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In this paper, a soft computing approach to a model-free vehicle stability control (VSC) algorithm is presented. The objective is to create a fuzzy inference system (FIS) that is robust enough to operate in a multitude of vehicle conditions (load, tire wear, alignment), and road conditions while at the same time providing optimal vehicle stability by detecting and minimizing loss of traction. In this approach, an adaptive neuro-fuzzy inference system (ANFIS) is generated using previously collected data to train and optimize the performance of the fuzzy logic VSC algorithm. This paper outlines the FIS detection algorithm and its benefits over a model-based approach. The performance of the FIS-based VSC is evaluated via a co-simulation of MATLAB/Simulink and CarSim model of the vehicle under various road and load conditions. The results showed that the proposed algorithm is capable of accurately indicating unstable vehicle behavior for two different types of vehicles (SUV and Sedan).

The recent trends of increasing driveline torque and use of traction control devices call for increasingly higher durability capacity from driveline components. Bench and vehicle durability tests are often used to validate designs, but they are not cost-effective and take months to complete. Traditional finite element analysis (FEA) procedures have been used effectively in the re-design of driveline components to reduce stress, and occasionally, to predict fatigue life. But in the case of certain rotating components, such as the Axle Differential Case, where the component sees large stress/strain fluctuations within the course of one complete rotation, even under constant input torque, historical fatigue analysis (when conducted) yields very conservative results. The axle differential case tends to be one of the weakest links in the rear axle assembly. Therefore, there is a crucial need for analytical methods to more accurately predict fatigue life to reduce testing time and cost.

A transportable instrumentation package to collect driver, vehicle and environmental data is described. This system is an improvement on an earlier system and is called TIP-II [13]. Two new modules were designed and added to the original system: a new and improved physiological signal module (PH-M) replaced the original physiological signals module in TIP, and a new hand pressure on steering wheel module (HP-M) was added. This paper reports on exploratory tests with TIP-II. Driving data were collected from ten driver participants. Correlations between On-Board-Diagnostics (OBD), video data, physiological data and specific driver behavior such as lane departure and car following were investigated. Initial analysis suggested that hand pressure, skin conductance level, and respiration rate were key indicators of lane departure lateral displacement and velocity, immediately preceding lane departure; heart rate and inter-beat interval were affected during lane changes.

This book draws upon a variety of the author's experiences during more than 25 years in automotive safety. It gives an introduction to plain film radiographs (x-rays), computed tomograms (CTs), and magnetic resonance images (MRIs) such that vehicle safety professionals can use these techniques to help piece together the puzzle and provide a better understanding of the relationship between vehicle crash scenarios and occupant injury. For those with a primarily vehicle background, Neck Injury provides an overview of how x-rays, CTs, and MRIs may be used as a source of information to help analyze vehicle crashes and the associated injuries. For those with a clinical background, the book provides insight into how injuries relate to the vehicle crash. Chapters cover: Anatomy Imaging Injuries and Injury Mechanisms

The increasing importance of safety performance in all aspects of motor vehicle design, development, manufacture and marketing makes it necessary for professionals working in these areas to be more aware of safety considerations. The background material and concepts presented in this book will be useful as a basis to aid in the understanding of future developments in this fascinating area.

Two rigid rollover test devices were constructed to have the approximate dimensions, mass and inertial properties of a mid-sized Car and Sport Utility Vehicle (SUV). The rigid devices were used to generate vehicle and occupant responses from a series of laboratory rollover tests. For each rigid rollover test, a deceleration sled was used to subject each rigid vehicle to nearly identical lateral speeds and decelerations. The rigid vehicles were limited to a single roll by tethering the vehicles to the deceleration cart. The vehicle's roll rate, roll angle, lateral acceleration and Anthropomorphic Test Devices (ATD) neck responses generated from the rigid SUV were compared to the responses of a full vehicle production SUV under similar test conditions. The rigid SUV and Car devices were then used to examine the effects of activating safety belt pre-tensioning systems and roof mounted side curtain airbags at various times on ATD neck forces and moments.

A new diesel engine, called the 6.7L Power Stroke® V-8 Turbo Diesel, and code named "Scorpion," was designed and developed by Ford Motor Company for the full-size pickup truck and light commercial vehicle markets. The combustion system includes the piston bowl, swirl level, number of nozzle holes, fuel spray angle, nozzle tip protrusion, nozzle hydraulic flow, and nozzle-hole taper. While all of these parameters could be explored through extensive hardware testing, 3-D CFD studies were utilized to quickly screen two bowl concepts and assess their sensitivities to a few of the other parameters. The two most promising bowl concepts were built into single-cylinder engines for optimization of the rest of the combustion system parameters. 1-D CFD models were used to set boundary conditions at intake valve closure for 3-D CFD which was used for the closed-cycle portion of the simulation.

With the current trend of including the evaluation of the risk of brain injuries in vehicle crashes due to rotational kinematics of the head, two injury criteria have been introduced since 2013 – BrIC and DAMAGE. BrIC was developed by NHTSA in 2013 and was suggested for inclusion in the US NCAP for frontal and side crashes. DAMAGE has been developed by UVa under the sponsorship of JAMA and JARI and has been accepted tentatively by the EuroNCAP. Although BrIC in US crash testing is known and reported, DAMAGE in tests of the US fleet is relatively unknown. The current paper will report on DAMAGE in NCAP-like tests and potential future frontal crash tests involving substantial rotation about the three axes of occupant heads. Distribution of DAMAGE of three-point belted occupants without airbags will also be discussed. Prediction of brain injury risks from the tests have been compared to the risks in the real world.

Several types of hybrid-electric vehicles have been developed at Ford Research Laboratory. Among the parallel hybrid systems with a single electric motor, two types were studied. In the first type, the electric motor was attached directly to the crankshaft (mild hybrid) [1], to enable the engine start-stop and regeneration functions. In the second type (full hybrid) the electric motor was connected to the engine through the use of a clutch to allow electric launch of the vehicle and pure electric driving at low speeds. The full hybrid powertrain described in this paper uses a more powerful electric motor for enhanced regenerative braking and engine power assist. An engine-disconnecting clutch saves energy during both the electric propulsion and during vehicle braking. When the clutch is disengaged the engine is shut-off, which eliminates the energy otherwise spent on motoring the engine during electric propulsion.