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General Motors Powertrain Division has developed the next generation big block V8 engine for introduction in the 1996 model year. In addition to meeting tighter emission and on-board diagnostic legislation, this engine evolved to meet both customer requirements and competitive challenges. Starting with the proven dependability of the time tested big block V8, goals were set to substantially increase the power, torque, fuel economy and overall pleaseability of GM's large load capacity gasoline engine. The need for this new engine to meet packaging requirements in many vehicle platforms, both truck and OEM, as well as a requirement for minimal additional heat rejection over the engine being replaced, placed additional constraints on the design.

The environment is one of the most important issues currently facing the world and the automobile industry is required to respond with eco-cars. To meet this requirement, the hybrid vehicle is one of the most optimal solutions. The hybrid system automatically stops engine idling (idling stop), or stops the engine during deceleration to recover energy. The engine stop however creates a problem concerning the vehicle's climate control system. Because the conventional climate control system incorporates a compressor driven by engine belt, there is almost no cooling performance while the engine is stopped. Until now, when a driver needed more cooling comfort the engine has been switched back on as a compromise measure. To realize cabin comfort that is consistent with fuel saving, a 2-way driven compressor has been developed that can be driven both by engine belt while the engine is running and by electric motor when the engine is stopped.

This paper is intended to give a general overview of the key aerodynamic developments for the 2006 Chevrolet Corvette C6 Z06. Significant computational and wind tunnel time were used to develop the 2006 Z06 to provide it with improved high speed stability, increased cooling capability and equivalent drag compared to the 2004 Chevrolet Corvette C5 Z06.

In the 42V Mild Hybrid System introduced into market by Toyota for the first time in the world, the crankshaft using belt(s) drives the motor/generator (MG). The set-up employs an inverter unit to control the MG electronically. This paper describes the system configuration, operations, characteristic features and development results of the new power control system. The focus is on the MG, the inverter-for-MG-control and energy regeneration, as well as DC/DC converter for the power supply to the 14V devices.

High frequency wind noise caused by turbulent flow around the front pillars of a vehicle is an important factor for customer perception of ride comfort. In order to reduce undesirable interior wind noise during vehicle development process, a calculation and visualization method for exterior wind noise with an acceptable computational cost and adequate accuracy is required. In this paper an index for prediction of the strength of exterior wind noise, referred to as Exterior Noise Power (ENP), is developed based on an assumption that the acoustic power of exterior wind noise can be approximated by the far field acoustic power radiated from vehicle surface. Using the well-known Curle’s equation, ENP can be represented as a surface integral of an acoustic intensity distribution, referred to as Exterior Noise Power Distribution (ENPD). ENPD is estimated from turbulent surface pressure fluctuation and mean convective velocity in the vicinity of the vehicle surface.

This paper quantifies the potential of electric propulsion systems to reduce petroleum use and greenhouse gas (GHG) emissions in the 2030 U.S. light-duty vehicle fleet. The propulsion systems under consideration include gasoline hybrid-electric vehicles (HEVs), plug-in hybrid vehicles (PHEVs), fuel-cell hybrid vehicles (FCVs), and battery-electric vehicles (BEVs). The performance and cost of key enabling technologies were extrapolated over a 25-30 year time horizon. These results were integrated with software simulations to model vehicle performance and tank-to-wheel energy consumption. Well-to-wheel energy and GHG emissions of future vehicle technologies were estimated by integrating the vehicle technology evaluation with assessments of different fuel pathways. The results show that, if vehicle size and performance remain constant at present-day levels, these electric propulsion systems can reduce or eliminate the transport sector's reliance on petroleum.

This paper presents a comparison of methods for the identification of a reduced set of useful variables using a multidimensional system. The Mahalanobis-Taguchi System and a standard statistical technique are used reduce the dimensionality of vehicle ride based on consumer satisfaction ratings. The Mahalanobis-Taguchi System and cluster analysis are applied to vehicle ride. The research considers 67 vehicle data sets for the 6 vehicle ride parameters. This paper applies the Mahalanobis-Taguchi System to forecast consumer satisfaction and provides a comparison of results with those obtained from a standard statistical approach to the problem.

