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Ford Motor Company is introducing “EcoBoost” gasoline turbocharged direct injection (GTDI) engine technology in the 2010 Lincoln MKS. A logical enhancement of EcoBoost technology is the use of E85 for knock mitigation. The subject of this paper is the optimal use of E85 by using two fuel systems in the same EcoBoost engine: port fuel injection (PFI) of gasoline and direct injection (DI) of E85. Gasoline PFI is used for starting and light-medium load operation, while E85 DI is used only as required during high load operation to avoid knock. Direct injection of E85 (a commercially available blend of ∼85% ethanol and ∼15% gasoline) is extremely effective in suppressing knock, due to ethanol's high inherent octane and its high heat of vaporization, which results in substantial cooling of the charge. As a result, the compression ratio (CR) can be increased and higher boost levels can be used.

Today's automotive and electronics technologies are evolving so rapidly that educators and industry are both challenged to re-educate the technological workforce in the new area before they are replaced with yet another generation. In early November 2009 Ford's Product Development senior management formally approved a proposal by the University of Detroit Mercy to transform 125 of Ford's “IC Engine Automotive Engineers” into “Advanced Electric Vehicle Automotive Engineers.” Two months later, the first course of the Advanced Electric Vehicle Program began in Dearborn. UDM's response to Ford's needs (and those of other OEM's and suppliers) was not only at the rate of “academic light speed,” but it involved direct collaboration of Ford's electric vehicle leaders and subject matter experts and the UDM AEV Program faculty.

Advanced High Strength Steels (AHSS) have been implemented in the automotive industry to balance the requirements for vehicle crash safety, emissions, and fuel economy. With lower ductility compared to conventional steels, the fracture behavior of AHSS components has to be considered in vehicle crash simulations to achieve a reliable crashworthiness prediction. Without considering the fracture behavior, component fracture cannot be predicted and subsequently the crash energy absorbed by the fractured component can be over-estimated. In full vehicle simulations, failure to predict component fracture sometimes leads to less predicted intrusion. In this paper, the feasibility of using computer simulations in predicting fracture during crash deformation is studied.

The adoption of the electronic controlled steering systems with new technologies has been extended in recent years. They have interactions with other complex vehicle subsystems and it is a hard task for the vehicle developer to find the best solution from huge number of the combination of parameter settings with track tests. In order to improve the efficiency of the steering system development, the authors had developed a steering bench test method for steering system using a Hardware-In-the-Loop Simulation (HILS). In the steering HILS system, vehicle dynamics simulation and the tie rod axial force calculation are required at the same time in the real-time simulation environment. The accuracy of the tie rod axial force calculation is one of the key factors to reproduce the vehicle driving condition. But the calculation cannot be realized by a commercial software for the vehicle dynamics simulation.

The vehicle interior constitutes the multi-sensory environment of driver and passengers. Beside overall design and execution, materials and its surfaces are of specific interest to the customer. They are not only needed to fulfil technical functions, but are in direct focus of the customer’s perception. The perceived quality is based on all sensory data collected by the human perceptual system. Surfaces express design intent and craftsmanship by their visual appearance. Haptic features supervene when materials are touched. And even smell has an influence on the perception of ambience. Although sound is generated nearly every time when fingers slide across a surface, touch-sounds have been disregarded so far. In various cases, these contact sounds are clearly audible. As essential sound responses to haptic activity, they can degrade perceived quality. A method has been developed for a standardized generation of touch-sounds.

Engine downsizing, boosting, direct injection and variable valve actuation, have become industry standards for reducing CO2 emissions in current production vehicles. Because of the increasing complexity of the engine air path system and the high number of degrees of freedom for engine charge management, the design of air path control algorithms has become a difficult and time consuming process. One possibility to reduce the control development time is offered by Software-in-the-Loop (SIL) or Hardware-in-the-Loop (HIL) simulation methods. However, it is significantly challenging to identify engine air path system simulation models that offer the right balance between fidelity, mathematical complexity and computational burden for SIL or HIL implementation.

This paper describes two case studies in which multiple microphone processing (beamforming) and microphone location were evaluated to determine their impact on improving embedded automatic speech recognition (ASR) in a vehicle hands-free environment. While each of these case studies was performed using slightly different evaluation set-ups, some specific and general conclusions can be drawn to help guide engineers in selecting the proper microphone location and configuration in a vehicle for the improvement of ASR. There were some outcomes that were common to both dual microphone solutions. When considering both solutions, neither was equally effective across all background noise sources. Both systems appear to be far more effective for noise conditions in which higher frequency energy is present, such as that due to high levels of wind noise and/or HVAC (heating, ventilation and air conditioning) blower noise.

