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This paper presents the final phase of a study to develop the modeling methodology for an advanced steering assembly with a safety-enhanced steering wheel and an adaptive energy absorbing steering column. For passenger cars built before the 1960s, the steering column was designed to control vehicle direction with a simple rigid rod. In severe frontal crashes, this type of design would often be displaced rearward toward the driver due to front-end crush of the vehicle. Consequently, collapsible, detachable, and other energy absorbing steering columns emerged to address this type of kinematics. These safety-enhanced steering columns allow frontal impact energy to be absorbed by collapsing or breaking the steering columns, thus reducing the potential for rearward column movement in severe crashes. Recently, more advanced steering column designs have been developed that can adapt to different crash conditions including crash severity, occupant mass/size, seat position, and seatbelt usage.

Motivated by a combination of increasing consumer demand for fuel efficient vehicles, more stringent greenhouse gas, and anticipated future Corporate Average Fuel Economy (CAFE) standards, automotive manufacturers are working to innovate in all areas of vehicle design to improve fuel efficiency. In addition to improving aerodynamics, enhancing internal combustion engines and transmission technologies, and developing alternative fuel vehicles, reducing vehicle weight by using lighter materials and/or higher strength materials has been identified as one of the strategies in future vehicle development. Weight reduction in vehicle components, subsystems and systems not only reduces the energy needed to overcome inertia forces but also triggers additional mass reduction elsewhere and enables mass reduction in full vehicle levels.

The Service Bay Diagnostic System (SBDS) will be designed to assist the dealership technician in diagnosing and repairing Ford Motor vehicles. The system hardware will be configured around a Service Bay Computer with mass storage capability and auxiliary service equipment. Major system features include: guided service writer/customer interaction, interactive vehicle diagnostics, information management. capabilities, and an additional aid to identifying intermittent failures through the use of a portable over-the-road data acquisition device. In order to assist the technician in properly diagnosing the causal factor, the Service Bay Computer System will also be enhanced through the use of an expert system knowledge base.

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.

Since the environment of vehicle operation is dynamic in nature, dynamic methods should be used in vehicle durability analysis. Due to the constraints in current computer resources, simulation of vehicle durability tests and structural fatigue life assessment need special approaches and efficient CAE tools. The purpose of this paper is to present an efficient methodology and a feasible vehicle dynamic durability analysis process. Two examples of structural durability analysis using transient dynamics are given. The examples show that vehicle stress analysis and fatigue life prediction using dynamic method is now feasible by employing the presented method and process.

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.

When considering ride comfort and precision there are lots of components in the vehicle suspensions that have influence in this behavior and some ride occurrences (mainly higher frequencies) are rubber bushing responsibility but due their compliance, other vehicle attributes, steering and handling, can be affected. So the correct components tuning can maintain or improve vehicle attributes to address desired brand DNA and vehicle its specific needs. These studies were done considering the elastokinematics of front axle only due need of improve its comfort concerning higher frequencies (impacts and harshness). In addiction, correlation between subjective evaluation and objective data acquisition/post processing is desirable to optimize development time. Based in subjective directional, the activities time was reduced and final configuration reached faster.

Seat Effective Amplitude Transmissibility (SEAT) values can be obtained from direct measurements at seat track and top or estimated from transmissibility data and seat track input. Vertical transmissibility was measured for sixteen seats and six subjects on the Ford Vehicle Vibration Simulator, and these 96 functions used to estimate the seat top response for rough road input. SEAT values were calculated, and good correlation to values computed from direct seat top measurements obtained (R2 of 0.86). Averaging transmissibilities and direct seat measurements over the 6 subjects to obtain correlations for the 16 seats improved R2 to 0.94, validating this approach.

This paper proposes a novel algorithm. This algorithm is called Self-Organizing Fuzzy Neural Network (SOFNN). SOFNN revolutionizes how researchers apply control theories, image/signal processing on control systems and other applications. In general, SOFNN is an identification technique that automatically initiates, builds and fine-tunes the required network parameters. SOFNN evaluates required structures without predefined parameters or expressions regarding systems. SOFNN sets out to learn and configure a system's characteristics. Self-constructing and self-tuning features enable SOFNN to handle complex, non-linear, and time-varying systems with higher accuracy, making systems identification easier. SOFNN constructs and fine-tunes the system parameter through two phases. The two phases are the construction and the parameter-tuning phase. The two phases run concurrently allowing SOFNN to identify systems on-line.

A flexible, easily configuration data acquisition system was designed and built for detailed studies of the steady state and dynamic properties of lean NOx traps for an engine dynamometer environment. The system is based on the industry standard VXI backplane. The overriding design philosophy was to design and develop a data acquisition system that was user friendly and could be operated easily by engine laboratory technicians, as well as by test engineers. The primary requirements guiding the design were the following: (1) the ability easily to configure, save, recall, modify, and print test configurations. (2) The ability to configure the gain, channel name, and engineering units for each analog channel. (3) The ability to trigger from one analog input channel. (4) A provision for numeric auto-incrementing of data file names. (5) The ability to save data in Excel™ compatible ASCII format. (6) The utilization of off-the shelf VXI hardware.

Drive shaft modelling effects frontal crash finite element simulation. A 35 mph rigid barrier impact of a body on frame SUV with an one piece drive shaft and a unibody SUV with a two piece drive shaft have been studied and simulated using finite element analyses. In the model, the drive shaft can take significant load in frontal impact crash. Assumptions regarding the drive shaft model can change the predicted engine motion in the simulation. This change influences the rocker @ B-pillar deceleration. Two modelling methods have been investigated in this study considering both joint mechanisms and material failure in dynamic impact. Model parameters for joint behavior and failure should be determined from vehicle design information and component testing. A body on frame SUV FEA model has been used to validate the drive shaft modeling technique by comparing the simulation results with crash test data.

