Drivers' ratings of different components of their own driving skill: a greater illusion of superiority for skills that relate to accident involvement

Different components of driving skill relate to accident involvement in different ways. For instance, while hazard-perception skill has been found to predict accident involvement, vehicle-control skill has not. We found that drivers rated themselves superior to both their peers and the average driver on 18 components of driving skill (N = 181 respondents). These biases were greater for hazard-perception skills than for either vehicle-control skills or driving skill in general. Also, ratings of hazard-perception skill related to self-perceived safety after overall skill was controlled for. We suggest that although drivers appear to appreciate the role of hazard perception in safe driving, any safety benefit to be derived from this appreciation may be undermined by drivers' inflated opinions of their own hazard-perception skill. We also tested the relationship between illusory beliefs about driving skill and risk taking and looked at ways of manipulating drivers' illusory beliefs.

Optimal kinematic control of an autonomous underwater vehicle

This note investigates the motion control of an autonomous underwater vehicle (AUV). The AUV is modeled as a nonholonomic system as any lateral motion of a conventional, slender AUV is quickly damped out. The problem is formulated as an optimal kinematic control problem on the Euclidean Group of Motions SE(3), where the cost function to be minimized is equal to the integral of a quadratic function of the velocity components. An application of the Maximum Principle to this optimal control problem yields the appropriate Hamiltonian and the corresponding vector fields give the necessary conditions for optimality. For a special case of the cost function, the necessary conditions for optimality can be characterized more easily and we proceed to investigate its solutions. Finally, it is shown that a particular set of optimal motions trace helical paths. Throughout this note we highlight a particular case where the quadratic cost function is weighted in such a way that it equates to the Lagrangian (kinetic energy) of the AUV. For this case, the regular extremal curves are constrained to equate to the AUV's components of momentum and the resulting vector fields are the d'Alembert-Lagrange equations in Hamiltonian form.

Comparison of static and dynamic engine models on the transient performance of a passenger vehicle powertrain

This paper presents experimental and computational results obtained on the Ford Barra 190 4.0 litres I6 gasoline engine and on the Ford Falcon car equipped with this engine. Measurements of steady engine performance, fuel consumption and exhaust emissions were first collected using an automated test facility for a wide range of cam and spark timings vs. throttle position and engine speed. Simulations were performed for a significant number of measured operating points at full and part load by using a coupled Gamma Technologies GT-POWER/GT-COOL engine model for gas exchange, combustion and heat transfer. The fluid model was made up of intake and exhaust systems, oil circuit, coolant circuit and radiator cooling air circuit. The thermal model was made up of finite element components for cylinder head, cylinder, piston, valves and ports and wall thermal masses for pipes. The model was validated versus measured steady state air and fuel flow rates, cylinder pressure parameters, indicated and brake mean effective pressures, and temperature of metal, oil and coolant in selected locations. Computational results agree well with experiments, demonstrating the ability of the approach to produce fairly accurate steady state maps of BMEP and BSFC, as well as to optimize engine operation changing geometry, throttle position, cam and spark timing. Measurements of the transient performance and fuel consumption of the full vehicle were then collected over the NEDC cycle. Simulations were performed by using a coupled Gamma Technologies GT-POWER/GT-COOL/GT-DRIVE model for instantaneous engine gas exchange, combustion and heat transfer and vehicle motion. The full vehicle model is made up of transmission, driveshaft, axles, and car components and the previous engine model. The model was validated with measured fuel flow rates through the engine, engine throttle position, and engine speed and oil and coolant temperatures in selected locations. Instantaneous engine states following a time dependent demand for torque and speed differ from those obtained by interpolating steady state maps of BSFC vs. BMEP and speed. Computational results agree well with experiments, demonstrating the utility of the approach in providing a more accurate prediction of the fuel consumption over test cycles.