This paper describes a method to validate in-vehicle speech recognition by combining synthetically mixed speech and noise samples with batch speech recognition. Vehicle cabin noises are prerecorded along with the impulse response from the driver's mouth location to the cabin microphone location. These signals are combined with a catalog of speech utterances to generate a noisy speech corpus. Several factors were examined to measure their relative importance on speech recognition robustness. These include road surface and vehicle speed, climate control blower noise, and driver's seat position. A summary of the main effects from these experiments are provided with the most significant factors coming from climate control noise. Additionally, a Signal to Noise Ratio (SNR) experiment was conducted highlighting the inverse relationship with speech recognition performance.

At various milestones during a vehicle’s development program, different CAE models are created to assess NVH error states of concern. Moreover, these CAE models may be developed in different commercial CAE software packages, each one with its own unique advantages and strengths. Fortunately, due to the wide spread acceptance that the Functional Mock-up Interface (FMI) standard gained in the CAE community over the past few years, many commercial CAE software now support cosimulation in one form or the other. Cosimulation allows performing multi-domain/multi-resolution simulations of the vehicle, thereby combining the advantages of various modeling techniques and software. In this paper, we explore cosimulation of full 3D vehicle model developed in MSC ADAMS with 1D driveline model developed in LMS AMESim. The target application of this work is investigation of vehicle NVH error states associated with both hybridized and non-hybridized powertrains.

This paper focuses on finding and analyzing the relevant parameters affecting traffic flow when autonomous vehicles are introduced for ride hailing applications and autonomous shuttles are introduced for circulator applications in geo-fenced urban areas. For this purpose, different scenarios have been created in traffic simulation software that model the different levels of autonomy, traffic density, routes, and other traffic elements. Similarly, software that specializes in vehicle dynamics, physical limitations, and vehicle control has been used to closely simulate realistic autonomous vehicle behavior under such scenarios. Different simulation tools for realistic autonomous vehicle simulation and traffic simulation have been merged together in this paper, creating a realistic simulator with Hardware-in-the-Loop (HiL), Traffic-in-the-Loop (TiL), and Software in-the-Loop (SiL) simulation capabilities.

To-date the primary challenge in conducting aerodynamic CFD simulations of actual vehicles with realistically complex geometry has been the construction of a computational mesh. The CAD-to-Mesh processes used to-date have been laborious, often requiring many weeks of engineering time. In this paper we present a new technique to greatly expedite the CAD-to-Mesh process. The fundamentals of this technique are discussed followed by case studies that show that this technique can reduce the engineering time required for the CAD-to-Mesh process to just a few hours.

A hybrid electric vehicle (HEV) system model, which directly simulates vehicle drive cycles with interactions among driver, environment, vehicle hardware and vehicle controls, is a critical CAE tool used through out the product development process to project HEV fuel economy (FE) capabilities. The accuracy of the model is essential and directly influences the HEV hardware designs and technology decisions. This ultimately impacts HEV product content and cost. Therefore, improving HEV system model accuracy and establishing high-level model-test correlation are imperative. This paper presents a Parameter Diagram (P-Diagram) based model-test correlation framework which covers all areas contributing to potential model simulation vs. vehicle test differences. The paper describes each area in detail and the methods of characterizing the influences as well as the correlation metrics.

In December 2006, Nissan announced its Nissan Green Program 2010 (NGP 2010), a mid-term environmental action plan that includes initiatives to reduce vehicle emissions. In line with this plan, the company intends to introduce a new and original hybrid system in fiscal year 2010. Specifically, this system-called the “Infiniti Direct Response Hybrid”-is a one-motor, two-clutch parallel hybrid system that eliminates the need for a torque converter. It will be featured in the 2012 Infiniti M35 Hybrid and provides the following advantages. 1 Significant improvement in fuel economy even in Highway driving 2 Better response and a more direct feeling 3 Lightweight and low cost This one-motor, two-clutch system without torque converter possesses a simple but highly capable architecture that is new to the passenger vehicle segment.

