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Disc brakes operate with very close proximity of the brake pads and the brake rotor, with as little as a tenth of a millimeter of movement of the pads required to bring them into full contact with the rotor to generate braking torque. It is usual for a disc brake to operate with some amount of residual drag in the fully released state, signifying constant contact between the pads and the rotor. With this contact, every miniscule movement of the rotor pushes against the brake pads and changes the forces between them. Sustained loads on the brake corner, and maneuvers such as cornering, can both produce rotor movement relative to the caliper, which can push it steadily against one or both of the brake pads. This can greatly increase the residual force in the caliper, and increase drag. This dependence of drag behavior on the movement of the brake rotor creates some vehicle-dependent behavior.

In the context of vehicle electrification, improving vehicle aerodynamics is not only critical for efficiency and range, but also for driving experience. In order to balance the necessary trade-offs between drag and downforce without significant impact on the vehicle styling, we see an increasing amount of active aerodynamic solutions on high-end passenger vehicles. Active rear spoilers are one of the most common active aerodynamic features. They deploy at high vehicle speed when additional downforce is required [1, 2]. For a vehicle with an active rear spoiler, the aerodynamic performance is typically predicted through simulations or physical testing at different static spoiler positions. These positions range from fully stowed to fully deployed. However, this approach does not provide any information regarding the transient effects during the deployment of the rear spoiler, which can be critical to understanding key performance aspects of the system.

Simultaneous two-component measurements of gas velocity and multi-dimensional numerical simulation are employed to characterize the evolution of the in-cylinder turbulent flow structure in a re-entrant bowl-in-piston engine under motored operation. The evolution of the mean flow field, turbulence energy, turbulent length scales, and the various terms contributing to the production of the turbulence energy are correlated and compared, with the objectives of clarifying the physical mechanisms and flow structures that dominate the turbulence production and of identifying the source of discrepancies between the measured and simulated turbulence fields. Additionally, the applicability of the linear turbulent stress modeling hypothesis employed in the k-ε model is assessed using the experimental mean flow gradients, turbulence energy, and length scales.

In-cylinder flow and combustion processes simulated with the standard k-ε turbulence model and with an alternative model-employing a non-linear, quadratic equation for the turbulent stresses-are contrasted for both motored and fired engine operation at two loads. For motored operation, the differences observed in the predictions of mean flow development are small and do not emerge until expansion. Larger differences are found in the spatial distribution and magnitude of turbulent kinetic energy. The non-linear model generally predicts lower energy levels and larger turbulent time scales. With fuel injection and combustion, significant differences in flow structure and in the spatial distribution of soot are predicted by the two models. The models also predict considerably different combustion efficiencies and NOx emissions.

In-cylinder fluid velocity is measured in an optically accessible, fired HSDI engine at idle. The velocity field is also calculated, including the full induction stroke, using multi-dimensional fluid dynamics and combustion simulation models. A detailed comparison between the measured and calculated velocities is performed to validate the computed results and to gain a physical understanding of the flow evolution. Motored measurements are also presented, to clarify the effects of the fuel injection process and combustion on the velocity field evolution. The calculated mean in-cylinder angular momentum (swirl ratio) and mean flow structures prior to injection agree well with the measurements. Modification of the mean flow by fuel injection and combustion is also well captured.

Engine-out CO emission and fuel conversion efficiency were measured in a highly-dilute, low-temperature diesel combustion regime over a swirl ratio range of 1.44-7.12 and a wide range of injection timing. At fixed injection timing, an optimal swirl ratio for minimum CO emission and fuel consumption was found. At fixed swirl ratio, CO emission and fuel consumption generally decreased as injection timing was advanced. Moreover, a sudden decrease in CO emission was observed at early injection timings. Multi-dimensional numerical simulations, pressure-based measurements of ignition delay and apparent heat release, estimates of peak flame temperature, imaging of natural combustion luminosity and spray/wall interactions, and Laser Doppler Velocimeter (LDV) measurements of in-cylinder turbulence levels are employed to clarify the sources of the observed behavior.

An investigation of high speed direct injection (DI) compression ignition (CI) engine combustion fueled with gasoline (termed GDICI for Gasoline Direct-Injection Compression Ignition) in the low temperature combustion (LTC) regime is presented. As an aid to plan engine experiments at full load (16 bar IMEP, 2500 rev/min), exploration of operating conditions was first performed numerically employing a multi-dimensional CFD code, KIVA-ERC-Chemkin, that features improved sub-models and the Chemkin library. The oxidation chemistry of the fuel was calculated using a reduced mechanism for primary reference fuel combustion. Operation ranges of a light-duty diesel engine operating with GDICI combustion with constraints of combustion efficiency, noise level (pressure rise rate) and emissions were identified as functions of injection timings, exhaust gas recirculation rate and the fuel split ratio of double-pulse injections.

