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Gasoline turbocharged direct injection (GTDI) engines, such as EcoBoost™ from Ford, are becoming established as a high value technology solution to improve passenger car and light truck fuel economy. Due to their high specific performance and excellent low-speed torque, improved fuel economy can be realized due to downsizing and downspeeding without sacrificing performance and driveability while meeting the most stringent future emissions standards with an inexpensive three-way catalyst. A logical and synergistic extension of the EcoBoost™ strategy is the use of E85 (approximately 85% ethanol and 15% gasoline) for knock mitigation. Direct injection of E85 is very effective in suppressing knock due to ethanol's high heat of vaporization - which increases the charge cooling benefit of direct injection - and inherently high octane rating. As a result, higher boost levels can be achieved while maintaining optimal combustion phasing giving high thermal efficiency.

This paper proposes an approach that characterizes a driver's driving behavior and style in real-time during car-following drives. It uses an online learning of the evolving Takagi-Sugeno fuzzy model combined with the Markov model. The inputs fed into the proposed algorithm are from the measured signals of on-board sensors equipped with current vehicles, including the relative distance sensors for Adaptive Cruise Control feature and the accelerometer for Electronic Stability Control feature. The approach is verified using data collected using a test vehicle from several car-following test trips. The effectiveness of the proposed approach has been shown in the paper.

The higher cylinder peak pressure and pressure rise rate of modern diesel and gasoline fueled engines tend to increase combustion noise while customers demand lower noise. The multiple degrees of freedom in engine control and calibration mean there is more scope to influence combustion noise but this must first be measured before it can be balanced with other attributes. An efficient means to realize this is to calculate combustion noise from the in-cylinder pressure measurements that are routinely acquired as part of the engine development process. This publication reviews the techniques required to ensure accurate and precise combustion noise measurements. First, the dynamic range must be maximized by using an analogue to digital converter with sufficient number of bits and selecting an appropriate range in the test equipment.

Fuel injection is a key process influencing the performance of Gasoline Direct Injection (GDI) Engines. Injecting fuel at elevated temperature can initiate flash boiling which can lead to faster breakup, reduced penetration, and increased spray-cone angle. Thus, it impacts engine efficiency in terms of combustion quality, CO2, NOx and soot emission levels. This research deals with modelling of flash boiling processes occurring in gasoline fuel injectors. The flashing mass transfer rate is modelled by the advanced Hertz-Knudsen model considering the deviation from the thermodynamic-equilibrium conditions. The effect of nucleation-site density and its variation with degree of superheat is studied. The model is validated against benchmark test cases and a substantiated comparison with experiment is achieved.

Idle Combustion Stability has previously been difficult to predict prior to prototype engine development. This paper describes an empirical modeling approach to predicting upfront idle combustion stability. The model outputs are the combustion torque harmonic magnitudes and %LNV. The paper describes the modeling methodology and provides correlation results for different engine configurations.

The world of automotive engineering shows a clear direction for upcoming development trends. Stringent fleet average fuel consumption targets and CO2 penalties as well as rising fuel prices and the consumer demand to lower operating costs increases the engineering efforts to optimize fuel economy. Passenger car engines have the benefit of higher degree of technology which can be utilized to reach the challenging targets. Variable valve timing, downsizing and turbo charging, direct gasoline injection, highly sophisticated operating strategies and even more electrification are already common technologies in the automotive industry but can not be directly carried over into a motorcycle application. The major differences like very small packaging space, higher rated speeds, higher power density in combination with lower production numbers and product costs do not allow implementation such high of degree of advanced technology into small-engine applications.

This paper proposes an approach to use ABS wheel speed sensor signals together with other vehicle state information from a brake control module to detect an unbalanced tire or tires in real-time. The proposed approach consists of two-stage algorithms that mix a qualitative method using band-pass filtering with a quantitative parameter identification using conditional least squares. This two-stage approach can improve the robustness of tire imbalance or imbalances. The proposed approach is verified through vehicle testing and the test results show the effectiveness of the approach.

In an attempt to predict the responses of side crash pressure sensors, the Corpuscular Particle Method (CPM) was adopted and enhanced in this research. Acceleration-based crash sensors have traditionally been used extensively in automotive industry to determine the air bag firing time in the event of a vehicle accident. The prediction of crash pulses obtained from the acceleration-based crash sensors by using computer simulations has been very challenging due to the high frequency and noisy responses obtained from the sensors, especially those installed in crash zones. As a result, the sensor algorithm developments for acceleration-based sensors are largely based on prototype testing. With the latest advancement in the crash sensor technology, side crash pressure sensors have emerged recently and are gradually replacing acceleration-based sensor for side impact applications.

