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The research objective was to measure and understand the preferred seat position of older drivers and younger drivers within their personal vehicles to influence recommended practices and meet the increased safety needs of all drivers. Improper selection of driver’s seat position may impact safety during a crash event and affect one’s capacity to see the roadway and reach the vehicle’s controls, such as steering wheel, accelerator, brake, clutch, and gear selector lever. Because of the stature changes associated with ageing and the fact that stature is normally distributed for both males and females, it was hypothesized that the SAE J4004 linear regression would be improved with the inclusion of gender and age terms that would provide a more accurate model to predict the seat track position of older drivers. Participants included 97 older drivers over the age of 60 and 20 younger drivers between the ages of 30 to 39.

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.

This set consists of three books, Design of Automotive Composites, CAE Design and Failure Analysis of Automotive Composites, and Biocomposites in Automotive Applications all developed by Dr. Charles Lu and Dr. Srikanth Pilla. Design of Automotive Composites reports successful designs of automotive composites occurred recently in this arena, CAE Design and Failure Analysis of Automotive Composites focuses on the latest use of CAE (Computer-Aided Engineering) methods in design and failure analysis of composite materials and structures, and Biocomposites in Automotive Applications, focuses on processing and characterization of biocomposites, their application in the automotive industry and new perspectives on automotive sustainability. Together, they are a focused collection providing the reader with must-read technical papers, hand-picked by the editors, supporting the growing importance of the use of composites in the ground vehicle industry. Dr. Charles Lu is H.E.

The automotive sector has taken a keen interest in lightweighting as new required performance standards for fuel economy come into place. This strategy includes parts consolidation, design optimization, and material substitution, with sustainable polymers playing a major role in reducing a vehicle’s weight. Sustainable polymers are largely biodegradable, biocompatible, and sourced from renewable plant and agricultural stocks. A facile way to enhance their properties, so they can indeed replace the ones made from fossil fuels, is by reinforcing them with fibers to make composites. Natural fibers are gaining more acceptance in the industry due to their renewable nature, low cost, low density, low energy consumption, high specific strength and stiffness, CO2 sequestration potential, biodegradability, and less wear imposed on machinery. Biocomposites then become a very feasible way to help address the fuel consumption challenge ahead of us.

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.

The highly transient operational nature of passenger car engines makes cylinder pressure based feedback control of combustion phasing difficult. The problem is further complicated by cycle-to-cycle combustion variation. A method for fast and accurate differentiation of normal combustion variations and true changes in combustion phasing is addressed in this research. The proposed method combines the results of a feed forward combustion phasing prediction model and “noisy” measurements from cylinder pressure using an iterative estimation technique. A modified version of an Extended Kalman Filter (EKF) is applied to calculate optimal estimation gain according to the stochastic properties of the combustion phasing measurement at the corresponding engine operating condition. Methods to improve steady state CA50 estimation performance and adaptation to errors are further discussed in this research.

As engines are equipped with an increased number of control actuators to meet fuel economy targets, they become more difficult to control and calibrate. The additional complexity created by a larger number of control actuators motivates the use of physics-based control strategies to reduce calibration time and complexity. Combustion phasing, as one of the most important engine combustion metrics, has a significant influence on engine efficiency, emissions, vibration and durability. To realize physics-based engine combustion phasing control, an accurate prediction model is required. This research introduces physics-based control-oriented laminar flame speed and turbulence intensity models that can be used in a quasi-dimensional turbulent entrainment combustion model. The influence of laminar flame speed and turbulence intensity on predicted mass fraction burned (MFB) profile during combustion is analyzed.

Smart thermal management systems can positively impact the performance, fuel economy, and reliability of internal combustion engines. Advanced cooling systems typically feature multiple computer controlled actuators - a three way smart valve, a variable speed pump, and a variable speed electric radiator fan(s). To investigate the contributions of these electro-mechanical devices, a scale multifunction test bench was constructed which integrated these actuators, accompanying system sensors, and a controllable engine thermal load with real time data acquisition and control hardware/software. This paper presents a series of experimental studies that focus on the engine's thermal transient response to various actuators input control combinations. The test results established a basis for several key operating conclusions.

