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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 use of model-based software development in automotive applications has increased in recent years. Current vehicles contain millions of lines of code, and millions of dollars are spent each year fixing software issues. Most new features are software controlled and many times include distributed functionality, resulting in increased vehicle software content and accelerated complexity. To handle rapid change, OEMs and suppliers must work together to accelerate software development and testing. As development processes adapt to meet this challenge, model-based design can provide a solution. Model-based design is a broad development approach that is applied to a variety of applications in various industries. This paper reviews a project using the MATLAB/Simulink/Stateflow environment to complete a functional model of a low cost radio.

Battery temperature variations have a strong effect on both battery aging and battery performance. Significant temperature variations will lead to different battery behaviors. This influences the performance of the Hybrid Electric Vehicle (HEV) energy management strategies. This paper investigates how variations in battery temperature will affect Lithium-ion battery aging and fuel economy of a HEV. The investigated energy management strategy used in this paper is the Equivalent Consumption Minimization Strategy (ECMS) which is a well-known energy management strategy for HEVs. The studied vehicle is a Honda Civic Hybrid and the studied battery, a BLS LiFePO4 3.2Volts 100Ah Electric Vehicle battery cell. Vehicle simulations were done with a validated vehicle model using multiple combinations of highway and city drive cycles. The battery temperature variation is studied with regards to outside air temperature.

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.

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.

The hazard analysis for the Stop-Start control strategy of a Micro-Hybrid vehicle with manual gearbox is presented. The strategy allows for stops in gear and in neutral; this leads to specific hazards. Implications for the architecture of the electronic control unit, the software architecture, and the development process, especially software testing, are discussed.

To achieve optimal axial and bending crush performance using dual phase steels for components designed for crash energy absorption and/or intrusion resistance applications, the cross sections of the components need to be optimized. In this study, Altair HyperMorph™ and HyperStudy® optimization software were used in defining the shape design variables and the optimization problem setup, and non-linear finite element code LS-DYNA® software was used in crush simulations. Correlated crash simulation models were utilized and the square cross-section was selected as the baseline. The optimized cross-sections for bending and axial crush performance resulted in significant mass and cost savings, particularly with the application of dual phase steels.

The United States Department of Transportation (USDOT) and the Crash Avoidance Metrics Partnership-Vehicle Safety Communications 2 (CAMP-VSC2) Consortium (Ford, General Motors, Honda, Mercedes-Benz, and Toyota) initiated, in December 2006, a three-year collaborative effort in the area of wireless-based safety applications under the Vehicle Safety Communications-Applications (VSC-A) Project. The VSC-A Project developed and tested Vehicle-to-Vehicle (V2V) communications-based safety systems to determine if Dedicated Short Range Communications (DSRC) at 5.9 GHz, in combination with vehicle positioning, would improve upon autonomous vehicle-based safety systems and/or enable new communications-based safety applications.

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.

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.

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 Kalman and Vold-Kalman order tracking filters have been implemented in commercial software since the early 90's. There are several mathematical formulations of filters that have been implemented by different software vendors. However, there have not been any papers that have been published which sufficiently explain the math behind these filters and discuss the actual implementations of the filters in software. In addition, upon generating the equations represented by these filters, solving the equations for datasets in excess of several hundred thousand datapoints is not trivial and has not been discussed in the literature. The papers which have attempted to cover these topics are generally vague and overly mathematically eloquent but not easily understandable by a practicing engineer.

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.

Auto-manufacturers are under increasing pressure to develop powertrain systems for automotive vehicles, which are more efficient regarding fuel consumption, less polluting and still keep high performance levels. Hybrid electrical vehicles (HEV) are considered the most promising technology in sight, considering a time horizon of more ore less twenty years. HEVs combine benefits of electrical vehicles, such zero emission, low noise and high torques at low velocities and advantages of conventional vehicles, such as large autonomy, great reliability and high levels of performance. This paper is focused on the major elements of an HEV powertrain: electrical motors, internal combustion engine (ICE) and batteries, which are described. The paper also presents a comparison of two possible HEV configurations: series and parallel. The mathematical model of a small hybrid vehicle is developed using software ADVISOR.

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.

The Time Variant Discrete Fourier Transform was implemented as a real-time order tracking method using developed software and commercially available hardware. The time variant discrete Fourier transform (TVDFT) with the application of the orthogonality compensation matrix allows multiple tachometers to be tracked with close and/or crossing orders to be separated in real-time. Signal generators were used to create controlled experimental data sets to simulate tachometers and response channels. Computation timing was evaluated for the data collection procedure and each of the data processing steps to determine how each part of the process affects overall performance. Many difficulties are associated with a real-time data collection and analysis tool and it becomes apparent that an understanding of each component in the system is required to determine where time consuming computation is located.