An experimental study of the performance of a reverse tumble, DISI engine is reported. Specific fuel consumption and engine-out emissions have been investigated for both homogeneous and stratified modes of fuel injection. Trends in performance with varying AFR, EGR, spark and injection timings have been explored. It is shown that neural networks can be trained to describe these trends accurately for even the most complex case of stratified charge operation with exhaust gas recirculation.

The Vehicle Exhaust Emissions Simulator was developed to evaluate the performance of vehicle emissions sampling and analytical systems. The simulator produces a representative tailpipe volume flow rate containing up to five emission constituents, injected via mass flow controllers (MFCs). Eliminating the variability of test results associated with the vehicle, driver, and dynamometer makes the simulator an ideal quality control tool for use in commissioning new test cells, checking data correlation between test cells, and evaluating overall system performance. Earlier vehicle emissions simulators being used in the industry were primarily for checking Constant Volume Samplers (CVSs) and Bag Benches but they did not have the ability to properly simulate tailpipe volume.

A number of advancements have been made in the coulometric sulfur trace instrumental technique for the real-time measurement of engine oil economy. These advancements include modification of the coulometric cell to improve reliability and reproducibility. The instrument has been interfaced with a microcomputer for instrument control as well as data acquisition, storage, and analysis. Studies were undertaken which demonstrate sufficient sensitivity and linearity for determination of engine oil economy at levels better than 10,000 miles/quart. Applications to steady-state engine oil consumption mapping and to instantaneous oil consumption during transient engine cycling are described. These instruments are being produced by an outside supplier for use in various company locations in both the engine production and engine research environments.

Most people still remember the introduction of the IBM PC in 1981 and the first Microsoft Windows operating system in 1985. These were the pioneering technologies that started a revolution in automotive test equipment in the service bay. What was once a purely mechanical garage environment where information was published annually in large paper manuals has evolved into a highly technical computing environment. Today vehicle networks link onboard vehicle control systems with diagnostic systems and updated service information is published daily over the Internet. A lot has changed over the last twenty years, and manufacturers of diagnostic test equipment are learning to deal with the constantly evolving computing platforms and host operating systems. This paper traces the history of automotive diagnostic equipment at Ford Motor Company and shares some of the hard lessons learned from the early systems.

This paper is the second in the series of documents designed to record the progress of a series of SAE documents - SAE J2836™, J2847, J2931, & J2953 - within the Plug-In Electric Vehicle (PEV) Communication Task Force. This follows the initial paper number 2010-01-0837, and continues with the test and modeling of the various PLC types for utility programs described in J2836/1™ & J2847/1. This also extends the communication to an off-board charger, described in J2836/2™ & J2847/2 and includes reverse energy flow described in J2836/3™ and J2847/3. The initial versions of J2836/1™ and J2847/1 were published early 2010. J2847/1 has now been re-opened to include updates from comments from the National Institute of Standards Technology (NIST) Smart Grid Interoperability Panel (SGIP), Smart Grid Architectural Committee (SGAC) and Cyber Security Working Group committee (SCWG).

Downhill tests are widely used as a method of evaluation, development and validation of braking efficiency, friction pair durability, braking balance, as well as fade characteristics and recovery of friction material properties. This test procedure is used for both: passenger vehicles and light & heavy commercial vehicles. The energy levels in the brake system are higher on commercial vehicles and the thermal characteristics much more critical. Added to the fact that such tests are conducted on public highways, it has an intrinsic security risk for both the vehicle tested and all others around. Until a few years ago, it was still feasible to conduct tests downhill on different routes keeping a high security level. Given an increasing traffic on highways, where the test is currently carried out, a need to create a similar downhill procedure (called Guaporé Mountain Test) within a Proving Ground under controlled conditions has been noticed.

To better reflect real world driving conditions, the EPA 5-Cycle Fuel Economy method encompasses high vehicle speeds, aggressive vehicle accelerations, climate control system use and cold temperature conditions in addition to the previously used standard City and Highway drive cycles in the estimation of vehicle fuel economy. A standard Powersplit Hybrid Electric Vehicle (HEV) system simulation environment has long been established and widely used within Ford to project fuel economy for the standard EPA City and Highway cycles. Direct modeling and simulation of the complete 5-Cycle fuel economy test set for HEV's presents significant new challenges especially with respect to modeling vehicle thermal management system and interactions with HEV features and system controls. It also requires a structured, systematic approach to validate the key elements of the system models and complete vehicle system simulations.

The viscous criterion (V*C) has been proposed by biomechanics researchers as a generic biomechanical index for potential soft tissue injury. It is defined by the product of the velocity of deformation and the instantaneous compression of torso and abdomen. This criterion requires calculation and differentiation of measured torso/abdomen compression data. Various computational algorithms for calculating viscous criterion are reviewed and evaluated in this paper. These include methods developed by Wayne State University (WSU), NHTSA (DOT) and Ford. An evaluation has been conducted considering the accuracy of these algorithms with both theoretical and experimental data from dummy rib compressions obtained during a crash test. Based on these results, it is found that: V*C results depend on the scheme used in the computation process, the sampling rate and filtering of original raw data. The NHTSA method yields the lowest V*C value.

Proving Ground cyclic testing was used to evaluate vehicles assembled with electrogalvanized and organic composite coated electrogalvanized steel. These same materials, along with several commonly available precoated steels, were also evaluated as hem flange assemblies on towed trailers at the Proving Ground. Testing was terminated as perforation of some of the assemblies occurred. Pitting depth was used to quantitatively evaluate metal loss.