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Recent advancements in simulation software and computational hardware make it realizable to simulate a full vehicle system comprised of multiple sub-models developed in different modeling languages. The so-called, co-simulation allows one to develop a control strategy and evaluate various aspects of a vehicle system, such as fuel efficiency and vehicle drivability, in a cost-effective manner. In order to study the feasibility of the synchronized parallel processing in co-simulation this paper presents two co-simulation frameworks for a complete vehicle system with multiple heterogeneous subsystem models. In the first approach, subsystem models are co-simulated in a serial configuration, and the same sub-models are co-simulated in a parallel configuration in the second approach.

An investigation of high speed direct injection (DI) compression ignition (CI) engine combustion fueled with gasoline injected using a triple-pulse strategy in the low temperature combustion (LTC) regime is presented. This work aims to extend the operation ranges for a light-duty diesel engine, operating on gasoline, that have been identified in previous work via extended controllability of the injection process. The single-cylinder engine (SCE) was operated at full load (16 bar IMEP, 2500 rev/min) and computational simulations of the in-cylinder processes were performed using 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 chosen to match ignition characteristics of the gasoline fuel used for the SCE experiments.

Recently, high-speed optical imaging data for a single operating point of a spray-guided gasoline engine has, along with the flamelet model and the G-equation theory, enabled the development of the new spark-ignition model SparkCIMM. Within its framework, detailed chemistry flamelet models capture the experimental feature of multiple localized ignition events along the excessively stretched and restriking spark channel, as well as the observations of non-spherical highly corrugated early turbulent flame fronts. The developed flamelet models account for the substantial turbulent fluctuations in equivalence ratio and enthalpy present under spray-guided conditions. A non-unity Lewis number formulation captures the deficient species diffusion into the highly curved flame reaction zone.

An iterative learning control (ILC) algorithm has been developed for a test cell electro-hydraulic, fully flexible valve actuation system to track valve lift profile under steady-state and transient operation. A dynamic model of the plant was obtained from experimental data to design and verify the ILC algorithm. The ILC is implemented in a prototype controller. The learned control input for two different lift profiles can be used for engine transient tests. Simulation and bench test are conducted to verify the effectiveness and robustness of this approach. The simple structure of the ILC in implementation and low cost in computation are other crucial factors to recommend the ILC. It does not totally depend on the system model during the design procedure. Therefore, it has relatively higher robustness to perturbation and modeling errors than other control methods for repetitive tasks.

Spot, or distributed, cooling and heating is an energy efficient way of delivering comfort to an occupant in the car. This paper describes an approach to distributed cooling in the vehicle. A two passenger CFD model of an SUV cabin was developed to obtain the solar and convective thermal loads on the vehicle, characterize the interior thermal environment and accurately evaluate the fluid-thermal environment around the occupants. The present paper focuses on the design and CFD analysis of the energy efficient HVAC system with spot cooling. The CFD model was validated with wind tunnel data for its overall accuracy. A baseline system with conventional HVAC air was first analyzed at mid and high ambient conditions. The airflow and cooling delivered to the driver and the passenger was calculated. Subsequently, spot cooling was analyzed in conjunction with a much lower conventional HVAC airflow.

This study investigates a novel approach towards boosted HCCI operation, which makes use of all engine system components in order to maximize overall efficiency. Four-cylinder boosted HCCI engines have been modeled employing valve strategies and turbomachines that enable high load operation with significant efficiency benefits. A commercially available engine simulation software, coupled to the University of Michigan HCCI combustion and heat transfer correlations, was used to model the HCCI engines with three different boosting configurations: turbocharging, variable geometry turbocharging and combined supercharging with turbocharging. The valve strategy features switching from low-lift Negative Valve Overlap (NVO) to high-lift Positive Valve Overlap (PVO) at medium loads. The new operating approach indicates that heating of the charge from external compression is more efficient than heating by residual gas retention strategies.