The components in a hybrid electric vehicle (HEV) powertrain include the battery pack, an internal combustion engine, and the electric machines such as motors and possibly a generator. These components generate a considerable amount of heat during driving cycles. A robust thermal management system with advanced controller, designed for temperature tracking, is required for vehicle safety and energy efficiency. In this study, a hybridized mid-size truck for military application is investigated. The paper examines the integration of advanced control algorithms to the cooling system featuring an electric-mechanical compressor, coolant pump and radiator fans. Mathematical models are developed to numerically describe the thermal behavior of these powertrain elements. A series of controllers are designed to effectively manage the battery pack, electric motors, and the internal combustion engine temperatures.

According to the National Highway Traffic Safety Administration (NHTSA), motor collisions account for nearly 2.4 million injuries and 37 thousand fatalities each year in the United States. A great deal of research has been done in the area of vehicular safety, but very little has been completed to ensure licensed drivers are properly trained. Given the inherent risks in driving itself, the test for licensure should be uniform and consistent. To address this issue, an inexpensive, portable data acquisition and analysis system has been developed for the evaluation of driver performance. A study was performed to evaluate the system, and each participant was given a normalized driver rating. The average driver rating was μ=55.6, with a standard deviation of σ=12.3. All but 3 drivers fell into the so-called “Target Zone”, defined by a Driver Rating of μ± 1σ.

Driver modeling is essential to both vehicle design and control unit development. It can improve the understanding of human driving behavior and decrease the cost and risk of vehicle system verification and validation. In this paper, three driver models were implemented to simulate the behavior of drivers subject to a run-off-road recovery event. Target path planning, pursuit behavior, compensate behavior, physical limitations, and neuromuscular modeling were taken into consideration in the feedforward/feedback driver model. A transfer function driver model and a cost function based driver model from a popular vehicle simulation software were also simulated and a comparison of these three models was made. The feedforward/feedback driver model exhibited the best balance of performance with smallest overshoot (0.226m), medium settling time (1.20s) and recovery time (4.30s).

Driving skills and driving experience develop differently between a civilian and a military service member. Since 2000, the Department of Defense reports that two-thirds of non-related to war fatalities among active duty service members were due to transportation-related incidents. In addition, vehicle crashes are the leading non-related to war cause of both fatalities and serious injuries among active duty Marines. A pilot safe driving program for Marines was jointly developed by the Richard Petty Driving Experience and Clemson University Automotive Safety Research Institute. The pilot program includes four modules based on leading causes of vehicle crashes, and uses classroom and behind the wheel components to improve and reinforce safe driving skills and knowledge. The assessment results of this pilot program conducted with 192 Marines in September 2011 at Camp LeJeune, NC are presented and discussed.

The recent advent of highly effective drilling and extraction technologies has decreased the price of natural gas and renewed interest in its use for transportation. Of particular interest is the conversion of dedicated diesel engines to operate on dual-fuel with natural gas injected into the intake manifold. Dual-fuel systems with natural gas injected into the intake manifold replace a significant portion of diesel fuel energy with natural gas (generally 50% or more by energy content), and produce lower operating costs than diesel-only operation. Diesel-natural gas engines have a high compression ratio and a homogeneous mixture of natural gas and air in the cylinder end gases. These conditions are very favorable for knock at high loads. In the present study, knock prediction concepts that utilize a single step Arrhenius function for diesel-natural gas dual-fuel engines are evaluated.

Design of Automotive Composites reports that successful designs of automotive composites occurred recently in this arena. The chapters consist of eleven technical papers selected from the Automotive Composites and other relevant sessions that the editors have been organizing for the SAE International World Congress over the past five years. The book is divided into four sections: o Body Structures o Powertrain Components o Suspension Components o Electrical and Alternative Vehicle Components The composite design examples presented in Design of Automotive Composites come from the major OEMs and top-tier suppliers and are most relevant to the automotive materials challenges currently faced by the industry. Many of the innovative ideas have already been implemented on existing or new model vehicles, although a great deal of innovation is still in the works.

