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The computer-aided engineering (CAE) automation study requires a large disk space and a premium processor. If all finite element (FE) models run locally, it may crash the local machine, and if the FE model runs on high-performance computing (HPC), transferring data from the server to the local machine to do the optimization may cause latency issues. This automation study provides a unique road map to optimize the design by working efficiently using the initial setup on the local machine, running an analysis of a large number of FE models on HPC, and performing optimization on the server. CAE Automation process has been demonstrated using a case study on a driveline component, crush spacer. Crush spacer is a very critical engineering design because, first, it provides the minimum required preload to the bearing inner races to keep them in position and, second, it endures a number of duty cycles.

Design optimization methods are commonly used for weight reduction subjecting to multiple constraints in automotive industry. One of the major challenges remained is to deal with a large number of design variables for large-scale design optimization problems effectively. In this paper, a new approach based on fuzzy rough set is proposed to address this issue. The concept of rough set theory is to deal with redundant information and seek for a reduced design variable set. The proposed method first exploits fuzzy rough set to screen out the insignificant or redundant design variables with regard to the output functions, then uses the reduced design variable set for design optimization. A vehicle body structure is used to demonstrate the effectiveness of the proposed method and compare with a traditional weighted sensitivity based main effect approach.

One of the major challenges in multiobjective, multidisciplinary design optimization (MDO) is the long computational time required in evaluating the new designs' performances. To shorten the cycle time of product design, a data mining-based strategy is developed to improve the efficiency of heuristic optimization algorithms. Based on the historical information of the optimization process, clustering and classification techniques are employed to identify and eliminate the low quality and repetitive designs before operating the time-consuming design evaluations. The proposed method improves design performances within the same computation budget. Two case studies, one mathematical benchmark problem and one vehicle side impact design problem, are conducted as demonstration.

Robustness/Reliability Assessment and Optimization (RRAO) is often computationally expensive because obtaining accurate Uncertainty Quantification (UQ) may require a large number of design samples. This is especially true where computationally expensive high fidelity CAE simulations are involved. Approximation methods such as the Polynomial Chaos Expansion (PCE) and other Response Surface Methods (RSM) have been used to reduce the number of time-consuming design samples needed. However, for certain types of problems require the RRAO, one of the first question to consider is which method can provide an accurate and affordable UQ for a given problem. To answer the question, this paper tests the PCE, RSM and pure sampling based approaches on each of the three selected test problems: the Ursem Waves mathematical function, an automotive muffler optimization problem, and a vehicle restraint system optimization problem.

Particle swarm optimization (PSO) is a relatively new stochastic optimization algorithm and has gained much attention in recent years because of its fast convergence speed and strong optimization ability. However, PSO suffers from premature convergence problem for quick losing of diversity. That is to say, if no particle discovers a new superiority position than its previous best location, PSO algorithm will fall into stagnation and output local optimum result. In order to improve the diversity of basic PSO, design of experiment technique is used to initialize the particle swarm in consideration of its space-filling property which guarantees covering the design space comprehensively. And the optimization procedure of PSO is divided into two stages, optimization stage and improving stage. In the optimization stage, the basic PSO initialized by Optimal Latin hypercube technique is conducted.

Finite Element (FE) models are widely used in automotive for vehicle design. Even with increasing speed of computers, the simulation of high fidelity FE models is still too time-consuming to perform direct design optimization. As a result, response surface models (RSMs) are commonly used as surrogates of the FE models to reduce the turn-around time. However, RSM may introduce additional sources of uncertainty, such as model bias, and so on. The uncertainty and model bias will affect the trustworthiness of design decisions in design processes. This calls for the development of stochastic model interpolation and extrapolation methods that can address the discrepancy between the RSM and the FE results, and provide prediction intervals of model responses under uncertainty.

This study presents the utilization of the hardware-in-the-loop (HIL) approach for regenerative braking (regen) control enhancement efforts for the power split hybrid vehicle architecture. The HIL stand used in this study includes a production brake control module along with the hydraulic brake system, constituted of an accelerator/brake pedal assembly, electric vacuum booster and pump, brake hydraulic circuit and four brake calipers. This work presents the validation of this HIL simulator with real vehicle data, during mild and heavy braking. Then by using the HIL approach, regen control is enhanced, specifically for two cases. The first case is the jerk in deceleration caused by the brake booster delay, during transitions from regen to friction braking. As an example, the case where the regen is ramped out at a low speed threshold, and the hydraulic braking ramped in, can be considered.

For spark-ignition gasoline engines operating under the wide speed and load conditions required for light duty vehicles, ignition quality limits the ability to minimize fuel consumption and NOx emissions via dilution under light and part load conditions. In addition, during transients including tip-outs, high levels of dilution can occur for multiple combustion events before either the external exhaust gas can be adjusted and cleared from the intake or cam phasing can be adjusted for correct internal dilution. Further improvement and a thorough understanding of the impact of the ignition system on combustion near the dilution limit will enable reduced fuel consumption and robust transient operation. To determine and isolate the effects of multiple parameters, a variable output ignition system (VOIS) was developed and tested on a 3.5L turbocharged V6 homogeneous charge direct-injection gasoline engine with two spark plug gaps and three ignition settings.