Using omeprazole to link the components of the post-prandial alkaline tide in the spiny dogfish, Squalus acanthias

After a meal, dogfish exhibit a metabolic alkalosis in the bloodstream and a marked excretion of basic equivalents across the gills to the external seawater. We used the H⁺, K⁺-ATPase pump inhibitor omeprazole to determine whether these post-prandial alkaline tide events were linked to secretion of H⁺ (accompanied by Cl^–) in the stomach. Sharks were fitted with indwelling stomach tubes for pretreatment with omeprazole (five doses of 5mg omeprazole per kilogram over 48 h) or comparable volumes of vehicle (saline containing 2% DMSO) and for sampling of gastric chyme. Fish were then fed an involuntary meal by means of the stomach tube consisting of minced flatfish muscle (2% of body mass) suspended in saline (4% of body mass total volume). Omeprazole pretreatment delayed the post-prandial acidification of the gastric chyme, slowed the rise in Cl^– concentration of the chyme and altered the patterns of other ions, indicating inhibition of H⁺ and accompanying Cl^– secretion. Omeprazole also greatly attenuated the rise in arterial pH and bicarbonate concentrations and reduced the net excretion of basic equivalents to the water by 56% over 48h. Arterial blood CO₂ pressure and plasma ions were not substantially altered. These results indicate that elevated gastric H⁺ secretion (as HCl) in the digestive process is the major cause of the systemic metabolic alkalosis and the accompanying rise in base excretion across the gills that constitute the alkaline tide in the dogfish.

Pneumatic vehicle

A pneumatic vehicle is provided with a first sub-assembly with a chassis, part of the vehicle body, a pair of B-pillars, a pair of rear rails, wheels, an elongate aluminum compressed load bearing air tank oriented longitudinally in the chassis, side panels connected to the tank and the wheels, a heat exchanger to heat the compressed air, and an air motor driven by the heated, compressed air and connected to a wheel. A ventilation system has a restrictive solenoid valve for directing air to the heat exchanger. The air tank is provided with a carbon filament reinforced plastic layer, and a fiberglass and aramid-fiber layer. A second sub-assembly includes part of the vehicle body bonded to the first-sub-assembly using a structural adhesive, a pair of A-pillars, and a pair of roof rails. Seating includes inflatable components for adjustment.

CHASSIS FOR PNEUMATIC VEHICLE

A pneumatic vehicle is provided with a first sub-assembly with a chassis, part of the vehicle body, a pair of B-pillars, a pair of rear rails, wheels, an elongate aluminum compressed load bearing air tank oriented longitudinally in the chassis, side panels connected to the tank and the wheels, a heat exchanger to heat the compressed air, and an air motor driven by the heated, compressed air and connected to a wheel. A ventilation system has a restrictive solenoid valve for directing air to the heat exchanger. The air tank is provided with a carbon filament reinforced plastic layer, and a fiberglass and aramid-fiber layer. A second sub-assembly includes part of the vehicle body bonded to the first-sub-assembly using a structural adhesive, a pair of A-pillars, and a pair of roof rails. Seating includes inflatable components for adjustment.

PNEUMATIC VEHICLE

A pneumatic vehicle is provided with a first sub- assembly with a chassis, part of the vehicle body, a pair of B-pillars, a pair of rear rails, wheels, an elongate aluminum compressed load bearing air tank oriented longitudinally in the chassis, side panels connected to the tank and the wheels, a heat exchanger to heat the compressed air, and an air motor driven by the heated, compressed air and connected to a wheel. A ventilation system has a restrictive solenoid valve for directing air to the heat exchanger. The air tank is provided with a carbon filament reinforced plastic layer, and a fiberglass and aramid-fiber layer. A second sub-assembly includes part of the vehicle body bonded to the first-sub-assembly using a structural adhesive, a pair of A-pillars, and a pair of roof rails. Seating includes inflatable components for adjustment.