In this paper, the Finite Element Method (FEM) is used to model and simulate the dynamic interaction between non-pneumatic tire and sand with obstacle to investigate the influence of obstacle on performance of the non-pneumatic tire. The non-pneumatic tire consists of three major components: two inextensible circumferential membranes, a critical shear beam, and a group of deformable spokes. The non-pneumatic tire fabricated of segmented cylinders is illustrated and the FEM model for the tire is given in detail. The tire is treated as an elastic deformable body with the inertia effect included. Lebanon sand found in New Hampshire is used in this simulation because of the availability of a complete set of material properties in the literature. Modified Drucker-Prager/Cap plasticity constitutive law with hardening is utilized to model the sand. The obstacle is represented as an elastic body.

Motor vehicle crashes involving novice drivers are significantly higher than matured driver incidents as reported by the National Highway Traffic Safety Administration Fatality Analysis Reporting System (NHTSA-FARS). Researchers around the world and the United States are focused on how to decrease crashes for this driver demographic. Novice drivers usually complete driver education classes as a pre-requisite for full licensure to improve overall knowledge and safety. However, compiled statistics still indicate a need for more in-depth training after full licensure. An opportunity exists to supplement in-vehicle driving with focused learning modules using automotive simulators. In this paper, a training program for “Following Etiquette” and “Situational Awareness” was developed to introduce these key driving techniques and to complete a feasibility study using a driving simulator as the training tool.

Hydrostatic (hydraulic hybrid) drives have demonstrated energy efficiency and emissions reduction benefits. This paper investigates the potential of an independent hydrostatic wheel drive system for implementing a traction-based vehicle lateral stability control system. The system allows an upper level vehicle stability controller to produce a desired corrective yaw moment via a differential distribution of torque to the independent wheel motors. In cornering maneuvers that require braking on any one wheel of the vehicle, the motors can be operated as pumps for re-generating energy into an on-board accumulator. This approach avoids or reduces activation of the friction brakes, thereby reducing energy waste as heat in the brake pads and offering potential savings in brake maintenance costs. For this study, a model of a 4×4 hydrostatic independent wheel drive system is constructed in a causal and modular fashion and is coupled to a 7 DOF vehicle handling dynamics model.

In an effort to build a shear band of a lunar rover wheel which operates at lunar surface temperatures (40 to 400K), the design of a metallic cellular shear band is suggested. Six representative honeycombs with aluminum alloy (7075-T6) are tailored to have a shear modulus of 6.5MPa which is a shear modulus of an elastomer by changing cell wall thickness, cell angles, cell heights and cell lengths at meso-scale. The designed cellular solids are used for a ring typed shear band of a wheel structure at macro-scale. A structural performance such as contact pressure at the outer layer of the wheel is investigated with the honeycomb shear bands when a vertical force is applied at the center of the wheel. Cellular Materials Theory (CMT) is used to obtain in-plane effective properties of a honeycomb structure at meso-scale. Finite Element Analysis (FEA) with commercial software ABAQUS is employed to investigate the structural behavior of a wheel at macro-scale.

Conventional geometric parameters of honeycombs (cell height, h, cell length, l, and cell angle, θ) have been used to find effective properties of honeycomb structures. However, these parameters appear to be difficult to control both a target shear stiffness (4 to 4.5 MPa) and a target level of shear strain (~10%) because the parameters are coupled to each other within a constant design space. A method to design hexagonal honeycombs is derived to design for both shear stiffness and shear flexibility independently by replacing the conventional geometric parameters with two new parameters; effective height, R, and horizontal separation, d. A parametric study with commercial software, ABAQUS, is conducted using the two new parameters to investigate their affects on in-plane effective shear stiffness, G₁₂*, and maximum shear strain, (γ₁₂*)max of polycarbonate honeycombs under a fixed overall honeycomb height of 12.7 mm (0.5 in).

Exhaust gas turbo-charging helps exploit the improved fuel efficiency of downsized engines by increasing the possible power density from these engines. However, turbo-charged engines exhibit poor transient performance, especially when accelerating from low speeds. In addition, during low-load operating regimes, when the exhaust gas is diverted past the turbine with a waste-gate or pushed through restricted vanes in a variable geometry turbine, there are lost opportunities for recovering energy from the enthalpy of the exhaust gas. Similar limitations can also be identified with mechanical supercharging systems. This paper proposes an electrical supercharging and turbo-generation system that overcomes some of these limitations. The system decouples the activation of the air compression and exhaust-energy recovery functions using a dedicated electrical energy storage buffer. Its main attributes fast speed of response to load changes and flexibility of control.