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This paper presents the application of a proposed fuzzy inference system as part of a stability control design scheme implemented with active steering actuator sets. The fuzzy inference system is used to detect the level of overseer/understeer at the high level and a speed-adaptive activation module determines whether an active front steering, active rear steering, or active 4 wheel steering is suited to improve vehicle handling stability. The resulting model-free system is capable of minimizing the amount of model calibration during the vehicle stability control development process as well as improving vehicle performance and stability over a wide range of vehicle and road conditions. A simulation study will be presented that evaluates the proposed scheme and compares the effectiveness of active front steer (AFS) and active rear steer (ARS) in enhancing the vehicle performance. Both time and frequency domain results are presented.

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.

In the thermal expansion valve (TXV) refrigerant system, transient high-pitched whistle around 6.18 kHz is often perceived following air-conditioning (A/C) compressor engagements when driving at higher vehicle speed or during vehicle acceleration, especially when system equipped with the high-efficiency compressor or variable displacement compressor. The objectives of this paper are to conduct the noise source identification, investigate the key factors affecting the whistle excitation, and understand the mechanism of the whistle generation. The mechanism is hypothesized that the whistle is generated from the flow/acoustic excitation of the turbulent flow past the shallow cavity, reinforced by the acoustic/structural coupling between the tube structural and the transverse acoustic modes, and then transmitted to evaporator. To verify the mechanism, the transverse acoustic mode frequency is calculated and it is coincided to the one from measurement.

Driveline plunge mechanism dynamics has a significant contribution to the driver's perceivable transient NVH error states and to the transmission shift quality. As it accounts for the pitch or roll movements of the front powerplant and rear drive unit, the plunging joints exhibit resisting force in the fore-aft direction under various driveline torque levels. This paper tackles the difficult task of quantifying the coefficient of static friction and the coefficient of dynamic friction in a simple to use metric as it performs in the vehicle. The comparison of the dynamic friction to the static friction allows for the detection of the occurrence of stick-slip in the slip mechanism; which enables for immediate determination of the performance of the design parameters such as spline geometry, mating parts fit and finish, and lubrication. It also provides a simple format to compare a variety of designs available to the automotive design engineer.

Drivelines used in modern pickup trucks commonly employ universal joints. This type of joint is responsible for second driveshaft order vibrations in the vehicle. Large displacements of the joint connecting the driveline and the rear axle have a detrimental effect on vehicle NVH. As leaf springs are critical energy absorbing elements that connect to the powertrain, they are used to restrain large axle windup angles. One of the most common types of leaf springs in use today is the multi-stage parabolic leaf spring. A simple SAE 3-link approximation is adequate for preliminary studies but it has been found to be inadequate to study axle windup. A vast body of literature exists on modeling leaf springs using nonlinear FEA and multibody simulations. However, these methods require significant amount of component level detail and measured data. As such, these techniques are not applicable for quick sensitivity studies at design conception stage.

OEMs are racing to develop lightweight vehicles as government regulations now mandate automakers to nearly double the average fuel economy of new cars and trucks by 2025. Lightweight materials such as aluminum, magnesium and carbon fiber composites are being used as structural members in vehicle body and suspension components. The reduction in weight in structural panels increases noise transmission into the passenger compartment. This poses a great challenge in vehicle sound package development since simply increasing weight in sound package components to reduce interior noise is no longer an option [1]. This paper discusses weight saving approaches to reduce noise level at the sources, noise transmission paths, and transmitted noise into the passenger compartment. Lightweight sound package materials are introduced to treat and reduce airborne noise transmission into multi-material lightweight body structure.

Electric vehicles are receiving considerable attention because they offer a more efficient and sustainable transportation alternative compared to conventional fossil-fuel powered vehicles. Since the battery pack represents the primary energy storage component in an electric vehicle powertrain, it requires accurate monitoring and control. In order to effectively estimate the battery pack critical parameters such as the battery state of charge (SOC), state of health (SOH), and remaining capacity, a high-fidelity battery model is needed as part of a robust SOC estimation strategy. As the battery degrades, model parameters significantly change, and this model needs to account for all operating conditions throughout the battery's lifespan. For effective battery management system design, it is critical that the physical model adapts to parameter changes due to aging.

Designing a vehicle body involves meeting numerous performance requirements related to different attributes such as NVH, Durability, Safety, and others. Multi-Disciplinary Optimization (MDO) is an efficient way to develop a design that optimizes vehicle performance while minimizing the weight. Since a body design evolves in course of the product development cycle, it is essential to repeat the MDO process several times as a design matures and more accurate data become available. This paper presents a real life application of the MDO process to reduce weight while optimizing performance over the design cycle of the 2015 Mustang. The paper discusses the timing and results of the applied Multi-Disciplinary Optimization process. The attributes considered during optimization include Safety, Durability and Body NVH. Several iterations of MDO have been performed at different milestones in the design cycle leading to a significant weight reduction of the already optimized design by over 16kg.

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.

This paper presents a numerical study of trace knocking combustion of ethanol/gasoline blends in a modern, single cylinder SI engine. Results are compared to experimental data from a prior, published work [1]. The engine is modeled using GT-Power and a two-zone combustion model containing detailed kinetic models. The two zone model uses a gasoline surrogate model [2] combined with a sub-model for nitric oxide (NO) [3] to simulate end-gas autoignition. Upstream, pre-vaporized fuel injection (UFI) and direct injection (DI) are modeled and compared to characterize ethanol's low autoignition reactivity and high charge cooling effects. Three ethanol/gasoline blends are studied: E0, E20, and E50. The modeled and experimental results demonstrate some systematic differences in the spark timing for trace knock across all three fuels, but the relative trends with engine load and ethanol content are consistent. Possible reasons causing the differences are discussed.

