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Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

Cost reduction in the automotive industry becomes a widely-adopted operational strategy not only for Original Equipment Manufacturers (OEMs) that take cost leader generic corporation strategy, but also for many OEMs that take differentiation generic corporation strategy. Since differentiation generic strategy requires an organization to provide a product or service above the industry average level, a premium is typically included in the tag price for those products or services. Cost reduction measures could increase risks for the organizations that pursue differentiation strategy. Although manufacturers in the automotive industry dramatically improved production efficiency in past ten years, they are still facing the pressure of cost control. The big challenge in cost control for automakers and suppliers is increasing prices of raw materials, energy and labor costs. These costs create constraints for the traditional economic expansion model.

Southwest Research Institute (SwRI) converted a 2012 Buick Regal GS to use an engine with Dedicated EGR™ (D-EGR™). D-EGR is an engine concept that uses fuel reforming and high levels of recirculated exhaust gas (EGR) to achieve very high levels of thermal efficiency [1]. To accomplish reformation of the gasoline in a cost-effective, energy efficient manner, a dedicated cylinder is used for both the production of EGR and reformate. By operating the engine in this manner, many of the sources of losses from traditional reforming technology are eliminated and the engine can take full advantage of the benefits of reformate. The engine in the vehicle was modified to add the following components: the dedicated EGR loop, an additional injector for delivering extra fuel for reformation, a modified boost system that included a supercharger, high energy dual coil offset (DCO) ignition and other actuators used to enable the control of D-EGR combustion.

Computer programs and models are playing an increasing role in simulating vehicle crashworthiness, dynamic, and fuel efficiency. To maximize the effectiveness of these models, the validity and predictive capabilities of these models need to be assessed quantitatively. For a successful implementation of Computer Aided Engineering (CAE) models as an integrated part of the current vehicle development process, it is necessary to develop objective validation metric that has the desirable metric properties to quantify the discrepancy between multiple tests and simulation results. However, most of the outputs of dynamic systems are multiple functional responses, such as time history series. This calls for the development of an objective metric that can evaluate the differences of the multiple time histories as well as the key features under uncertainty.

A copula-based approach for model bias characterization was previously proposed [18] aiming at improving prediction accuracy compared to other model characterization approaches such as regression and Gaussian Process. This paper proposes an adaptive copula-based approach for model bias identification to enhance the available methodology. The main idea is to use cluster analysis to preprocess data, then apply the copula-based approach using information from each cluster. The final prediction accumulates predictions obtained from each cluster. Two case studies will be used to demonstrate the superiority of the adaptive copula-based approach over its predecessor.

To date, model validation metric is prominently designed for non-dynamic model responses. Though metrics for dynamic responses are also available, they are specifically designed for the vehicle impact application and uncertainties are not considered in the metric. This paper proposes the validation metric for general dynamic system responses under uncertainty. The metric makes use of the popular U-pooling approach and extends it for dynamic responses. Furthermore, shape deviation metric was proposed to be included in the validation metric with the capability of considering multiple dynamic test data. One vehicle impact model is presented to demonstrate the proposed validation metric.

Simulation based design optimization has become the common practice in automotive product development. Increasing computer models are developed to simulate various dynamic systems. Before applying these models for product development, model validation needs to be conducted to assess their validity. In model validation, for the purpose of obtaining results successfully, it is vital to select or develop appropriate metrics for specific applications. For dynamic systems, one of the key obstacles of model validation is that most of the responses are functional, such as time history curves. This calls for the development of a metric that can evaluate the differences in terms of phase shift, magnitude and shape, which requires information from both time and frequency domain. And by representing time histories in frequency domain, more intuitive information can be obtained, such as magnitude-frequency and phase-frequency characteristics.

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.

