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This presentation 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. Presenter Jianbo Lu, Ford Motor Co.

This session focuses on kinetically controlled combustion. Experimental and simulation studies pertaining to various means of controlling combustion are welcome. Examples are research studies dealing with temperature and composition distribution inside the cylinder and their impact on heat release process. Studies clarifying the role of fuel physical and chemical properties in autoignition are also welcome. Presenter Hanho Yun, General Motors Company

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?

Operation of flex fuel vehicles requires operation with a range of fuel properties. The significant differences in the heat of vaporization and energy density of E0-E100 fuels and the effect on spray development need to be fully comprehended when developing engine control strategies. Limited enthalpy for fuel vaporization needs to be accounted for when developing injection strategies for cold start, homogeneous and stratified operation. Spray imaging of multi-hole gasoline injectors with fuels ranging from E0 to E100 and environmental conditions that represent engine operating points from ambient cold start to hot conditions was performed in a spray chamber. Schlieren visualization technique was used to characterize the sprays and the results were compared with Laser Mie scattering and Back-lighting technique. Open chamber experiments were utilized to provide input and validation of a CFD model.

New European emissions legislation (Euro5) specifies a limit for Particle Number (PN) emissions and therefore drives measurement of PN during vehicle development and homologation. Concurrently, the use of biofuel is increasing in the marketplace, and Euro5 specifies that reference fuel must contain a bio-derived portion. Work was carried out to test the effect of fuels containing different levels of Fatty Acid Methyl Ester (FAME) on particle number, size, mass and composition. Measurements were conducted with a Cambustion Differential Mobility Spectrometer (DMS) to time-resolve sub-micron particles (5-1000nm), and a Horiba Solid Particle Counting System (SPCS) providing PN data from a Euro5-compliant measurement system. To ensure the findings are relevant to the modern automotive business, testing was carried out on a Euro4 compliant passenger car fitted with a high-pressure common-rail diesel engine and using standard homologation procedures.

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.

Ion current sensors have been considered for the feedback electronic control of gasoline and diesel engines and for onboard vehicles powered by both engines, while operating on their conventional cycles or on the HCCI mode. The characteristics of the ion current signal depend on the progression of the combustion process and the properties of the combustion products in each engine. There are large differences in the properties of the combustible mixture, ignition process and combustion in both engines, when they operate on their conventional cycles. In SI engines, the charge is homogeneous with an equivalence ratio close to unity, ignition is initiated by an electric spark and combustion is through a flame propagating from the spark plug into the rest of the charge.

In this study, the particle emission characteristics of 10% alternative diesel fuel blends (Rapeseed Methyl Ester and Gas-to-Liquid) were investigated through the tests carried out on a light duty common-rail Euro 4 diesel engine. Under steady engine conditions, the study focused on particle number concentration and size distribution, to comply with the particle metrics of the European Emission Regulations (Regulation NO 715/2007, amended by 692/2008 and 595/2009). The non-volatile particle characteristics during the engine warming up were also investigated. They indicated that without any modification to the engine, adding selected alternative fuels, even at a low percentage, can result in a noticeable reduction of the total particle numbers; however, the number of nucleation mode particles can increase in certain cases.

The acoustic and performance characteristics of an automotive centrifugal compressor are studied on a steady-flow turbocharger test bench, with the goal of advancing the current understanding of compression system instabilities at the low-flow range. Two different ducting configurations were utilized downstream of the compressor, one with a well-defined plenum (large volume) and the other with minimized (small) volume of compressed air. The present study measured time-resolved oscillations of in-duct and external pressure, along with rotational speed. An orifice flow meter was incorporated to obtain time-averaged mass flow rate. In addition, fast-response thermocouples captured temperature fluctuations in the compressor inlet and exit ducts along with a location near the inducer tips.

This paper presents the extended Kalman filter-based sideslip angle estimator design using a nonlinear 5DoF single-track vehicle dynamics model with stochastic modeling of tire forces. Lumped front and rear tire forces have been modeled as first-order random walk state variables. The proposed estimator is primarily designed for vehicle sideslip angle estimation; however it can also be used for estimation of tire forces and cornering stiffness. This estimator design does not rely on linearization of the tire force characteristics, it is robust against the variations of the tire parameters, and does not require the information on coefficient of friction. The estimator performance has been first analyzed by means of computer simulations using the 10DoF two-track vehicle dynamics model and underlying magic formula tire model, and then experimentally validated by using data sets recorded on a test vehicle.

Pareto optimal map concept has been applied to the optimization of the vehicle system control (VSC) strategy for a power-split hybrid electric vehicle (HEV) system. The methodology relies on an inner-loop optimization process to define Pareto maps of the best engine and electric motor/generator operating points given wheel power demand, vehicle speed, and battery power. Selected levels of model fidelity, from simple to very detailed, can be used to generate the Pareto maps. Optimal control is achieved by applying Pontryagin's minimum principle which is based on minimization of the Hamiltonian comprised of the rate of fuel consumption and a co-state variable multiplied by the rate of change of battery SOC. The approach delivers optimal control for lowest fuel consumption over a drive cycle while accounting for all critical vehicle operating constraints, e.g. battery charge balance and power limits, and engine speed and torque limits.