An Arbitrary Lagrangian Eulerian (ALE) approach was adopted in this study to predict the responses of side crash pressure sensors in an attempt to assist pressure sensor algorithm development by using computer simulations. Acceleration-based crash sensors have traditionally been used to deploy restraint devises (e.g., airbags, air curtains, and seat belts) in vehicle crashes. The crash pulses recorded by acceleration-based crash sensors usually exhibit high frequency and noisy responses depending on the vehicle's structural design. As a result, it is very challenging to predict the responses of acceleration-based crash sensors by using computer simulations, especially those installed in crush zones. Therefore, the sensor algorithm developments for acceleration-based sensors are mostly based on physical testing.

Two combustion systems were developed and optimized for an engine for a power cylinder of 0.8-0.9L/cylinder. The first design was a re-entrant bowl concept which was based on the combustion system of a smaller engine with roughly 0.5L/cylinder. The second design was a chamfered bowl concept, a variant of a reentrant bowl that deliberately splits fuel between the bowl and the squish region. For each combustion system concept, nozzle tip protrusion, swirl, and nozzle configuration (number of holes, nozzle flow, and spray angle) were optimized. Several similarities between combustion system concepts were noted, including the optimal swirl and number of holes. The resulting optimums for each concept were compared. The chamfered combustion system was found to have better part-load emissions and fuel consumption tradeoffs. Full load performance was similar at low speed between the two combustion systems, but the reentrant combustion system had advantages at high engine speed and load.

Internal combustion (IC) engines fueled by hydrogen are among the most efficient means of converting chemical energy to mechanical work. The exhaust has near-zero carbon-based emissions, and the engines can be operated in a manner in which pollutants are minimal. In addition, in automotive applications, hydrogen engines have the potential for efficiencies higher than fuel cells.[1] In addition, hydrogen engines are likely to have a small increase in engine costs compared to conventionally fueled engines. However, there are challenges to using hydrogen in IC engines. In particular, efficient combustion of hydrogen in engines produces nitrogen oxides (NOx) that generally cannot be treated with conventional three-way catalysts. This work presents the results of experiments which consider changes in direct injection hydrogen engine design to improve engine performance, consisting primarily of engine efficiency and NOx emissions.

With a goal to help develop pressure sensor calibration and deployment algorithms using computer simulations, an Arbitrary Lagrangian Eulerian (ALE) approach was adopted in this research to predict the responses of side crash pressure sensors for unitized vehicles. For occupant protection, acceleration-based crash sensors have been used in the automotive industry to deploy restraint devices when vehicle crashes occur. With improvements in the crash sensor technology, pressure sensors that detect pressure changes in door cavities have been developed recently for vehicle crash safety applications. Instead of using acceleration (or deceleration) in the acceleration-based crash sensors, the pressure sensors utilize pressure change in a door structure to determine the deployment of restraint devices. The crash pulses recorded by the acceleration-based crash sensors usually exhibit high frequency and noisy responses.

The Leaner Lifted-Flame Combustion (LLFC) strategy offers a possible alternative to low temperature combustion or other globally lean, premixed operation strategies to reduce soot directly in the flame, while maintaining mixing-controlled combustion. Adjustments to fuel properties, especially fuel oxygenation, have been reported to have potentially beneficial effects for LLFC applications. Six fuels were selected or blended based on cetane number, oxygen content, molecular structure, and the presence of an aromatic hydrocarbon. The experiments compared different fuel blends made of n-hexadecane, n-dodecane, methyl decanoate, tri-propylene glycol monomethyl ether (TPGME), as well as m-xylene. Several optical diagnostics have been used simultaneously to monitor the ignition, combustion and soot formation/oxidation processes from spray flames in a constant-volume combustion vessel.

Natural luminosity (NL) and chemiluminescence (CL) imaging diagnostics are employed to investigate fuel-property effects on mixing-controlled combustion, using select research fuels-a #2 ultra-low sulfur emissions-certification diesel fuel (CF) and four of the Fuels for Advanced Combustion Engines (FACE) diesel fuels (F1, F2, F6, and F8)-that varied in cetane number (CN), distillation characteristics, and aromatic content. The experiments were performed in a single-cylinder heavy-duty optical compression-ignition (CI) engine at two injection pressures, three dilution levels, and constant start-of-combustion timing. If the experimental results are analyzed only in the context of the FACE fuel design parameters, CN had the largest effect on emissions and efficiency.