Engine dynamometer testing was performed comparing E10, E20, and E30 splash-blended fuels in a Ford 3.5L EcoBoost direct injection (DI) turbocharged engine. The engine was tested with compression ratios (CRs) of 10.0:1 (current production) and 11.9:1. In this engine, E20 (96 RON) fuel at 11.9:1 CR gave very similar knock performance to E10 (91 RON) fuel at 10:1 CR. Similarly, E30 (101 RON) fuel at 11.9:1 CR resulted in knock-limited performance equivalent to E20 at 10:1 CR, indicating that E30 could have been run at even higher CR with acceptable knock behavior. The data was used in a vehicle simulation of a 3.5L EcoBoost pickup truck, which showed that the E20 (96 RON) fuel at 11.9:1 CR offers 5% improvement in U.S. EPA Metro-Highway (M/H) and US06 Highway cycle tank-to-wheels CO₂ emissions over the E10 fuel, with comparable volumetric fuel economy (miles per gallon) and range before refueling.

A robotic driver has been designed on the basis of an analysis of a human driver's action in following a given driving schedule. The self-learning algorithm enables the robot to learn the vehicle characteristics without human intervention. Based on learned relationships, the robotic driver can determine an appropriate accelerator position and execute other operations through sophisticated calculations using the future scheduled vehicle speed and vehicle characteristics data. Compensation is also provided to minimize vehicle speed error. The robotic driver can reproduce the same types of exhaust emission and fuel economy data obtained with human drivers with good repeatability. It doesn't require long preparation time. Thereby making it possible to reduce experimentation work in the vehicle development process while providing good accuracy and reliability.

The fuel consumption of a vehicle is shown to be linearly proportional to (1) total vehicle work required to drive the cycle due to mass and acceleration, tire friction, and aerodynamic drag and (2) the powertrain (PT) mechanical losses, which are approximately proportional to the engine displaced volume per unit distance travelled (displacement time gearing). The fuel usage increases linearly with work and displacement over a wide range of applications, and the rate of increase is inversely proportional to the marginal efficiency of the engine. The theoretical basis for these predictions is reviewed. Examples from current applications are discussed, where a single PT is used across several vehicles. A full vehicle cycle simulation model also predicts a linear relationship between fuel consumption, vehicle work, and displacement time gearing and agrees well with the application data.

The brake pedal is the brake system component that the driver fundamentally has contact and through its action wait the response of the whole system. Each OEM defines during vehicle conceptualization the behavior of brake pedal that characterizes the pedal feel that in general reflects not only the characteristic from that vehicle but also from the entire brand. Technically, the term known as Pedal Feel means the relation between the force applied on the pedal, the pedal travel and the deceleration achieved by the vehicle. Such relation curves are also analyzed in conjunction with objective analysis sheets where the vehicle brake behavior is analyzed in test track considering different deceleration conditions, force and pedal travel. On technical literature, it is possible to find some data and studies considering the hydraulic brakes behavior.

Wheel Fight is the undesirable rotational response of a vehicle's steering wheel due to road input at any or all of the road/wheel tire patches. The type of road input that will cause wheel fight comes in two forms: continuous rough road surfaces such as broken concrete or transient inputs such as pot-holes and tar strips. An objective method to quantify a vehicle's wheel fight sensitivity would be of great value to the vehicle development engineer. To that end, a study was conducted on Ford's Vehicle Vibration Simulator (VVS) to gather subjective responses and use those as a basis for correlation to an objective metric. One road surface known to induce wheel fight consists of using a rubber strip and driving over it while impacting only one side of the vehicle. Under this condition, steering wheel data was acquired on five different light trucks from which paired comparison studies were conducted.

Oil formulation has been varied to modify oil viscosity characteristics; the effect on the rubbing friction losses of a 2.4litre diesel engine has been investigated for a range of temperatures from -20 to around 60°C. The aims of the study were first, to examine the extent to which viscosity alone determined the effect of formulation changes, and second, to define an effective viscosity to relate changes in viscosity due to formulation and temperature to changes in engine friction. This effective viscosity is based on cold cranking simulator measurements at -30°C, high temperature high shear viscosity at 150°C and kinematic viscosity measurements at three intermediate temperatures to define the variation with temperature. The effective viscosity has been described using a modified Vogel equation, which is presented.

This paper describes a headway distance control system for platoon driving on an automated highway system (AHS). The system implemented on a test vehicle is described first, followed by a description of a vehicle control method based on the use of throttle and brake actuators. This method makes it possible to obtain the target acceleration and deceleration regardless of the vehicle speed range and the rate of acceleration or deceleration. Experimental and simulation results obtained with this method are presented. A control method is then described that uses inter-vehicle communication and laser radar to maintain a constant headway between vehicles. The results of simulations and driving tests conducted with three vehicles are presented to illustrate that the use of inter-vehicle communication is highly effective in improving headway control performance.