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This investigation was aimed at measuring the relative performance of two spray-guided, single-cylinder, spark-ignited direct-injected (SIDI) engine combustion system designs. The first utilizes an outwardly-opening poppet, piezo-actuated injector, and the second a conventional, solenoid operated, inwardly-opening multi-hole injector. The single-cylinder engine tests were limited to steady state, warmed-up conditions. The comparison showed that these two spray-guided combustion systems with two very different sprays had surprisingly close results and only differed in some details. Combustion stability and smoke emissions of the systems are comparable to each other over most of the load range. Over a simulated Federal Test Procedure (FTP) cycle, the multi-hole system had 15% lower hydrocarbon and 18% lower carbon monoxide emissions.

With deflected-disc dampers, digressive force-velocity shapes are achieved via the combined effects of disc stack stiffness and hub-offset. The degree of digressiveness can be adjusted to alter vehicle performance by changing the proportion of these parameters. Optimizing this relationship can yield substantial vehicle performance improvements, but the time consuming iterative process of developing a new disc stack for each hub-offset discourages experimentation. To enable more efficient digressiveness comparisons, a regression-based computational method has been developed which converts disc stack stiffness from one hub-offset to other offsets directly, without iteration. Once an initial disc stack for one offset has been tuned by traditional methods, stacks for other offsets can be calculated that maintain overall damper control.

A simulation methodology is developed for the Constant Radius Constant Speed (CRCS) analysis to predict the ISO4138 [1] road test performance. The CRCS analysis can be used to predict the vehicle steady-state handling characteristics such as understeer, rear cornering compliance, and roll gradient, etc. The Yaw-Rate Control methodology is applied to replace the traditional driver-in-the-loop path-following approaches. Comparing to the path-following approaches, the proposed method is simpler to use, more efficient, accurate, and robust.

This paper outlines a process to assess the aerodynamic performance of different vehicle exterior surfaces. The initial section of the paper summarizes the details of white-light scanning process that maps entire vehicle to points in Cartesian co-ordinate system which is followed by the conversion of scanned points to theme surface. The concept of point-cloud modeling is employed to generate a smooth theme surface from scanned points. Theme surfaces thus developed are stitched to under-body/under-hood (UB/UH) parts of the base vehicle and the numerical simulations were carried out to understand the aerodynamic efficiency of the surfaces generated. Specifics of surface/volume mesh generated, boundary conditions imposed and numerical scheme employed are discussed in detail. Flow field over vehicle exterior is thoroughly analyzed. A comparison study highlighting the effect of front grilles in unblocked condition along with air-dam on flow field has been provided.

Determining Li-ion battery life through life modeling is an excellent tool in determining and estimating end-of-life performance. Achieving End-of-Life (EOL) can be challenging since it is difficult to achieve both cycle and calendar life during the same test without years of testing. The plan to correlate testing with the model included three (3) distinct temperature ranges, beginning with the four-Season temperature profile, an aggressive profile with temperatures in the 50 to 55°C range, and using a mid-temperature range (40-45°C) as a final comparison test. A high duty-cycle drive profile was used to cycle all of the batteries as quickly as possible to reach the one potential definition of EOL; significant increases in resistance or capacity fade.

The main objective of this work is to demonstrate the merits of the Adjoint method to provide comprehensive information for shape sensitivities and design directions to achieve low drag vehicle shapes. The adjoint method is applied to a simple 2D airfoil and a 3D vehicle shape. The discrete Adjoint equations in the flow solvers are used to investigate further potential shape improvements of the low drag vehicle shapes. The low drag vehicle used in this study was designed earlier using the conventional approach (i.e., extensive use of wind tunnel testing). The goal is to use the already low drag vehicle shape and reduce its drag even further using the adjoint methodology without using the time-consuming and the high cost of wind tunnel testing. In addition, the present study is intended to compare the results with the other computational techniques such as surface pressure gradients method.

Understanding the flow characteristics and, especially, how the aerodynamic forces are influenced by the changes in the vehicle body shape, are very important in order to improve vehicle aerodynamics. One specific goal of aerodynamic shape optimization is to predict the local shape sensitivities for aerodynamic forces. The availability of a reliable and efficient sensitivity analysis method will help to reduce the number of design iterations and the aerodynamic development costs. Among various shape optimization methods, the Adjoint Method has received much attention as an efficient sensitivity analysis method for aerodynamic shape optimization because it allows the computation of sensitivity information for a large number of shape parameters simultaneously.