Prior HCCI optical engine experiments utilizing laser-induced fluorescence (LIF) measurements of stratified fuel-air mixtures have demonstrated the utility of probability density function (PDF) statistics for correlating mixture preparation with combustion. However, PDF statistics neglect all spatial details of in-cylinder fuel distribution. The current computational paper examines the effects of spatial fuel distribution on combustion using a novel combination of a 3-D CFD model with a 1-D linear-eddy model of turbulent mixing. In the simulations, the spatial coarseness of initial fuel distribution prior to the start of heat release is varied while keeping PDF statistics constant. Several cases are run, and as the initial mixture is made coarser, combustion phasing monotonically advances due to high local equivalence ratios that persist longer. The effect of turbulent mixing is more complex.

Spark-ignition (SI) engine efficiency is typically limited by fuel auto-ignition resistance, which is described in practice by the Research Octane Number (RON) and the Motor Octane Number (MON). The goal of this work is to assess whether fuel properties (i.e. RON, MON, and heat of vaporization) are sufficient to describe the antiknock behavior of varying gasoline formulations in modern engines. To this end, the auto-ignition resistance of three compositionally dissimilar gasoline-like fuels with identical RON values and varying or non-varying MON values were evaluated in a modern, prototype, 12:1 compression ratio, high-swirl (by nature of intake valve deactivation), directly injected spark ignition (DISI) engine at 1400 RPM. The three gasolines are an alkylate blend (RON=98, MON=97), a blend with high aromatic content (RON=98, MON=88), and a blend of 30% ethanol by volume with a gasoline BOB (RON=98, MON=87; see Table 2 for details).

The wedge clutch takes advantages of small actuation force/torque, space-saving and energy-saving. However, big challenge arises from the varying self-reinforced ratio due to the varying friction coefficient inevitably affected by temperature and wear. In order to improve the smoothness and synchronization time of the slipping process of the wedge clutch, this paper proposes a self-tuning PID controller based on Lyapunov principle. A new Lyapunov function is developed for the wedge clutch system. Simulation results show that the self-tuning PID obtains much less error than the conventional PID with fixed gains. Moreover, the self-tuning PID is more adaptable to the variation of the friction coefficient for the error is about 1/5 of the conventional PID.

General corrosion protection of sheet materials such as steel used in automobile construction has reached a high level of performance, due primarily to the incorporation of mill-applied treatments such as electrogalvanizing, galvannealing and other coil-coating processes developed over the last half century. While such treatments have greatly extended the corrosion resistance of steel and its various body constructs, attention is now focused on aspects of the manufacturing process wherein these intended protections are compromised by such features as weldments, joins, cut edges and extreme metal deformations such as hems. A novel metal deposition process, based on high-velocity impact fusion of solid metal particles, has been used to extend the corrosion resistance of base steel and pre-galvanized sheet, by selectively placing highly controlled depositions of zinc and other sacrificial materials in close proximity to critical manufacturing details.

The paper presents a robust adaptive control technique for precise regulation of a port fuel injection + direct injection (PFI+DI) system, a dual fuel injection configuration adopted in modern gasoline engines to boost performance, fuel efficiency, and emission reduction. Addressing parametric uncertainties on the actuators, inherent in complex fuel injection systems, the proposed approach utilizes an indirect model reference adaptive control scheme. To accommodate the increased control complexity in PFI+DI and the presence of additional uncertainties, a nonlinear plant model is employed, incorporating dynamics of the exhaust burned gas fraction. The primary objective is to optimize engine performance while minimizing fuel consumption and emissions in the presence of uncertainties. Stability and tracking performance of the adaptive controller are evaluated to ensure safe and reliable system operation under various conditions.

The reaction zone of a diesel fuel jet stabilizes at a location downstream of the fuel injector once the initial autoignition phase is over. This distance is referred to as flame lift-off length. Recent investigations have examined the effects of a wide range of parameters (injection pressure, orifice diameter, and ambient gas temperature, density and oxygen concentration) on lift-off length under quiescent diesel conditions. Many of the experimental trends in lift-off length were in agreement with scaling laws developed for turbulent, premixed flame propagation in gas-jet lifted flames at atmospheric conditions. However, several effects did not correlate with the gas-jet scaling laws, suggesting that other mechanisms could be important to lift-off stabilization at diesel conditions. This paper shows experimental evidence that ignition processes affect diesel lift-off stabilization.