This paper proposes an approach to determine driver's driving behavior, style or habit during vehicle handling maneuvers and heavy traction and braking events in real-time. It utilizes intelligence inferred from driver's control inputs, vehicle dynamics states, measured signals, and variables processed inside existing control modules such as those of anti-lock braking, traction control, and electronic stability control systems. The algorithm developed for the proposed approach has been experimentally validated and shows the effectiveness in characterizing driver's handling behavior. Such driver behavior can be used for personalizing vehicle electronic controls, driver assistant and active safety systems, and the other vehicle control features.

Side swipe accidents occur primarily when drivers attempt an improper lane change, drift out of lane, or the vehicle loses lateral traction. Past studies of lane change detection have relied on vehicular data, such as steering angle, velocity, and acceleration. In this paper, we use three physiological signals from the driver to detect lane changes before the event actually occurs. These are the electrocardiogram (ECG), galvanic skin response (GSR), and respiration rate (RR) and were determined, in prior studies, to best reflect a driver's response to the driving environment. A novel system is proposed which uses a Granger causality test for feature selection and a neural network for classification. Test results showed that for 30 lane change events and 60 non lane change events in on-the-road driving, a true positive rate of 70% and a false positive rate of 10% was obtained.

Aftertreatment system design involves multiple tradeoffs between engine performance, fuel economy, regulatory emission levels, packaging, and cost. Selection of the best design solution (or “architecture”) is often based on an assumption that inherent catalyst activity is unaffected by location within the system. However, this study acknowledges that catalyst activity can be significantly impacted by location in the system as a result of varying thermal exposure, and this in turn can impact the selection of an optimum system architecture. Vehicle experiments with catalysts aged over a range of mild to moderate to severe thermal conditions that accurately reflect select locations on a vehicle were conducted on a chassis dynamometer. The vehicle test data indicated CO and NOx could be minimized with a catalyst placed in an intermediate location.

Modification of gasoline blendstock composition in preparing ethanol-gasoline blends has a significant impact on vehicle exhaust emissions. In “splash” blending the blendstock is fixed, ethanol-gasoline blend compositions are clearly defined, and effects on emissions are relatively straightforward to interpret. In “match” blending the blendstock composition is modified for each ethanol-gasoline blend to match one or more fuel properties. The effects on emissions depend on which fuel properties are matched and what modifications are made, making trends difficult to interpret. The purpose of this paper is to illustrate that exclusive use of a match blending approach has fundamental flaws. For typical gasolines without ethanol, the distillation profile is a smooth, roughly linear relationship of temperature vs. percent fuel distilled.

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.

Engine dynamometer testing was performed comparing fuels having different octane ratings and ethanol content in a Ford 3.5L direct injection turbocharged (EcoBoost) engine at three compression ratios (CRs). The fuels included midlevel ethanol “splash blend” and “octane-matched blend” fuels, E10-98RON (U.S. premium), and E85-108RON. For the splash blends, denatured ethanol was added to E10-91RON, which resulted in E20-96RON and E30-101 RON. For the octane-matched blends, gasoline blendstocks were formulated to maintain constant RON and MON for E10, E20, and E30. The match blend E20-91RON and E30-91RON showed no knock benefit compared to the baseline E10-91RON fuel. However, the splash blend E20-96RON and E10-98RON enabled 11.9:1 CR with similar knock performance to E10-91RON at 10:1 CR. The splash blend E30-101RON enabled 13:1 CR with better knock performance than E10-91RON at 10:1 CR. As expected, E85-108RON exhibited dramatically better knock performance than E30-101RON.

The purpose of this work is to analytically investigate automotive exhaust system noise generation and propagation phenomena. The turbulent exhaust gas flow interacts with the exhaust system structure, and as a result of this interaction, the structure vibrates and radiates noise. In the meantime, pressure wave becomes acoustic wave at its outlet. This study focuses on an exhaust system and carrying out transient fluid-structure analysis by using an explicit finite element solver that is capable of solving the Navier Stokes equations for turbulent, compressible viscous fluids as well as the field equations for solid structures in a fully coupled fashion. The time domain signals obtained from the transient analysis are post-processed to yield frequency domain data, sound pressure levels, noise source pattern as well as the selected acoustic field contour snapshots.

The aluminum alloy 7075-T6 has the potential to be used for structural automotive body components as an alternative to boron steel. Although this alloy shows poor formability at room temperature, it has been demonstrated that hot stamping is a feasible sheet metal process that can be used to overcome the forming issues. Hot stamping is an elevated temperature forming operation in which a hot blank is formed and quenched within a stamping die. Attaining a high quench rate is a critical step of the hot stamping process and corresponds to maximum strength and corrosion resistance. This work looks at measuring the quench rate of AA7075-T6 by way of three different approaches: water, a water-cooled plate, and a bead die. The water-cooled plate and the bead die are laboratory-scale experimental setups designed to replicate the hot stamping/die quenching process.

The ability to operate a spark-ignition (SI) engine near the knock limit provides a net reduction of engine fuel consumption. This work presents a real-time knock control system based on stochastic knock detection (SKD) algorithm. The real-time stochastic knock control (SKC) system is developed in MATLAB Simulink, and the SKC software is integrated with the production engine control strategy through ATI's No-Hooks. The SKC system collects the stochastic knock information and estimates the knock level based on the distribution of knock intensities fitting to a log-normal (LN) distribution. A desired knock level reference table is created under various engine speeds and loads, which allows the SKC to adapt to changing engine operating conditions. In SKC system, knock factor (KF) is an indicator of the knock intensity level. The KF is estimated by a weighted discrete FIR filter in real-time.