Ultrasonic fatigue tests (testing frequency around 20 kHz) have been conducted on four different cast aluminum alloys each with a distinct composition, heat treatment, and microstructure. Tests were performed in dry air, laboratory air and submerged in water. For some alloys, the ultrasonic fatigue lives were dramatically affected by the environment humidity. The effects of different factors like material composition, yield strength, secondary dendrite arm spacing and porosity were investigated; it was concluded that the material strength may be the key factor influencing the environmental humidity effect in ultrasonic fatigue testing. Further investigation on the effect of chemical composition, especially copper content, is needed.

The use of cooled EGR as a knock suppression tool is gaining more acceptance worldwide. As cooled EGR become more prevalent, some challenges are presented for engine designers. In this study, the impact of cooled EGR on peak cylinder pressure was evaluated. A 1.6 L, 4-cylinder engine was operated with and without cooled EGR at several operating conditions. The impact of adding cooled EGR to the engine on peak cylinder pressure was then evaluated with an attempt to separate the effect due to advanced combustion phasing from the effect of increased manifold pressure. The results show that cooled EGR's impact on peak cylinder pressure is primarily due to the knock suppression effect, with the result that an EGR rate of 25% leads to an almost 50% increase in peak cylinder pressure at a mid-load condition if the combustion phasing is advanced to Knock Limited Spark Advance (KLSA). When combustion phasing was held constant, increasing the EGR rate had almost no effect on PCP.

Although soot-formation processes in diesel engines have been well characterized during the mixing-controlled burn, little is known about the distribution of soot throughout the combustion chamber after the end of appreciable heat release during the expansion and exhaust strokes. Hence, the laser-induced incandescence (LII) diagnostic was developed to visualize the distribution of soot within an optically accessible single-cylinder direct-injection diesel engine during this period. The developed LII diagnostic is semi-quantitative; i.e., if certain conditions (listed in the Appendix) are true, it accurately captures spatial and temporal trends in the in-cylinder soot field. The diagnostic features a vertically oriented and vertically propagating laser sheet that can be translated across the combustion chamber, where “vertical” refers to a direction parallel to the axis of the cylinder bore.

The ongoing pursuit of improved engine efficiency and emissions is driving gasoline low-pressure loop EGR systems into production around the globe. The Dedicated EGR (D-EGR®) engine was developed to minimize some of the challenges of cooled EGR while maintaining its advantages. The D-EGR engine is a high efficiency, low emissions internal combustion engine for automotive and off-highway applications. The core of the engine development focused on a unique concept that combines the efficiency improvements associated with recirculated exhaust gas and the efficiency improvements associated with fuel reformation. To outline the differences of the new engine concept with a conventional LPL EGR setup, a turbocharged 2.0 L PFI engine was modified to operate in both modes. The second part of the cooled EGR engine concept comparison investigates efficiency, knock resistance, combustion stability, and maximum load potential at high load conditions.

In light of the increasingly stringent efficiency and emissions requirements, several new engine technologies are currently under investigation. One of these new concepts is the Dedicated EGR (D-EGR®) engine. The concept utilizes fuel reforming and high levels of recirculated exhaust gas (EGR) to achieve very high levels of thermal efficiency. While the positive impact of reformate, in particular hydrogen, on gasoline engine performance has been widely documented, the on-board reforming process and / or storage of H2 remains challenging. The Water-Gas-Shift (WGS) reaction is well known and has been used successfully for many years in the industry to produce hydrogen from the reactants water vapor and carbon monoxide. For this study, prototype WGS catalysts were installed in the exhaust tract of the dedicated cylinder of a turbocharged 2.0 L in-line four cylinder MPI engine. The potential of increased H2 production in a D-EGR engine was evaluated through the use of these catalysts.