This paper presents a custom integrated circuit (IC) on which circuit functions necessary for “Active Hydraulic Brake (AHB) system” are integrated, and its key component, “Current-to-Digital Converter” for solenoid current measurement. The AHB system, which realizes a seamless brake feeling for Antilock Brake System (ABS) and Regenerative Brake Cooperative Control of Hybrid Vehicle, and the custom IC are installed in the 4th-generation Prius released in 2015. In the AHB system, as linear solenoid valves are used for hydraulic brake pressure control, high-resolution and high-speed sensing of solenoid current with ripple components due to pulse width modulation (PWM) is one of the key technologies. The proposed current-to-digital converter directly samples the drain-source voltage of the sensing DMOS (double-diffused MOSFET) with an analog-to-digital (A/D) converter (ADC) on the IC, and digitizes it.

A new process is developed for the aerodynamic shape optimization of racing cars using Computational Fluid Dynamics (CFD). The process is based on using the mesh morphing techniques to create new designs for analysis by morphing the CFD mesh of the original design. The resulting improvements in the analysis turnaround time allow a quick exploration of the design parameters for determining the optimum aerodynamic design. The approach is used to perform a parametric study to optimize a racing car shape for maximum downforce. The analysis procedure used for the CFD analysis is tuned to ensure grid independence and accuracy of the predictions. The parametric study shows that the morpher-based process can quickly and precisely create designs for the CFD analysis. This process can become the foundation for the automated aerodynamic design optimization of the racing cars.

The battery support in a small car is an example of a subsystem that lends itself to mounted component dynamic fatigue analysis, due to its weight and localized attachments. This paper describes a durability analysis method that was developed to define the required enforced motion, stress response, and fatigue life for such subsystems. The method combines the large mass method with the modal transient formulation to determine the dynamic stress responses. The large mass method was selected over others for its ease of use and efficiency when working with the modal formulation and known accelerations from a single driving point. In this example, these known accelerations were obtained from the drive files of a 4-DOF shake table that was used for corresponding lab tests of a rear compartment body structure. These drive files, originally displacements, were differentiated twice and filtered to produce prescribed accelerations to the finite element model.

Advances in avionics and display technology are significantly changing the cockpit environment in current transport aircraft. The MIT Aeronautical Systems Lab (ASL) has developed a part-task flight simulator specifically to study the effects of these new technologies on flight crew situational awareness and performance. The simulator is based on a commercially-available graphics workstation, and can be rapidly reconfigured to meet the varying demands of experimental studies. The simulator has been successfully used to evaluate graphical microburst alerting displays, electronic instrument approach plates, terrain awareness and alerting displays, and ATC routing amendment delivery through digital datalinks.

Future Automotive Systems Technology Simulator (FASTSim) is a free and open-source tool developed by National Renewable Energy Lab (NREL). Among the attractive capabilities of the FASTSim is that it can perform computationally efficient fuel economy simulations of automotive vehicles with reasonable accuracy for standard or arbitrary drive cycles. The modeling capability includes vehicles with various types of powertrains such as: conventional vehicles (CVs), hybrid-electric vehicles (HEVs), plugin hybrid electric vehicles (PHEVs) and battery-only electric vehicles (BEVs). The public version of FASTSim available from NREL is implemented in Excel, which achieves the goal of good accessibility to a broad audience, but has some limitations, including: i) bottleneck in computations when importing arbitrary drive cycles, ii) slower computations in general than other scripting or programming languages, and iii) less portable to integration with other applications and/or other platforms.

In developing the 2007 Model Year Saturn VUE Green Line hybrid vehicle, a vehicle model for prediction of fuel economy and performance was developed. This model was developed in Matlab / Simulink / Stateflow by augmenting an existing conventional vehicle model to include hybrid components and controls. The generic structure and the functionalities of the model are presented. This simulation model was used for rapid concept selection and requirements balancing early in the vehicle development process. Engine usage and energy distributions are shown based on simulation results. Fuel economy breakdown was also discussed.

This paper describes the use of a modified quasi-dimensional spark-ignition engine simulation code to predict the extent of cycle-to-cycle variations in combustion. The modifications primarily relate to the combustion model and include the following: 1. A flame kernel model was developed and implemented to avoid choosing the initial flame size and temperature arbitrarily. 2. Instead of the usual assumption of the flame being spherical, ellipsoidal flame shapes are permitted in the model when the gas velocity in the vicinity of the spark plug during kernel development is high. Changes in flame shape influence the flame front area and the interaction of the enflamed volume with the combustion chamber walls. 3. The flame center shifts due to convection by the gas flow in the cylinder. This influences the flame front area through the interaction between the enflamed volume and the combustion chamber walls. 4. Turbulence intensity is not uniform in cylinder, and varies cycle-to-cycle.

