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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.

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.

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.

Comparisons have been made between dual-fuel (80% port-injection gasoline and 20% direct-injection diesel by mass) Highly Premixed Charge Combustion (HPCC) and blended-fuel (80% gasoline and 20% diesel) Low Temperature Combustion (LTC) modes on a 1-L single-cylinder test engine. In the HPCC mode, both early-injection (E-HPCC) and late-injection (L-HPCC) of diesel have been used. The comparisons have been conducted with a fixed fuel injection rate of 50 mg/cycle at 1500 rpm, and with the combustion phasing fixed (by adjusting the injection timing) so that the 50% heat release point (CA50) is at 8° ATDC. The rapid heat release process of LTC leads to the highest maximum pressure rise rate (MPRR). A two-peak heat release process is observed in L-HPCC, resulting in a lower MPRR. The heat release rate and MPRR values for the E-HPCC are comparable to the L-HPCC values. The EHPCC mode provides the lowest NOX emission. The soot emissions for all three modes are low.

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.

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.

A model has been developed to predict the performance of the Texaco Controlled Combustion, Stratified Charge Engine starting from engine geometry, fuel characteristics and the operating conditions. This performance model divides the engine cycle into the following phases: Intake, Compression, Rapid Combustion, Mixing-Dominated Expansion, Heat-Transfer Dominated Expansion and Exhaust. During the rapid combustion phase, the rate of heat release is assumed to be controlled by the rate of fuel injection and the air-to-fuel ratio. The burning rate in the mixing controlled stage appears to be dominated by the rate of entrainment of the surrounding gas by the plume of burning products and this rate is assumed to be controlled by the turbulent eddy entrainment velocity. A plume geometry model has been developed to obtain the surface area of the plume for entrainment during the mixing dominated phase.

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.

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.

Cranking and startup fuel control has become increasingly important due to ever tightening emission requirements. Additionally, engine-off strategies during idle will require substantially more engine startup events with the associated need for very clean starts. Thus, knowledge of an engine's Air-Fuel Ratio (AFR) during its early cycles is necessary in order to optimize cranking and startup fueling. This paper examines and compares two methods of measuring an engine's AFR during engine startup (approximately the first second of operation); an in-cylinder technique using a Fast Flame Ionization Detector (FFID) and the conventional exhaust based Universal Exhaust Gas Oxygen (UEGO) sensor method. Engine starts using a Ford Zetec engine were performed at three different temperatures (0, 20 and 90 C) as well as different initial engine starting positions.

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.

Rare earths are a group of elements whose availability has been of concern due to monopolistic supply conditions and environmentally unsustainable mining practices. To evaluate the risks of rare earths availability to automakers, a first step is to determine raw material content and value in vehicles. This task is challenging because rare earth elements are used in small quantities, in a large number of components, and by suppliers far upstream in the supply chain. For this work, data on rare earth content reported by vehicle parts suppliers was assessed to estimate the rare earth usage of a typical conventional gasoline engine midsize sedan and a full hybrid sedan. Parts were selected from a large set of reported parts to build a hypothetical typical mid-size sedan. Estimates of rare earth content for vehicles with alternative powertrain and battery technologies were made based on the available parts' data.

To cope with the conflict requirements between the stability and handling performance, and the high-order and complex vehicle-trailer plant, a model tracking method is proposed. With this approach, a feedback control is designed to “decouple” the vehicle and the trailer plant, such that each tracks a well-defined second-order reference model independently yet coordinately. A feedforward control is designed to maintain its system steady-state performance. As a result, the proposed approach not only improves the system transient responses, but also its steady-state performance. This approach further yields a simple yet analytical control derivation that provides more insight to the system dynamics.

This paper describes a post-race analysis of team KOMMIT EVT’s electric motorcycle data collected during the 2016 Pikes Peak International Hill Climb (PPIHC). The motorcycle consumed approximately 4 kWh of battery energy with an average and maximum speed of 107 km/h and 149 km/h, respectively. It was the second fastest electric motorcycle with a finishing time of 11:10.480. Data was logged of the motorcycle’s speed, acceleration, motor speed, power, currents, voltages, temperatures, throttle position, GPS position, rider’s heart rate and the ambient environment (air temperature, pressure and humidity). The data was used to understand the following factors that may have prevented a faster time: physical fitness of the rider, thermal limits of the motor and controller, available battery energy and the sprocket ratio between the motor and rear wheel.

In recent years, the slip lock-up mechanism has been adopted widely, because of its fuel efficiency and its ability to improve NVH. This necessitates that the automatic transmission fluid (ATF) used in automatic transmissions with slip lock-up clutches requires anti-shudder performance characteristics. The test methods used to evaluate the anti-shudder performance of an ATF can be classified roughly into two types. One is specified to measure whether a μ-V slope of the ATF is positive or negative, the other is the evaluation of the shudder occurrence in the practical vehicle. The former are μ-V property tests from MERCON® V, ATF+4®, and JASO M349-98, the latter is the vehicle test from DEXRON®-III. Additionally, in the evaluation of the μ-V property, there are two tests using the modified SAE No.2 friction machine and the modified low velocity friction apparatus (LVFA).

When pickup trucks are driven on concrete paved freeways, freeway hop shake is a major complaint. Freeway hop shake occurs when the vehicle passes over the concrete joints of the freeway which impose in-phase harmonic road inputs. These road inputs excite vehicle modes that degrade ride comfort. The worst shake level occurs when the vehicle speed is such that the road input excites the vehicle 1st bending mode and/or the rear wheel hop mode. The hop and bending mode are very close in frequency. This phenomenon is called freeway hop shake. Automotive manufacturers are searching for ways to mitigate freeway hop shake. There are several ways to reduce the shake amplitude. This paper documents a new approach using hydraulic body mounts to reduce the shake. A full vehicle analytical model was used to determine the root cause of the freeway hop shake.