Adaptive intelligent energy management system of plug-in hybrid electric vehicle

Efficient energy management in hybrid vehicles is the key for reducing fuel consumption and emissions. To capitalize on the benefits of using PHEVs (Plug-in Hybrid Electric Vehicles), an intelligent energy management system is developed and evaluated in this paper. Models of vehicle engine, air conditioning, powertrain, and hybrid electric drive system are first developed. The effect of road parameters such as bend direction and road slope angle as well as environmental factors such as wind (direction and speed) and thermal conditions are also modeled. Due to the nonlinear and complex nature of the interactions between PHEV-Environment-Driver components, a soft computing based intelligent management system is developed using three fuzzy logic controllers. The crucial fuzzy engine controller within the intelligent energy management system is made adaptive by using a hybrid multi-layer adaptive neuro-fuzzy inference system with genetic algorithm optimization. For adaptive learning, a number of datasets were created for different road conditions and a hybrid learning algorithm based on the least squared error estimate using the gradient descent method was proposed. The proposed adaptive intelligent energy management system can learn while it is running and makes proper adjustments during its operation. It is shown that the proposed intelligent energy management system is improving the performance of other existing systems. © 2014 Elsevier Ltd.

Chassis for pneumatic vehicle

A pneumatic vehicle is provided with a first sub-assembly with a chassis, part of the vehicle body, a pair of B-pillars, a pair of rear rails, wheels, an elongate aluminum compressed load bearing air tank oriented longitudinally in the chassis, side panels connected to the tank and the wheels, a heat exchanger to heat the compressed air, and an air motor driven by the heated, compressed air and connected to a wheel. A ventilation system has a restrictive solenoid valve for directing air to the heat exchanger. The air tank is provided with a carbon filament reinforced plastic layer, and a fiberglass and aramid-fiber layer. A second sub-assembly includes part of the vehicle body bonded to the first-sub-assembly using a structural adhesive, a pair of A-pillars, and a pair of roof rails. Seating includes inflatable components for adjustment.

Chassis for pneumatic vehicle

A pneumatic vehicle is provided with a first sub-assembly with a chassis, part of the vehicle body, a pair of B-pillars, a pair of rear rails, wheels, an elongate aluminum compressed load bearing air tank oriented longitudinally in the chassis, side panels connected to the tank and the wheels, a heat exchanger to heat the compressed air, and an air motor driven by the heated, compressed air and connected to a wheel. A ventilation system has a restrictive solenoid valve for directing air to the heat exchanger. The air tank is provided with a carbon filament reinforced plastic layer, and a fiberglass and aramid-fiber layer. A second sub-assembly includes part of the vehicle body bonded to the first-sub-assembly using a structural adhesive, a pair of A-pillars, and a pair of roof rails. Seating includes inflatable components for adjustment.

Prostate carcinogenesis induced by N-methyl-N-nitrosourea (mnu) in gerbils: Histopathological diagnosis and potential invasiveness mediated by extracellular matrix components

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

STUDY OF HYBRID ELECTRIC VEHICLE BATTERY MODELING AND CONTROL USING AUTONOMIE

This report presents the research results of battery modeling and control for hybrid electric vehicles (HEV). The simulation study is conducted using plug-and-play powertrain and vehicle development software, Autonomie. The base vehicle model used for testing the performance of battery model and battery control strategy is the Prius MY04, a power-split hybrid electric vehicle model in Autonomie. To evaluate the battery performance for HEV applications, the Prius MY04 model and its powertrain energy flow in various vehicle operating modes are analyzed. The power outputs of the major powertrain components under different driving cycles are discussed with a focus on battery performance. The simulation results show that the vehicle fuel economy calculated by the Autonomie Prius MY04 model does not match very well with the official data provided by the department of energy (DOE). It is also found that the original battery model does not consider the impact of environmental temperature on battery cell capacities. To improve battery model, this study includes battery current loss on coulomb coefficient and the impact of environmental temperature on battery cell capacity in the model. In addition, voltage losses on both double layer effect and diffusion effect are included in the new battery model. The simulation results with new battery model show the reduced fuel economy error to the DOE data comparing with the original Autonomie Prius MY04 model.

