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It is well known that the ride quality of trucks is much harsher than that of automobiles. Additionally, truck drivers typically drive trucks for much longer duration than automobile drivers. These two factors contribute to the fatigue that a truck driver typically experiences during long haul deliveries. Fatigue reduces driver alertness and increases reaction times, increasing the possibility of an accident. One may conclude that better ride quality contributes to safer operation. The secondary suspensions of a tractor have been an area of particular interest because of the considerable ride comfort improvements they provide. A gap exists in the current engineering domain of an easily configurable high fidelity low computational cost simulation tool to analyze the ride of a tractor semi-trailer. For a preliminary design study, a 15 d.o.f. model of the tractor semi-trailer was developed to simulate in the Matlab/Simulink environment.

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.

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 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).

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.

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.

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.

Two methods for analyzing and evaluating the environmental control system on an advanced aircraft as described in this paper include the conventional first law energy conservation technique and the second law entropy generation minimization technique. Simplified analytical models of the ECS are developed for each method and compared to determine the validity of using the latter to facilitate the design process in optimizing the overall system for a minimum gross takeoff weight (GTW). Preliminary results have illustrated the importance of taking into account system optimization based on system (or component) efficiency. For instance, even though different values were obtained for the rate of entropy generation, the second law analysis of a shell-in-tube heat exchanger led to an optimum tube diameter of 0.12 in (3.05 mm) when both R-12 and R-114 were used as the refrigerant in the vapor cycle.