This paper presents some of the challenges and successful outcomes in developing the aerodynamic characteristics of the Chevrolet Volt, an electric vehicle with an extended-range capability. While the Volt's propulsion system doesn't directly affect its shape efficiency, it does make aerodynamics much more important than in traditional vehicles. Aerodynamic performance is the second largest contributor to electric range, behind vehicle mass. Therefore, it was critical to reduce aerodynamic drag as much as possible while maintaining the key styling cues from the original concept car. This presented a number of challenges during the development, such as evaluating drag due to underbody features, balancing aerodynamics with wind noise and cooling flow, and interfacing with other engineering requirements. These issues were resolved by spending hundreds of hours in the wind tunnel and running numerous Computational Fluid Dynamics (CFD) analyses.

An air suspension system can consist of many different components. These components include an air compressor, air springs, pneumatic solenoid valves, height sensors, electronic control unit, air reservoir, air lines, pressure sensor, temperature sensor, etc. The system could be designed as a 2-corner rear air suspension or a 4-corner air suspension. In this paper, the pneumatic models of air suspension systems are presented. The suspension system models are implemented in AmeSim. The suspension controls are implemented using Matlab/Simulink. The compressor was modeled using the standard AmeSim element with known mass flow rate as a function of pressure ratio. Air lines were modeled using a friction submodel of pneumatic pipe and control (isolation) valves are modeled using 2 position, 2 port pneumatic servo valves. The air spring is modeled as a single pneumatic chamber, single rod jack with spring assistance to account for spring nonlinearities.

Presented in the paper is a comprehensive analysis for floating piston pin. It is more challenging because it is a special type of journal bearing where the rotation of the journal is coupled with the friction between the journal and the bearing. In this analysis, the multi-degree freedom mass-conserving mixed-EHD equations are solved to determine the coupled pin rotation and friction. Other bearing characteristics, such as minimum film thickness, pin secondary motions in both connecting-rod small-end bearing and piston pin-boss bearing, power loss etc are also determined. The mechanism for floating pin to have better scuffing resistance is discovered. The theoretical and numerical model is implemented in the GM internal software FLARE (Friction and Lubrication Analysis for Reciprocating Engines).

Diesel engine developers are continually striving to reduce harmful NOx emissions through various calibration and hardware strategies. One strategy being implemented in production Diesel engines involves utilizing cooled exhaust gas recirculation (EGR). Although there is a significant NOx reduction potential by utilizing cooled EGR, there are also several issues associated with it, such as EGR cooler fouling and a reduction in cooler effectiveness that can occur over time. The exact cause of these issues and many others related to cooler fouling are not clearly understood. One such unanswered issue or phenomenon that has been observed in both field tested and lab tested EGR coolers is that of a recovery in EGR cooler effectiveness after a shutdown or after cycling between various conditions.

The present paper describes the results of a research project aimed at studying the impact of nozzle flow number on a Euro5 automotive diesel engine, featuring Closed-Loop Combustion Control. In order to optimize the trade-offs between fuel economy, combustion noise, emissions and power density for the next generation diesel engines, general trend among OEMs is lowering nozzle flow number and, as a consequence, nozzle hole size. In this context, three nozzle configurations have been characterized on a 2.0L Euro5 Common Rail Diesel engine, coupling experimental activities performed on multi-cylinder and optical single cylinder engines to analysis on spray bomb and injector test rigs. More in detail, this paper deeply describes the investigation carried out on the multi-cylinder engine, specifically devoted to the combustion evolution and engine performance analysis, varying the injector flow number.

The sustainable use of energy and the reduction of pollutant emissions are main concerns of the automotive industry. In this context, Hybrid Electric Vehicles (HEVs) offer significant improvements in the efficiency of the propulsion system and allow advanced strategies to reduce pollutant and noise emissions. The paper presents the results of a simulation study that addresses the minimization of fuel consumption, NOx emissions and combustion noise of a medium-size passenger car. Such a vehicle has a parallel-hybrid diesel powertrain with a high-voltage belt alternator starter. The simulation reproduces real-driver behavior through a dynamic modeling approach and actuates an automatic power split between the Internal Combustion Engine (ICE) and the Electric Machine (EM). Typical characteristics of parallel hybrid technologies, such as Stop&Start, regenerative braking and electric power assistance, are implemented via an operating strategy that is based on the reduction of total losses.