Driving through intersections can be potentially dangerous because nearly 23 percent of the total automotive related fatalities and almost 1 million injury-causing crashes occur at or within intersections every year [1]. The impact of traffic intersections on trip delays also leads to waste of human and natural resources. Our goal is to increase the safety and throughput of traffic intersections using co-operative driving. In earlier work [2], we have proposed a family of vehicular network protocols, which use Dedicated Short Range Communications (DSRC) and Wireless Access in Vehicular Environment (WAVE) technologies to manage a vehicle's movement at intersections Specifically, we have provided a collision detection algorithm at intersections (CDAI) to avoid potential crashes at or near intersections and improve safety. We have shown that vehicle-to-vehicle (V2V) communications can be used to significantly decrease the trip delays introduced by traffic lights and stop signs.

A displacement-based CAE analysis is applied to liftgate chucking noise problems. A CAE simulation model of a small-size sport utility vehicle (SUV) is simulated with a set of realistic road loads as a time transient simulation. The model contains a trimmed vehicle, a liftgate and structural body-liftgate interface components such as the latch-striker wire, contact wedges and slam bumpers. Simulation design of experiments (DOE) is carried out with the model. As performance measures, the relative displacements at the contact points of the interface components are selected, since they are considered the direct cause of liftgate chucking. As design variables, body structure stiffness, liftgate stiffness, liftgate opening stiffness, stiffness characteristics of the interface components and additional liftgate mass are selected. Results of the simulation DOE is post-processed, and response surface models (RSM) are fit for the performance measures.

In today's highly competitive marketplace and ever-shrinking vehicle development cycle, automotive HVAC engineers are constantly challenged to develop systems that deliver adequate thermal comfort at lower cost and higher fuel-efficiency. However, in the absence of a reliable predictive tool that is capable of quantifying thermal comfort early in the vehicle development program, OEMs employ expensive and time-consuming human subject test rides to assess HVAC system's performance. In order to address this issue, a Computational Fluid Dynamics (CFD) model of a virtual thermal manikin in a passenger cabin is developed in this study. The model is capable of providing thermal sensations, as experienced by humans, under any arbitrary thermal environment. Additionally, the model can provide sensitivity of various critical parameters, such as solar load, A/C discharge outlet air flow-rate and temperature, A/C outlet locations, various HVAC modes etc., to thermal sensation.

The comfort assessment of seats in the automotive industry has historically been accomplished by subjective ratings. This approach is expensive and time consuming since it involves multiple prototype seats and numerous people in supporting processes. In order to create a more efficient and robust method, objective metrics must be developed and utilized to establish measurable boundaries for seat performance. Objective measurements already widely accepted, such as IFD (Indentation Force Deflection) or CFD (Compression Force Deflection) [1], have significant shortcomings in defining seat comfort. The most obvious deficiency of these component level tests is that they only deal with a seats' foam rather than the system response. Consequently, these tests fail to take into account significant factors that affect seat comfort such as trim, suspension, attachments and other components.

An Arrhenius combustion model (chemically controlled model) with a spark-energy deposition model having a moving spherical ignition source in the Converge CFD code is validated with a single-cylinder spray-guided SIDI engine at idle-like lean-burn operating conditions with both single- and double-pulse fuel injection. It was found that a fine mesh is required for accurate solving of "laminar-flame" like reaction front propagation. A reduced chemistry mechanism for iso-octane is used as gasoline surrogate. The effects of spark advance were studied by the simulation and experiment. The results show that this modeling approach can provide reasonable predictions for the spray-guided SIDI engine with single- and double-pulse injections.

Automobile drivers/passengers perceive automatic transmission (AT) shift quality through the torque transferred by the transmission. Clearly, torque regulation is important for transmission control. Unfortunately, a physical torque sensor has been too costly for production applications. With no torque measurement for feedback, controls in AT is mainly implemented in an open-loop fashion. Therefore, complicated adaptation algorithms are necessary while undesired shifts may still occur. To further simplify the controls and enhance its consistency and robustness, a direct torque feedback has long been desired in transmission control synthesis and development. A “virtual” torque sensor (VTS) algorithm has recently been developed to show a good potential in estimating relative torque along transmission output shaft using transmission output speed sensor and wheel speed sensors.