This paper presents engine dynamometer testing and modeling analysis of ethanol compared to gasoline at part load conditions where the engine was not knock-limited with either fuel. The purpose of this work was to confirm the efficiency improvement for ethanol reported in published papers, and to quantify the components of the improvement. Testing comparing E85 to E0 gasoline was conducted in an alternating back-to-back manner with multiple data points for each fuel to establish high confidence in the measured results. Approximately 4% relative improvement in brake thermal efficiency (BTE) was measured at three speed-load points. Effects on BTE due to pumping work and emissions were quantified based on the measured engine data, and accounted for only a small portion of the difference.

The optimization of engine NVH is still an important aspect for vehicle interior and exterior noise radiation. To optimize the engine noise / vibration contribution to the vehicle, a complete understanding of the excitation mechanism, the vibration transfer in the engine structure and the radiation efficiency of the individual engine components is required. Concerning the excitation within the engine, a very efficient analysis methodology for the combustion- and mechanical excitation within gasoline and diesel engines has been developed. Out of this methodology a software tool has been designed for a fast, efficient and detailed evaluation of the combustion- and mechanical excitation content of total engine noise. Recently this software tool has been successfully applied in engine NVH optimization work for defining the best optimization strategies for engine NVH reduction and noise quality improvement especially with respect to combustion excitation.

The small-displacement direct-injection (DI) diesel engine is a prime candidate for future transportation needs because of its high thermal efficiency combined with near term production feasibility. Ford Motor Company and FEV Engine Technology, Inc. are working together with the US Department of Energy to develop a small displacement DI diesel engine that meets the key challenges of emissions, NVH, and power density. The targets for the engine are to meet ULEV emission standards while maintaining a best fuel consumption of 200g/kW-hr. The NVH performance goal is transparency with state-of-the-art, four-cylinder gasoline vehicles. Advanced features are required to meet the ambitious targets for this engine. Small-bore combustion systems enable the downsizing of the engine required for high fuel economy with the NVH advantages a four- cylinder has over a three-cylinder engine.

A model of Ford's current FTP based OBD-II catalyst monitor has been developed and used in determining the optimal monitored catalyst volume for several LEV applications. The model predictions were found to agree reasonably well with the available experimental data. Furthermore, the results of this study indicate that the optimal monitored catalyst volume for meeting LEV requirements is vehicle application specific. As a result, it is concluded that a general guideline for sizing of the monitored catalyst volume for LEVs will most likely be inadequate and could result in grossly suboptimal catalyst monitor function for some applications. The model which is described in this paper offers a potentially more effective means of determining the best monitored catalyst volume for a given vehicle application. It should be possible to utilize this model during the early phase of a vehicle program in order to provide for the optimal packaging of the catalyst monitor sensor (CMS).

The effect of fuel sulfur on the dual HEGO sensor OBD-II catalyst monitor has been investigated. Laboratory studies revealed two competing effects of the fuel sulfur on the operation of the catalyst monitor: 1. the loss of catalyst oxygen storage capacity, and 2. the degradation in the response rate of the rear HEGO sensor. The magnitude of the loss in catalyst OSC relative to the increase in rear HEGO sensor response time determined whether the rear HEGO sensor index increased, decreased, or remained constant as the fuel sulfur level was increased. The effect of fuel sulfur on tailpipe emissions and the catalyst monitor was also measured for two LEVs equipped with Pd-only catalyst technology (a 1997MY Escort and a 1998MY Crown Victoria). For both vehicles, the effect of the fuel sulfur on the rear HEGO sensor response characteristics dominated; as the fuel sulfur level was increased, tailpipe emissions increased, but the rear HEGO sensor index decreased.

Ford Motor Company is researching and developing multiple propulsion strategies which include advanced gasoline engines, clean diesel, flexible fuel (ethanol blends up to E-85), hybrids and hydrogen propulsion, both in internal combustion (IC) engines and fuel cells. Hydrogen utilized as a transportation fuel is viewed as a long term solution as it is sustainable and clean when derived from renewable resources. The development and use of hydrogen IC engine (H2ICE) technology can readily be utilized to drive the transition strategy from the petroleum economy to the hydrogen economy. Because the “more conventional” H2ICE systems can be brought to market more quickly and in higher volume, business initiatives for hydrogen fueling infrastructure and other hydrogen complimentary required technologies can be realized sooner. To that end Ford has fully re-engineered a 6.8L Triton V-10 engine to run on hydrogen and power an E-450 shuttle van.