This paper describes research and development for reducing the aerodynamic drag of heavy vehicles by demonstrating new approaches for the numerical simulation and analysis of aerodynamic flow. In addition, greater use of newly developed computational tools holds promise for reducing the number of prototype tests, for cutting manufacturing costs, and for reducing overall time to market. Experimental verification and validation of new computational fluid dynamics methods are also an important part of this approach. Experiments on a model of an integrated tractor-trailer are underway at NASA Ames Research Center and the University of Southern California. Companion computer simulations are being performed by Sandia National Laboratories, Lawrence Livermore National Laboratory, and California Institute of Technology using state-of- the-art techniques, with the intention of implementing more complex methods in the future.

In this work computational and experimental approaches are combined to characterize in-cylinder flow structures and local flow field properties during operation of the Sandia 1.9L light-duty optical Diesel engine. A full computational model of the single-cylinder research engine was used that considers the complete intake and exhaust runners and plenums, as well as the adjustable throttling devices used in the experiments to obtain different swirl ratios. The in-cylinder flow predictions were validated against an extensive set of planar PIV measurements at different vertical locations in the combustion chamber for different swirl ratio configurations. Principal Component Analysis was used to characterize precession, tilting and eccentricity, and regional averages of the in-cylinder turbulence properties in the squish region and the piston bowl.

Thermal cabin comfort is the largest consumer of battery energy second only to propulsion in Battery Electric Vehicles (BEV’s). Accurate prediction of thermal comfort in the vehicle cabin with fast turnaround times will allow engineers to study the impact of various thermal comfort technologies and develop energy efficient Heating, Ventilation and Air Conditioning (HVAC) systems. In this study a novel data-driven model based on physics-guided Sparse Identification of Nonlinear Dynamics (SINDy) method was developed to predict Equivalent Homogeneous Temperature (EHT), Mean Radiant Temperature (MRT) and cabin air temperature under transient conditions and drive cycles. EHT is a recognized measure of the total heat loss from the human body that can be used to characterize highly non-uniform thermal environments such as a vehicle cabin. The SINDy model was trained on drive cycle data from Climatic Wind Tunnel (CWT) for a representative Battery Electric Vehicle.

This paper presents a study of the turbulence field in an optical diesel engine operated under motored conditions using both large eddy simulation (LES) and Particle Image Velocimetry (PIV). The study was performed in a laboratory optical diesel engine based on a recent production engine from VOLVO Car. PIV is used to study the flow field in the cylinder, particularly inside the piston bowl that is also optical accessible. LES is used to investigate in detail the structure of the turbulence, the vortex cores, and the temperature field in the entire engine, all within a single engine cycle. The LES results are compared with the PIV measurements in a 40 × 28 mm domain ranging from the nozzle tip to the cylinder wall. The LES grid consists of 1283 cells. The grid dynamically adjusts itself as the piston moves in the cylinder so that the engine cylinder, including the piston bowl, is described by the grid.

Styrene-Butadiene Rubber (SBR), a copolymer of butadiene and styrene, is widely used in the automotive industry due to its high durability and resistance to abrasion, oils and oxidation. Some of the common applications include tires, vibration isolators, and gaskets, among others. This paper characterizes the dynamic behavior of SBR and discusses the suitability of a visco-elastic model of elastomers, known as the Kelvin model, from a mathematical and physical point of view. An optimization algorithm is used to estimate the parameters of the Kelvin model. The resulting model was shown to produce reasonable approximations of measured dynamic stiffness. The model was also used to calculate the self heating of the elastomer due to energy dissipation by the viscous damping components in the model. Developing such a predictive capability is essential in understanding the dynamic behavior of elastomers considering that their dynamic stiffness can in general depend on temperature.

Advanced rechargeable lithium-ion batteries are presently being developed and commercialized worldwide for use in consumer electronics, military and space applications. The motivation behind these efforts involves, among other things, a favorable combination of energy and power density. For some of the applications the power sources may need to perform at a reasonable rate at subambient temperatures. Given the nature of the lithium-ion cell chemistry the low temperature performance of the cells may not be very good. At Sandia National Laboratories, we have used different electrochemical techniques such as impedance and charge/discharge at ambient and subambient temperatures to probe the various electrochemical processes that are occurring in Li-ion cells. The purpose of this study is to identify the component that reduces the cell performance at subambient temperatures.

The Lockheed Martin Low-Speed Wind Tunnel (LSWT) is a closed-return wind tunnel with two solid-wall test sections. This facility originally entered into service in 1967 for aerodynamic research of aircraft in low-speed and vertical/short take-off and landing (V/STOL) flight. Since this time, the client base has evolved to include a significant level of automotive aerodynamic testing, and the needs of the automotive clientele have progressed to include acoustic testing capability. The LSWT was therefore acoustically upgraded in 2016 to reduce background noise levels and to minimize acoustic reflections within the low-speed test section (LSTS). The acoustic upgrade involved detailed analysis, design, specification, and installation of acoustically treated wall surfaces and turning vanes in the circuit as well as low self-noise acoustic wall and ceiling treatment in the solid-wall LSTS.