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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.

An operational scheme with fuel-lean and exhaust gas dilution in spark-ignited engines increases thermal efficiency and decreases NOx emission, while these operations inherently induce combustion instability and thus large cycle-to-cycle variation in engine. In order to stabilize combustion variations, the development of an advanced ignition system is becoming critical. To quantify the impact of spark-ignition discharge, ignitability tests were conducted in an optically accessible combustion vessel to characterize the flame kernel development of lean methane-air mixture with CO₂ simulating exhaust diluent. A shrouded fan was used to generate turbulence in the vicinity of J-gap spark plug and a Variable Output Ignition System (VOIS) capable of producing a varied set of spark discharge patterns was developed and used as an ignition source. The main feature of the VOIS is to vary the secondary current during glow discharge including naturally decaying and truncated with multiple strikes.

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.

Pending reductions in light duty vehicle PM emissions standards from 10 to 3 mg/mi and below will push the limits of the gravimetric measurement method. At these levels the PM mass collected approaches the mass of non-particle gaseous species that adsorb onto the filter from exhaust and ambient air. This introduces an intrinsic lower limit to filter based measurement that is independent of improvements achieved in weighing metrology. The statistical variability of back-up filter measurements at these levels makes them an ineffective means for correcting the adsorption artifact. The proposed subtraction of a facility based estimate of the artifact will partially alleviate the mass bias from adsorption, but its impact on weighing variability remains a problem that can reach a significant fraction of the upcoming 3 and future 1 mg/mi standards. This paper proposes an improved PM mass method that combines the gravimetric filter approach with real time aerosol measurement.

In order to meet more stringent evaporative emissions requirements, multiple advancements in vehicle fuel system and carbon canister technologies have been made. Regardless of technological advancements, the vapor pressure of the fuel remains a vital property in controlling evaporative emissions. A series of tests were performed to explore the effects of vapor pressure on multiday diurnal evaporative emissions for 9 and 10 psi Reid Vapor Pressure (RVP) 10% ethanol (E10) gasoline-blend fuels, followed by tests with 7 psi RVP E10 gasoline on a subset of the same vehicles. A test procedure was developed to monitor evaporative emissions, canister loading profiles and breakthrough emissions for each of the fuels. A total of five vehicles were tested on all 3 fuels, blended to represent 7, 9, and 10 psi at sea level. Tests were run over 14 days using the United States (U.S.)

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.

Diesel fuels are complex mixtures of thousands of hydrocarbons. Since modeling their combustion characteristics with the inclusion of all hydrocarbon species is not feasible, a hybrid surrogate model approach is used in the present work to represent the physical and chemical properties of three different diesel fuels by using up to 13 and 4 separate hydrocarbon species, respectively. The surrogates are arrived at by matching their distillation profiles and important properties with the real fuel, while the chemistry surrogates are arrived at by using a Group Chemistry Representation (GCR) method wherein the hydrocarbon species in the physical property surrogates are grouped based on their chemical classes, and the chemistry of each class is represented by using up to two hydrocarbon species.

Alkali and alkaline earth metal impurities found in diesel fuels are potential poisons for diesel exhaust catalysts. Using an accelerated aging procedure, a set of production exhaust systems from a 2011 Ford F250 equipped with a 6.7L diesel engine have been aged to an equivalent of 150,000 miles of thermal aging and metal exposure. These exhaust systems included a diesel oxidation catalyst (DOC), selective catalytic reduction (SCR) catalyst, and diesel particulate filter (DPF). Four separate exhaust systems were aged, each with a different fuel: ULSD containing no measureable metals, B20 containing sodium, B20 containing potassium and B20 containing calcium. Metals levels were selected to simulate the maximum allowable levels in B100 according to the ASTM D6751 standard. Analysis of the aged catalysts included Federal Test Procedure emissions testing with the systems installed on a Ford F250 pickup, bench flow reactor testing of catalyst cores, and electron probe microanalysis (EPMA).

In recent years, the residential and transportation sectors have made significant strides in reducing energy consumption, mainly by focusing efforts on low-hanging fruit in each sector independently. This independent viewpoint has been successful in the past because the user needs met and resources consumed in each sector have been clearly distinct. However, the trend towards vehicle electrification has blurred the boundary between the sectors. With both the home and vehicle now relying upon the same energy source, interactions between the systems can no longer be neglected. For example, when tiered utility pricing schemes are considered, the energy consumption of each system affects the cost of the other. In this paper, the authors present an integrated Home-Vehicle Simulation Model (HVSM), allowing the designer to take a holistic view.

Chrysler, Ford, General Motors, the U.S. Environmental Protection Agency (EPA) and the California Air Resources Board (CARB) have collaborated over the past two years to develop an efficiency test for mobile air conditioner (MAC) systems. Because the effect of efficiency differences between different MAC systems and different technologies is relatively small compared to overall vehicle fuel consumption, quantifying these differences has been challenging. The objective of this program was to develop a single dynamic test procedure that is capable of discerning small efficiency differences, and is generally representative of mobile air conditioner usage in the United States. The test was designed to be conducted in existing test facilities, using existing equipment, and within a sufficiently short time to fit standard test facility scheduling. Representative ambient climate conditions for the U.S. were chosen, as well as other test parameters, and a solar load was included.

In-line hydrocarbon (HC) traps are not widely used to reduce HC emissions due to their limited durability, high platinum group metal (PGM) concentrations, complicated processing, and insufficient hydrocarbon (HC) retention temperatures required for efficient conversion by the three-way catalyst component. New trapping materials and system architectures were developed utilizing an engine dynamometer test equipped with dual Fourier Transform Infrared (FTIR) spectrometers for tracking the adsorption and desorption of various HC species during the light-off period. Parallel laboratory reactor studies were conducted which show that the new HC trap formulations extend the traditional adsorption processes (i.e., based on physic-sorption and/or adsorption at acid sites) to chemical reaction mechanisms resulting in oligomerized, dehydro-cyclization, and partial coke formation.

A Ford 2.4-liter 115PS light-duty diesel engine was modified to allow solenoid control of the oil feed to the piston cooling jets, enabling these to be switched on or off on demand. The influence of the jets on piston temperatures, engine thermal state, gaseous emissions and fuel economy has been investigated. With the jets switched off, piston temperatures were measured to be between 23 and 88°C higher. Across a range of speed-load points, switching off the jets increased engine-out emissions of NOx typically by 3%, and reduced emissions of CO by 5-10%. Changes in HC were of the same order and were reductions at most conditions. Fuel consumption increased at low-speed, high-load conditions and decreased at high-speed, low-load conditions. Applying the results to the NEDC drive cycle suggests active on/off control of the jets could reduce engine-out emissions of CO by 6%, at the expense of a 1% increase in NOx, compared to the case when the jets are on continuously.

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.