As a renewable energy source, the ethanol fuel was employed with a diesel fuel in this study to improve the cylinder charge homogeneity for high load operations, targeting on ultra-low nitrogen oxides (NOx) and smoke emissions. A light-duty diesel engine is configured to adapt intake port fuelling of the ethanol fuel while keeping all other original engine components intact. High load experiments are performed to investigate the combustion control and low emission enabling without sacrificing the high compression ratio (18.2:1). The intake boost, exhaust gas recirculation (EGR) and injection pressure are independently controlled, and thus their effects on combustion and emission characteristics of the high load operation are investigated individually. The low temperature combustion is accomplished at high engine load (16~17 bar IMEP) with regulation compatible NOx and soot emissions.

U.S. federal vehicle emission standards effective in 2007 require tight control of NOx and hydrocarbon emissions. For light-duty vehicles, the current standard of Tier 2 Bin 5 is about 0.07 g/mi NOx and 0.09 g/mi NMOG (non-methane organic gases) at 120,000 mi. However, the proposed future standard is 0.03 g/mi for NMOG + NOx (~SULEV30) at 150,000 mi. There is a significant improvement needed in catalyst system efficiencies for diesel vehicles to achieve the future standard, mainly during cold start. In this study, a less than 6000 lbs diesel truck equipped with an advanced urea Selective Catalytic Reduction (SCR) system was used to pursue lower tailpipe emissions with an emphasis on vehicle calibration and catalyst package. The calibration was tuned by optimizing exhaust gas recirculation (EGR) fuel injection and cold start strategy to generate desirable engine-out emissions balanced with reasonable temperatures.

Exhaust gas recirculation (EGR) coolers are commonly used in diesel engines to reduce the temperature of recirculated exhaust gases in order to reduce NOx emissions. The presence of a cool surface in the hot exhaust causes particulate soot deposition as well as hydrocarbon and water condensation. Fouling experienced through deposition of particulate matter and hydrocarbons results in degraded cooler effectiveness and increased pressure drop. In this study, a visualization test setup is designed and constructed so that the effect of water condensation on the deposit formation and growth at various coolant temperatures can be studied. A water-cooled surrogate rectangular channel is employed to represent the EGR cooler. One side of the channel is made of glass for visualization purposes. A medium duty diesel engine is used to generate the exhaust stream.

A new diesel engine, called the 6.7L Power Stroke® V-8 Turbo Diesel and code named "Scorpion" was designed and developed by Ford Motor Company for the full-size pickup truck and light commercial vehicle markets. A high pressure Exhaust Gas Recirculation (EGR) layout in combination with a Variable Geometry Turbine (VGT) is used to deliver cooled EGR for in-cylinder NOx reduction. The cylinder-to-cylinder variation of EGR and swirl ratio is tightly controlled by the careful design of the EGR mixer and intake system flow path to reduce variability of cylinder-out PM and NOx emissions. 3D-CFD studies were used to quickly screen several EGR mixer designs based on mixing efficiency and pressure drop considerations. To optimize the intake system, 1D-3D co-simulation methodology with AVL-FIRE and AVL-BOOST has been used to assess the cylinder-to-cylinder EGR distribution and dynamic swirl.

ACOUSTOMIZE™ is a new method of acoustic evaluation used for the purpose of understanding and optimizing NVH performance of vehicles. The following paper documents a case study of the ACOUSTOMIZE™ test methodology on a passenger car BIW. This study includes an analysis of noise flow through BIW locations, a comparison of noise sound levels through BIW cavities with and without a sound treatment package and a comparison of the original cavity sealing design package consisting of baffles, tapes and baggies to low density polyurethane NVH Foam. The results of the study show detection of complex BIW pass throughs that the body leakage test (BLT) was not able to find. In addition, the data shows improved noise reduction with the low density polyurethane foam versus the original cavity sealing design package.

A benchmark study was conducted to assess the capability of an open source CFD based process to accurately simulate the physics of the flow field around various vehicle types. The ICON FOAMpro process was used to simulate the flow field of four baseline geometries of a Truck, CD-Car, B-Car and an SUV. Further studies were carried out to assess the effects of geometry variations on the predicted aerodynamic lift and drag. A Detached-Eddy Simulation (DES) approach was chosen for the benchmarks. In addition to aerodynamic lift and drag values, the results for surface pressure data, surface and wake flow fields were calculated. These results were compared with values obtained using Ford's existing CFD processes.

Accessory belt “chirp” noise is a major quality issue in the automotive and truck industry. Chirp noise control is often achieved by very tight pulley alignment, a guideline being .33 degree maximum belt entry angle into each grooved pulley. Occasionally belts will chirp at pulleys where the system alignment is this good or better. This study offers an explanation for such occurrences. This is a study to see if fundament groove side sticking theory correlates with the belt entry angle, and how the coefficient of friction relates to this entry angle. The study combines theory with lab data. In summary, the study fundamentally links the coefficient of friction of the belt to the belt chirp noise phenomenon, and allows the projection of a belt's general tendency to chirp to be predicted by the measurement of belt coefficient of friction on a test stand.