Predictive control of hybrid vehicle powertrain for intelligent energy management

This thesis studies the minimization of the fuel consumption for a Hybrid Electric Vehicle (HEV) using Model Predictive Control (MPC). The presented MPC – based controller calculates an optimal sequence of control inputs to a hybrid vehicle using the measured plant outputs, the current dynamic states, a system model, system constraints, and an optimization cost function. The MPC controller is developed using Matlab MPC control toolbox. To evaluate the performance of the presented controller, a power-split hybrid vehicle, 2004 Toyota Prius, is selected. The vehicle uses a planetary gear set to combine three power components, an engine, a motor, and a generator, and transfer energy from these components to the vehicle wheels. The planetary gear model is developed based on the Willis’s formula. The dynamic models of the engine, the motor, and the generator, are derived based on their dynamics at the planetary gear. The MPC controller for HEV energy management is validated in the MATLAB/Simulink environment. Both the step response performance (a 0 – 60 mph step input) and the driving cycle tracking performance are evaluated. Two standard driving cycles, Urban Dynamometer Driving Schedule (UDDS) and Highway Fuel Economy Driving Schedule (HWFET), are used in the evaluation tests. For the UDDS and HWFET driving cycles, the simulation results, the fuel consumption and the battery state of charge, using the MPC controller are compared with the simulation results using the original vehicle model in Autonomie. The MPC approach shows the feasibility to improve vehicle performance and minimize fuel consumption.

THERMAL CHARACTERIZATION OF COMBUSTION CHAMBER COMPONENTS IN A GASOLINE TURBOCHARGED DIRECT INJECTION (GTDI) ENGINE

This report is a PhD dissertation proposal to study the in-cylinder temperature and heat flux distributions within a gasoline turbocharged direct injection (GTDI) engine. Recent regulations requiring automotive manufacturers to increase the fuel efficiency of their vehicles has led to great technological achievements in internal combustion engines. These achievements have increased the power density of gasoline engines dramatically in the last two decades. Engine technologies such as variable valve timing (VVT), direct injection (DI), and turbocharging have significantly improved engine power-to-weight and power-to-displacement ratios. A popular trend for increasing vehicle fuel economy in recent years has been to downsize the engine and add VVT, DI, and turbocharging technologies so that a lighter more efficient engine can replace a larger, heavier one. With the added power density, thermal management of the engine becomes a more important issue. Engine components are being pushed to their temperature limits. Therefore it has become increasingly important to have a greater understanding of the parameters that affect in-cylinder temperatures and heat transfer. The proposed research will analyze the effects of engine speed, load, relative air-fuel ratio (AFR), and exhaust gas recirculation (EGR) on both in-cylinder and global temperature and heat transfer distributions. Additionally, the effect of knocking combustion and fuel spray impingement will be investigated. The proposed research will be conducted on a 3.5 L six cylinder GTDI engine. The research engine will be instrumented with a large number of sensors to measure in-cylinder temperatures and pressures, as well as, the temperature, pressure, and flow rates of energy streams into and out of the engine. One of the goals of this research is to create a model that will predict the energy distribution to the crankshaft, exhaust, and cooling system based on normalized values for engine speed, load, AFR, and EGR. The results could be used to aid in the engine design phase for turbocharger and cooling system sizing. Additionally, the data collected can be used for validation of engine simulation models, since in-cylinder temperature and heat flux data is not readily available in the literature..

Evaluation of the Magnetic Field Generated by the Inverter of an Electric Vehicle

In hybrid and electric vehicles, passengers sit very close to an electric system of significant power, which means that they may be subjected to high electromagnetic fields. The hazards of long-term exposure to these fields must be taken into account when designing electric vehicles and their components. Among all the electric devices present in the power train, the electronic converter is the most difficult to analyze, given that it works with different frequencies. In this paper, a methodology to evaluate the magnetic field created by a power electronics converter is proposed. After a brief overview of the recommendations of electromagnetic fields exposure, the magnetic field produced by an inverter is analyzed using finite element techniques. The results obtained are compared to laboratory measurements, taken from a real inverter, in order to validate the model. Finally, results are used to draw some conclusions regarding vehicle design criteria and magnetic shielding efficiency.