Quietness is one of the most important characteristics for Hybrid Electric Vehicle quality. Reduction of the rattle noise caused by the torque fluctuation of an internal combustion engine can contribute to get a customer satisfaction. Toyota Hybrid System(THS) also has same requirement. Especially, the rattle noise during idling may happen discontinuously despite of periodical engine combustion excitation. It is necessary to study the mechanism and reduce the rattle noise. At lower engine torque range, decreasing the torsional damper’s stiffness can improve this condition as the manual transaxle done. However, the rattle noise can occur easily in conditions of relatively large torque spike inputs to the torsional system, such as the engine start/stop function of THS using the motor/generator in the transaxle.

Plugin hybrid electric vehicles (PHEVs) have several attractive features in terms of reduction of greenhouse gas (GHG) emissions. Compared to conventional vehicles (CVs) that only have an internal combustion engine (ICE), PHEVs have better energy efficiency like regular hybrids (HEVs), allow for electrifying an appreciable portion of traveled miles, and have no range anxiety issues like battery-only electric vehicles (BEVs). However, in terms of criteria emissions (e.g., NOx, NMOG, HC), it is unclear if PHEVs are any better than HEVs or CVs. Unlike GHG emissions, criteria emissions are not continuously emitted in proportional quantities to fossil fuel consumption. Rather, the amount and type of criteria emissions is a rather complex function of many factors, including type of fuel, ICE temperature, speed and torque, catalyst temperature, as well as the ICE controls (e.g., fuel-to-air ratio, valve and ignition timing).

Accurately predicting real-world vehicle energy consumption is essential for optimizing vehicle designs, enhancing energy efficiency, and developing effective energy management strategies. This paper presents a data-driven approach that utilizes machine learning techniques and a comprehensive dataset of vehicle parameters and environmental factors to create precise energy consumption prediction models. The methodology involves recording real-world vehicle data using data loggers to extract information from the CAN bus systems for ICE and hybrid electric, as well as hydrogen and battery fuel cell vehicles. Data cleaning and cycle-based analysis are employed to process the dataset for accurate energy consumption prediction. This includes cycle detection and analysis using methods from statistics and signal processing, and then pattern recognition based on these metrics.

Currently, states that are out of compliance with the National Ambient Air Quality Standards must, according to the Clean Air Act Amendments of 1990 (CAAA), develop and implement control strategies that demonstrate specific degrees of reduction in emissions-with the degree of reduction depending upon the severity of the problem. One tool that has been developed to aid regulators in both deciding an appropriate course of action and to demonstrate the desired reductions in mobile emissions is EPA's Mobile 5a emission estimation model. In our study, Mobile 5a has been used to examine the effects of regulatory strategies, as applied to the Northeast United States, on vehicle emissions under worst-case ozone-forming conditions.

MIT Lincoln Laboratory is tasked by the U.S. Federal Aviation Administration to investigate the use of the NEXRAD polarimetric radars* for the remote sensing of icing conditions hazardous to aircraft. A critical aspect of the investigation concerns validation that has relied upon commercial airline icing pilot reports and a dedicated campaign of in situ flights in winter storms. During the month of February in 2012 and 2013, the Convair-580 aircraft operated by the National Research Council of Canada was used for in situ validation of snowstorm characteristics under simultaneous observation by NEXRAD radars in Cleveland, Ohio and Buffalo, New York. The most anisotropic and easily distinguished winter targets to dual pol radar are ice crystals.

Traffic accidents in the United States were analyzed using FARS and NASS data. When classified according to vehicle body type and collision type, fatalities were most common in the case of (1) passenger car to passenger car frontal impacts, (2) passenger car to passenger car side impacts, (3) passenger car to LTV side impacts, (4) passenger car to truck frontal impacts, and (5) passenger car to LTV frontal impacts. Among these collisions, it was clearly confirmed that the occupants of a passenger car have a strong tendency to suffer injury when “the passenger car has a frontal impact with a heavier passenger car,” “the passenger car has a frontal impact with an LTV/SUV, truck,” and “the passenger car is side impacted by an LTV/SUV,” or the like. These examples should be recognized as clear cases of incompatibility. This paper will describe an approach which aim at improving compatibility. However, around 60% of occupants who suffer fatal injuries are not wearing a seat belt.