation errors caused by inertial sensors offsets. Adaptation of EKF state covariance matrix ensures a fast convergence of inertial sensors offsets estimates, and consequently a more accurate sideslip angle estimate.

This paper presents a practical and straightforward method of identifying geometry parameters of a cam-like lever-based electromechanical dual-clutch actuator, with application to actuator dynamics model parameterization. The lever-based actuator resembles a cam mechanism in that a movable roller fulcrum, driven by an electromotor through a ball-screw, drives the lever by direct contact along the lever profile. This necessitates the identification of the lever profile geometry in order to accurately model the mechanism dynamics. The identification method is based on the measured basic lever mechanism dimensions, experimentally recorded input-output response of the lever mechanism during unloaded operation, observed geometric constraints satisfied during operation, and common CAD software tools to conduct a CAD-based mechanism synthesis and position analysis.

Dual Clutch Transmissions with dry electromechanically actuated clutches have emerged on the market recently. In order to provide their favorable operation in terms of the clutch torque control, it is very important to have a good knowledge on the system behavior related to the actuator dynamics, the dry friction coefficient behavior, and the thermal dynamics. This paper describes two test rigs developed to support the research work on a dry dual clutch with a lever-based electromechanical actuation system. The first test rig (actuation system test rig) provides a basis for a comprehensive multi-step identification of the actuation system parameters and characterization of the overall system behavior. This test rig includes a modified dual clutch assembly including a built-in sensor for the purpose of direct normal force measurement.

Models for the convective heat transfer from the combustion gases to the walls inside a spark ignition engine are an important keystone in the simulation tools which are being developed to aid engine optimization. The existing models have, however, been cited to be inaccurate for hydrogen, one of the alternative fuels currently investigated. One possible explanation for this inaccuracy is that the models do not adequately capture the effect of the gas properties. These have never been varied in a wide range because air and ‘classical’ fossil fuels have similar values, but they are significantly different in the case of hydrogen. As a first step towards a fuel independent heat transfer model, we have investigated the effect of the gas properties on the heat flux in a spark ignition engine.

Knowledge of fuel mass injected in an individual cycle is important for engine performance and modeling. At the moment, such measurements are not possible on engine or in real time. In this article, a new method using Coriolis flow meters (CFMs) and a new, patented, signal processing technique, known as the Prism, are introduced. CFMs are extensively used for flow measurement both in the automotive industry and further afield and, when coupled with the Prism, have the potential to make these challenging high-speed measurements. A rig-based feasibility study was conducted injecting very small quantities of diesel (3 mg) at pressures of up to 1000 bar at simulated engine speeds of up to 4000 rpm. The results show that these small quantities can in principle be measured. The results also reveal a previously unknown behavior of CFMs when measuring very low flow rates at high speed.

Spray guided Direct Injection Gasoline Engines are a key enabler to reducing CO2 emissions and improving the fuel economy of light duty vehicles. Particulate emissions from these engines have been shown to be lower than from first generation direct injection gasoline engines, but they may still be significantly higher than port fuel injected engines due to the reduced time available for mixture preparation and increased incidence of fuel impingement on the piston crown and combustion chamber surfaces. These factors are particularly severe in the period following a cold start. Both nuclei and accumulation mode particle size and number concentration were measured using a Cambustion differential mobility spectrometer. These data are reported for different coolant temperature intervals during the warm-up period. The bulk composition was determined using thermo-gravimetric analysis, and PM mass fractions are given for different volatility ranges and for elemental carbon.

Particulate Emissions from Homogeneous Charge Compression Ignition (HCCI) combustion are routinely assumed to be negligible. It is shown here that this is not the case when HCCI combustion is implemented in a direct injection gasoline engine. The conditions needed to sustain HCCI operation were realized using the negative valve overlap method for trapping high levels of residual exhaust gases in the cylinder. Measurements of emitted particle number concentration and electrical mobility diameter were made with a Cambustion DMS500 over the HCCI operating range possible with this hardware. Emissions of oxides of nitrogen, carbon monoxide and unburned hydrocarbons were also measured. These data are presented and compared with similar measurements made under conventional spark ignition (SI) operation in the same engine. Under both SI and HCCI operation, a significant accumulation mode was detected with particle equivalent diameters between 80 and 100 nm.

The blending of oxygenated compounds with gasoline is projected to increase because oxygenate fuels can be produced renewably, and because their high octane rating allows them to be used in substitution of the aromatic fraction in gasoline. Blending oxygenates with gasoline changes the fuels' properties and can have a profound affect on the distillation curve, both of which are known to affect engine-out emissions. In this work, the effect of blending methanol and ethanol with gasoline on unburned hydrocarbon and particulate emissions is experimentally determined in a spray guided direct injection engine. Particulate number concentration and size distribution were measured using a Cambustion DMS500. These data are presented for different air fuel ratios, loads, ignition timings and injection timings. In addition, the ASTM D86 distillation curve was modeled using the binary activity coefficients method for the fuel blends used in the experiments.

Planar Laser-Induced Fluorescence has been widely accepted and applied to measurements of fuel concentration distributions in IC engines. The need for such measurements has increased with the introduction of Direct Injection (DI) gasoline engines, where it is critical to understand the influence of mixture inhomogeneity on ignition and subsequent combustion, and in particular the implications for cyclic variability. The apparent simplicity of PLIF has led to misunderstanding of the technique when applied to quantitative measurements of fuel distributions. This paper presents a series of engineering methods for optimizing, calibrating and referencing, which together demonstrate a quantitative measure of fuel concentration with an absolute accuracy of 10%. PLIF is widely used with single component fuels as carriers for the fluorescent tracers.