This work is to propose a new Iterative Learning Observer (ILO)-based strategy for State Of Charge (SOC) estimation. The ILO is able to estimate the SOC in real time while identifying modeling errors and/or disturbances at the same time. An Electrical-Circuit Model (ECM) is adopted to characterize the Lithium-ion battery behavior. The ILO is designed based on this ECM and the stability is proved. Several experiments are conducted and the collected data is used to extract ECM parameters. The effectiveness of the estimated SOCs via ILO is verified by the experimental results. This implies that the ILO-based SOC determination scheme is effective to identify the SOC in real time.

In the last few years, the application of downsizing and turbocharging to internal combustion engines has considerably increased due to the proven potential of this technology to increase engine efficiency. Variable geometry turbines have been largely adopted to optimize the exhaust energy recovery over a large operating range. Two-stage turbocharger systems have also been studied as a solution to improve engine low-end torque and efficiency, with the first units currently available on the market. However, the compressor technology is today still based on fixed geometry machines, which are sized to efficiently operate at the maximum air flow and therefore lead to poor efficiency values at low air flow conditions. Furthermore, the surge limits prevents the full capabilities of VGT systems to increase the boosting at low engine speed.

The focus of this study is to validate the predictive capability of a recently developed physiology based thermal comfort modeling tool in a realistic thermal environment of a vehicle passenger compartment. Human subject test data for thermal sensation and comfort was obtained in a climatic wind tunnel for a cross-over vehicle in a relatively warm thermal environment including solar load. A CFD/thermal model that simulates the vehicle operating conditions in the tunnel, is used to provide the necessary inputs required by the stand-alone thermal comfort tool. Comparison of the local and the overall thermal sensation and comfort levels between the human subject test and the tool's predictions shows a reasonably good agreement. The next step is to use this modeling technique in designing and developing energy-efficient HVAC systems without compromising thermal comfort of the vehicle occupants.

A multidisciplinary toolset integrating ANSYS FLUENT CFD solver and GM in-house thermal system design tool - e-Thermal has been developed to design automotive HVAC systems. This toolset utilizes COM software interface standard of MS Windows for inter-process communication at simulation run-time to synchronize the two applications and to exchange data. In this report, first, the implementation of this fully transient, coupled method between FLUENT CFD and e-Thermal is introduced. We then apply this integrated tool to simulate a transient A/C operating cycle including hot-soak and cool-down of a cabin. The coupled simulation consists of an A/C and an Air-Handling (HVAC module) system models, and a cabin CFD model. It demonstrates that the coupled method can simulate fully transient HVAC system operations in a vehicle.

Vehicle manufacturers have developed new vehicle and diesel engine technologies compatible with B6-B20 biodiesel blends meeting ASTM D7467, “Standard Specification for Diesel Fuel Oil, Biodiesel Blend (B6 to B20).” However, recent U.S. market place fuel surveys have shown that many retail biodiesel samples are out of specification. A vehicle designed to use biodiesel blends is likely to encounter occasional use of poor quality biodiesel fuel; and therefore understanding the effects of bad marketplace biodiesel fuels on engine and fuel system performance is critical to develop durable automotive technologies. The results presented herein are from vehicle evaluation studies with both on-specification and off-specification bio-based fuels. These studies focused on the performance of fuel injection equipment, engine, engine oil, emissions and emissions system durability.

Exhaust Emission Control: DPF Systems. Presenter Shingo Iwasaki, NGK Insulators, Ltd.

As mass reduction becomes an increasingly important enabler for fuel economy improvement, having a robust structural development process that can comprehend Vehicle Dynamics-specific requirements is correspondingly important. There is a correlation between the stiffness of the body structure and the performance of the vehicle when evaluated for ride and handling. However, an unconstrained approach to body stiffening will result in an overly-massive body structure. In this paper, the authors employ loads generated from simulation of quasi-static and dynamic vehicle events in ADAMS, and exercise structural finite element models to recover displacements and deflected shapes. In doing so, a quantitative basis for considering structural vehicle dynamics requirements can be established early in the design/development process.

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).