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Combustion engines are typically only 20-30% efficient at part-load operating conditions, resulting in poor fuel economy on average. To address this, LiquidPiston has developed an improved thermodynamics cycle, called the High-Efficiency Hybrid Cycle (HEHC), which optimizes each process (stroke) of the engine operation, with the aim of maximizing fuel efficiency. The cycle consists of: 1) a high compression ratio; 2) constant-volume combustion, and 3) over-expansion. At a modest compression ratio of 18:1, this cycle offers an ideal thermodynamic efficiency of 74%. To embody the HEHC cycle, LiquidPiston has developed two very different rotary engine architectures ? called the ?M? and ?X? engines. These rotary engine architectures offer flexibility in executing the thermodynamics cycle, and also result in a very compact package. In this talk, I will present recent results in the development of the LiquidPiston engines. The company is currently testing 20 and 40 HP versions of the ?M?

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.

When a vehicle with a partially filled fuel tank undergoes sudden acceleration, braking, turning or pitching motion, fuel sloshing is experienced. It is important to establish a CAE methodology to accurately predict slosh phenomenon. Fuel slosh can lead to many failure modes such as noise, erroneous fuel indication, irregular fuel supply at low fuel level and durability issues caused by high impact forces on tank surface and internal parts. This paper summarizes activities carried out by the fuel system team at Ford Motor Company to develop and validate such CAE methodology. In particular two methods are discussed here. The first method is Volume Of Fluid (VOF) based incompressible multiphase Eulerian transient CAE method. The CFD solvers used here are Star CD and Star CCM+. The second method incorporates Fluid-Structure interaction (FSI) using Arbitrary Lagrangian-Eulerian (ALE) formulation.

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.

A new turbocharged 60° 2.7L 4V-V6 gasoline engine has been developed by Ford Motor Company for both pickup trucks and car applications. This engine was code named “Nano” due to its compact size; it features a 4-valves DOHC valvetrain, a CGI cylinder block, an Aluminum ladder, an integrated exhaust manifold and twin turbochargers. The goal of this engine is to deliver 120HP/L, ULEV70 emission, fuel efficiency improvements and leadership level NVH. This paper describes the upfront design and optimization process used for the NVH development of this engine. It showcases the use of analytical tools used to define the critical design features and discusses the NVH performance relative to competitive benchmarks.

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.

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 modeling of plastic fuel tank systems for crash safety applications has been very challenging. The major challenges include the prediction of fuel sloshing in high speed impact conditions, the modeling of multilayer thermoplastic fuel tanks with post-forming (non-uniform) material properties, and the modeling of tank straps with pre-tensions. Extensive studies can be found in the literature to improve the prediction of fuel sloshing. However, little research had been conducted to model the post-forming fuel tank and to address the tension between the fuel tank and the tank straps for crash safety simulations. Hoping to help improve the modeling of fuel systems, the authors made the first attempt to tackle these major challenges all at once in this study by dividing the modeling of the fuel tank into eight stages. An ALE (Arbitrary Lagrangian-Eulerian) method was adopted to simulate the interaction between the fuel and the tank.

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.

Until now no results have been available regarding the composition of evaporative emissions in a SHED test. In particular, for alcohol containing fuels, it is important to assess the relative percentage of alcohols and hydrocarbons in view of their different environmental impacts. This paper presents the results of a study conducted to determine the composition of the emissions from a number of multilayer coextruded plastic fuel tanks soaked in IE10 and CM15 test fuels. These emissions were analyzed for composition using a gas chromatography analytical method which employs a vapor trap and desorb sampling technique. In the case of CM15, methanol was found to account for as much as 50% of the overall evaporative emissions. This speciation method also allows estimation of how leakage and permeation contribute separately to the overall emissions.

This report is a comprehensive investigation into the use of resin transfer molded glass fiber reinforced plastics in a structural application. A pickup truck cab structure is an ideal application for plastic composites. The cab is designed to fit a production Ranger pickup truck and uses carryover frame and front end structure. The cab concept consists primarily of two molded pieces. This design demonstrates extensive parts integration and allows for low-cost tooling, along with automated assembly.

A simple set of equations has been developed to characterize automotive fuel behavior in fuel tanks, fuel vapor systems and fuel rails, particularly under hot weather conditions. The system of equations links the vapor pressure P, the temperature T, and the mass fraction evaporated Z. Parameters are determined empirically from laboratory vapor pressure and distillation tests. With appropriate values for heat capacity, heat of vaporization, and vapor composition, the equations can be used to estimate upper flammability limits, fuel weathering under hot fuel handling conditions, pressure rise in tanks, and evaporative vapor generation. The equations were developed as part of a larger fuel vapor system model.

Experimental forms of two different types of engine oil viscosity sensors have been tested that use uniformly poled disks of piezoelectric PZT ceramic. In both cases, the disks were used to form electromechanical resonators functioning as the frequency-controlling element in a transistor oscillator circuit. The simpler type of sensor used only one disk, vibrating in a radial-longitudinal mode of vibration. In this mode, a disk 2.54 cm in diameter and 0.127 cm thick had a resonant frequency of approximately 90 kHz. The second type of sensor used two such disks bonded together by a conducting epoxy, with poling directions oriented in opposite directions. This composite resonator vibrated in a radially-symmetrical, flexural mode of vibration, with the lowest resonant frequency at approximately 20 kHz. The presence of tangential components of motion on the major faces of both resonators made them sensitive to the viscosity of fluids in which they were immersed.

A piezoelectrically driven vibrating cantilever blade is damped by a number of mechanisms including viscous damping in a still fluid and aerodynamic damping in a flow. By measuring the damping of devices operating at resonance in the 1 to 5 kHz region, one can measure such properties as mass flow, absolute pressure or the product of molecualar mass and viscosity. In the case of the mass flow measurement, the device offers a mechanical alternative to hotwire and hot film devices for the automotive application.

A new diesel engine, called the 6.7L Power Stroke® V-8 Turbocharged Diesel, and code named "Scorpion" has been designed and developed by Ford Motor Company for the full-size pickup truck and light commercial vehicle markets. It incorporates the latest design technology to meet 2010 model year emission regulations for both chassis and dynamometer-based certifications, and is compatible with up to B20 biodiesel fuel. The engine is an entirely new 90 degree V-8 design featuring inboard exhaust, piezo common rail fuel injection, a new dual compressor wheel turbocharger, and dual loop cooling systems. The 6.7L is Ford's first diesel engine designed for the North American pickup and light commercial truck market.

Increasing electronics content, growing computing power, and proliferation of opportunities for information connectivity (through improved sensors, GPS, road and traffic information systems, wireless internet access, vehicle-to-vehicle communication, etc.) are technology trends which can significantly transform and impact future automotive vehicle's control and diagnostic strategies. One aspect of the increasing vehicle connectivity is access to ambient and road condition information, such as ambient temperature, ambient pressure, humidity, % cloudiness, visibility, cloud ceiling, precipitation, rain droplet size, wind speed, and wind direction based on wireless internet access. The paper discusses the potential opportunities made available through wireless communication between the vehicle and the internet.

Ford developed the 6R140 TorqShift six-speed transmission for the Ford F-series SuperDuty trucks. The 6R140 transmission is specifically designed to manage the increased torque produced by the 6.7-liter Power Stroke V-8 turbocharged diesel engine. It is also matched with the 6.2-liter V-8 gasoline engine. By design, the new 6R140 transmission seamlessly delivers the enormous low-rpm torque produced by the new diesel engine and efficiently manages the higher rpm of the new gasoline engine.