Today, nearly half of the world population lives in urban areas. As the world population continues to migrate to urban areas for increased economic opportunities, addressing personal mobility challenges such as air pollution, Greenhouse Gases (GHGs) and traffic congestion in these regions will become even a greater challenge especially in rapidly growing nations. Road transportation is a major source of air pollution in urban areas causing numerous health concerns. Improvements in automobile technology over the past several decades have resulted in reducing conventional vehicle tailpipe emissions to exceptionally low levels. This transformation has been attained mainly through advancements in engine and transmission technologies and through partial electrification of vehicles. However, the technological advancements made so far alone will not be able to mitigate the issues due to increasing GHGs and air pollution in urban areas.

This paper examines Smart Electric Power Management as it pertains to when the vehicle charging system is active. Over the past decade there have been several factors at play which have stressed the demands placed upon the vehicle electrical power system. Many of these factors present challenges to electrical power that are at cross-purposes with one another. For example, demands of new and existing electrical loads, customer expectations about load performance and battery life, and the push by governments' world-wide for increased fuel economy (FE) and reduced CO2 emissions all have direct impact and can be directly impacted by decisions made in electric power design. As the electrification of the vehicle has progressed we now have much more specific vehicle state data available and the means to share this information among on-board computers through serial data link connectivity.

For many years, the computer aided math model has been the foundation for lowering cost and reducing time to market for many manufacturing industries. The automotive industry applies a variety of tools and methods to evaluate the expected vehicle performance to a forever expanding set of requirements. These mathematical predictions of performance are then repeated for both a set of design cycles and a multitude of vehicles in the product portfolio. This paper presents a CAE perspective of the unique problems of the large scale virtual vehicle engineering factory and a set of solutions. Different strategies to create the various complex math models required are explored. These strategies include using COTS FEA pre-processers, producing FEA models internal to the CAD tools, as well as custom built tools, macros and process automation tools.

Conventional HVAC systems adjust the position of a temperature door, to achieve a required air temperature discharged into the passenger compartment. Such systems are based upon the fact that a conventional (non-hybrid) vehicle's engine coolant temperature is controlled to a somewhat constant temperature, using an engine thermostat. Coolant flow rate through the cabin heater core varies as the engine speed changes. EREVs (Extended Range Electric Vehicles) & PHEVs (Plug-In Hybrid Electric Vehicles) have two key vehicle requirements: maximize EV (Electric Vehicle) range and maximize fuel economy when the engine is operating. In EV mode, there is no engine heat rejection and battery pack energy is consumed in order to provide heat to the passenger compartment, for windshield defrost/defog and occupant comfort. Energy consumption for cabin heating must be optimized, if one is to optimize vehicle EV range.

Biodiesel, a fuel comprised of mono-alkyl esters of long-chain fatty acids also known as Fatty Acid Methyl Esters(FAME), derived from vegetable oils or animal fats, has become an important commercial marketplace automotive fuel in the United States (US) and around the world over last few years. FAME biodiesels have many chemical and physical property differences compared to conventional petroleum based diesel fuels. Also, the properties of biodiesel vary based on the feedstock chosen for biodiesel production. One of the key differences between petroleum diesel fuels and biodiesel is the energy content. The energy content, or heating value, is an important property of motor fuel, since it directly affects the vehicle fuel economy. While the energy content can be measured by combustion of the fuel in a bomb calorimeter, this analytical laboratory testing is time consuming and expensive.

This paper proposes a model-based “Cascaded Dual Extended Kalman Filter” (CDEKF) for combined vehicle state estimation, namely, tire vertical forces and parameter identification. A sensitivity analysis is first carried out to recognize the vehicle inertial parameters that have significant effects on tire normal forces. Next, the combined estimation process is separated in two components. The first component is designed to identify the vehicle mass and estimate the longitudinal forces while the second component identifies the location of center of gravity and estimates the tire normal forces. A Dual extended Kalman filter is designed for each component for combined state estimation and parameter identification. Simulation results verify that the proposed method can precisely estimate the tire normal forces and accurately identify the inertial parameters.

The U.S. Renewable Fuel Standard 2 (RFS2) mandates the use of advanced renewable fuels such as cellulosic ethanol to be blended into gasoline in the near future. As such, determining the impact of these new fuel blends on vehicle performance is important. Therefore, General Motors conducted engine dynamometer evaluations on the impact of cellulosic ethanol blends on port fuel injected (PFI) intake valve deposits and gasoline direct injected (GDI) fuel injector plugging. Chemical analysis of the test fuels was also conducted and presented to support the interpretation of the engine results. The chemical analyses included an evaluation of the specified fuel parameters listed in ASTM International's D4806 denatured fuel ethanol specification as well as GC/MS hydrocarbon speciations to help identify any trace level contaminant species from the new ethanol production processes.