In this paper, the cyclic deformation behavior of an Al-Si-Cu alloy is studied under strain-controlled thermo-mechanical loading. Tests are carried out at temperatures from 20 °C to 440 °C. The effect of strain rate, hold time at temperature and loading sequence are investigated at each temperature. The results show that temperature has a significant effect on the cyclic deformation of Al-Si-Cu alloys. With increasing temperature, the effect of strain rate and hold time become more significant, while load sequence effects remain negligible within the investigated temperature range. Thus, an elasto-viscoplastic model is required for modeling the alloy's behavior at high temperature. This study provides an insight into the necessary information required for modeling of automotive engine components operating at elevated temperature.

Modern diesel engines employ a multitude of strategies for oxides of nitrogen (NOx) emission abatement, with exhaust gas recirculation (EGR) being one of the most effective technique. The need for a precise control on the intake charge dilution (as a result of EGR) is paramount since small fluctuations in the intake charge dilution at high EGR rates may cause larger than acceptable spikes in NOx/soot emissions or deterioration in the combustion efficiency, especially at low to mid-engine loads. The control problem becomes more pronounced during transient engine operation; currently the trend is to momentarily close the EGR valve during tip-in or tip-out events. Therefore, there is a need to understand the transient EGR behaviour and its impact on the intake charge development especially under unstable combustion regimes such as low temperature combustion.

Many approaches have been taken to determine the burning velocity in internal combustion engines. Experimentally, the burning velocity has been determined in optically accessible gasoline engines by tracking the propagation of the flame front from the spark plug to the end of the combustion chamber. These experiments are costly as they require special imaging techniques and major modifications in the engine structure. Another approach to determine the burning velocity is from 3D CFD simulation models. These models require basic information about the mechanisms of combustion which are not available for distillate fuels in addition to many assumptions that have to be made to determine the burning velocity. Such models take long periods of computational time for execution and have to be calibrated and validated through experimentation.

Emissions of Unburned Hydrocarbons (UHC) from diesel engines are a particular concern during the starting process, when after-treatment devices are typically below optimal operating temperatures. Drivability in the subsequent warm-up phase is also impaired by large cyclic fluctuations in mean effective pressure (MEP). This paper discusses in-cylinder wall temperature influence on unburned hydrocarbon emissions and combustion stability during the starting and warm-up process in an optical engine. A laser-induced phosphorescence technique is used for quantitative measurements of in-cylinder wall temperatures just prior to start of injection (SOI), which are correlated to engine out UHC emission mole fractions and combustion phasing during starting sequences over a range of charge densities, at a fixed fueling rate. Squish zone cylinder wall temperature shows significant influence on engine out UHC emissions during the warm-up process.

On-board fuel identification is important to ensure engine safe operation, similar power output, fuel economy and emissions levels when different fuels are used. Real-time detection of physical and chemical properties of the fuel requires the development of identifying techniques based on a simple, non-intrusive sensor. The measured crankshaft speed signal is already available on series engine and can be utilized to estimate at least one of the essential combustion parameters such as peak pressure and its location, rate of cylinder pressure rise and start of combustion, which are an indicative of the ignition properties of the fuel. Using a dynamic model of the crankshaft numerous methods have been previously developed to identify the fuel type but all with limited applications in terms of number of cylinders and computational resources for real time control.

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 performance of an organic Rankine cycle (ORC) that recovers heat from the exhaust of a heavy-duty diesel engine was simulated. The work was an extension of a prior study that simulated the performance of an experimental ORC system developed and tested at Oak Ridge National laboratory (ORNL). The experimental data were used to set model parameters and validate the results of that simulation. For the current study the model was adapted to consider a 15 liter turbocharged engine versus the original 1.9 liter light-duty automotive turbodiesel studied by ORNL. Exhaust flow rate and temperature data for the heavy-duty engine were obtained from Southwest Research Institute (SwRI) for a range of steady-state engine speeds and loads without EGR. Because of the considerably higher exhaust gas flow rates of the heavy-duty engine, relative to the engine tested by ORNL, a different heat exchanger type was considered in order to keep exhaust pressure drop within practical bounds.

Exhaust pressures (P3) are hard parameters to measure and can be readily estimated, the cost of the sensors and the temperature in the exhaust system makes the implementation of an exhaust pressure sensor in a vehicle control system a costly endeavor. The contention with measured P3 is the accuracy required for proper engine and vehicle control can sometimes exceed the accuracy specification of market available sensors and existing models. A turbine inlet exhaust pressure observer model based on isentropic expansion and heat transfer across a turbocharger turbine was developed and investigated in this paper. The model uses 4 main components; an open loop P3 orifice flow model, a model of isentropic expansion across the turbine, a turbine and pipe heat transfer models and an integrator with the deviation in the downstream turbine outlet parameter.

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.