The ongoing pursuit of improved engine efficiency and emissions are driving gasoline low-pressure loop EGR systems into production around the globe. To minimize inevitable downsides of cooled EGR while maintaining its advantages, the Dedicated EGR (D-EGR®) engine was developed. The core of the D-EGR engine development focused on a unique concept that combines the efficiency improvements associated with recirculated exhaust gas and the efficiency improvements associated with fuel reformation. To outline the differences of the new engine concept with a conventional low-pressure loop (LPL) EGR setup, a turbocharged 2.0 L PFI engine was modified to operate in both modes and also compared to the baseline. The first part of the cooled EGR engine concept comparison investigates efficiency, emissions, combustion stability, and robustness at throttled part load conditions.

A series of ignition systems were evaluated for their suitability for high-EGR SI engine applications. Testing was performed in a constant-volume combustion chamber and in a single-cylinder research engine, with EGR rates of up to 40% evaluated. All of the evaluated systems were able to initiate combustion at a simulated 20% EGR level, but not all of the resulting combustion rates were adequate for stable engine operation. High energy spark discharge systems were better, and could ignite a flame at up to 40% simulated EGR, though again the combustion rates were slow relative to that required for stable engine performance. The most effective systems for stable combustion at high EGR rates were systems which created a large effective flame kernel and/or a long kernel lifetime, such as a torch-style prechamber spark plug or a corona discharge igniter.

In this work, a dynamically loaded hydrodynamic journal bearing test rig is developed and introduced. The rig is a novel design, using a hydraulic actuator with fast acting spool valves to apply load to a connecting rod. This force is transmitted through the connecting rod to the large end bearing which is mounted on a spinning shaft. The hydraulic actuator allows for fully variable control and can be used to apply either static load in compression or tension, or dynamic loading to simulate engine operation. A variable speed electric motor controls shaft speed and is synchronized to the hydraulic actuator to accurately simulate loading to represent all four engine strokes. A high precision torque meter enables direct measurements of friction torque, while shaft position is measured via a high precision encoder.

A push for more stringent emissions regulations has resulted in larger, increasingly complex aftertreatment solutions. In particular, oxides of nitrogen (NOX) and particulate matter (PM) have been controlled using two separate systems, selective catalytic reduction (SCR) and the catalyze diesel particulate filter (CDPF), or the functionality has been combined into a single device producing the SCR on filter (SCRoF). The SCRoF forgoes beneficial NO2 production present in the CDPF to avoid NH3 oxidation which occurs when using platinum group metals (PGM) for oxidation. In this study, mixed-metal oxides are shown to oxidize NO to NO2 without appreciable NH3 oxidation. This selectivity leads to enhanced performance when combined with a typical Cu-zeolite catalyst.

Battery temperature variations have a strong effect on both battery aging and battery performance. Significant temperature variations will lead to different battery behaviors. This influences the performance of the Hybrid Electric Vehicle (HEV) energy management strategies. This paper investigates how variations in battery temperature will affect Lithium-ion battery aging and fuel economy of a HEV. The investigated energy management strategy used in this paper is the Equivalent Consumption Minimization Strategy (ECMS) which is a well-known energy management strategy for HEVs. The studied vehicle is a Honda Civic Hybrid and the studied battery, a BLS LiFePO4 3.2Volts 100Ah Electric Vehicle battery cell. Vehicle simulations were done with a validated vehicle model using multiple combinations of highway and city drive cycles. The battery temperature variation is studied with regards to outside air temperature.

This paper presents a combined numerical and experimental investigation of the characteristics of spark discharge in a spark-ignition engine. The main objective of this work is to gain insights into the spark discharge process and early flame kernel development. Experiments were conducted in an inert medium within an optically accessible constant-volume combustion vessel. The cross-flow motion in the vessel was generated using a previously developed shrouded fan. Numerical modeling was based on an existing discharge model in the literature developed by Kim and Anderson. However, this model is applicable to a limited range of gas pressures and flow fields. Therefore, the original model was evaluated and improved to predict the behavior of spark discharge at pressurized conditions up to 45 bar and high-speed cross-flows up to 32 m/s. To accomplish this goal, a parametric study on the spark channel resistance was conducted.