Search Results

One promising solution for increasing vehicle fuel economy, while still maintaining long-range driving capability, is the plug-in hybrid electric vehicle (PHEV). A PHEV is a hybrid electric vehicle (HEV) whose rechargeable energy source can be recharged from an external power source, making it a combination of an electric vehicle and a traditional hybrid vehicle. A PHEV is capable of operating as an electric vehicle until the battery is almost depleted, at which point the on-board internal combustion engine turns on, and generates power to meet the vehicle demands. When the vehicle is not in use, the battery can be recharged from an external energy source, once again allowing electric driving. A series of models is presented which simulate various powertrain architectures of PHEVs. To objectively evaluate the effect of powertrain architecture on fuel economy, the models were run according to the latest test procedures and all fuel economy values were utility factor weighted.

In order to meet the increasingly stringent emissions standard it is imperative that a two pronged approach is pursued for reduction of tailpipe emissions. In this regard emissions, and often the exhaust compositions, are needed to be controlled both at its source and then subsequently cleaned up at the exhaust system. In addition, an aftertreatment system often consists of an array of catalysts and its performance depends on the transient characteristics of the exhaust gas composition. To complicate the matter furthermore, relevant technologies are still evolving at a rapid pace. Consequently, an aftertreatment modeling approach should not only be system based but also offer a high level of configurability. Thus a system level approach that includes a model of an engine and vehicle may provide an efficient means to analyze system performance and examine relative effects of competing phenomena and technologies.

In order to reduce the cost of exhaust aftertreatment development, OEMs are increasingly relying on simulation of catalysts, traps and associated control systems. In this regards, for example, considerable progresses have been made on modeling diesel particulate filters. The work described in this paper was sought to provide a valid diesel particulate filter (DPF) model for coupling with engine/vehicle models under the same toolbox. A comprehensive two-level modeling approach, including a lumped parameter model and a detailed 1-D 3-layer-kinetics model, has been proposed for modeling wall-flow diesel particulate filters. Both are capable of modeling virtually all aspects of filter performance in terms of deep-bed filtration, particulate matter loading and filter regeneration.

There exists a strong interaction between the engine cylinder, intake and exhaust gas flow dynamics and the dynamics of mechanical and hydraulic components constituting the valvetrain system, which controls the engine gas flow. Technologies such as turbo-charging and Diesel particulate filtration (DPF) can significantly increase port gas pressure forces acting on the exhaust valve. When such systems are introduced or undergo design modifications, the operation of valvetrain system can be greatly affected and even compromised, which in turn may lead to degradation of performance of the internal combustion engine. Often, the valvetrain system needs to be retuned. Further, predictive analysis of design issues or evaluation of design changes requires highly coupled simulations, combining models of gas pressure forces and the dynamics of all mechanical and hydro-mechanical parts constituting the valvetrain.

An advanced simulation code has been developed that models the fluid, mechanical, and thermal aspects of fuel injection and various thermal-hydraulic systems. The flow model is based on the solution of one-dimensional, unsteady, fully compressible, Navier-Stokes and energy equations. The code solves the governing equations using a finite volume formulation. In addition, the code employs a newly developed equation of state that exhibits the observed behavior of measurable fluid properties such as wave propagation speed. Furthermore, the code allows for multi-component, multi-phase treatment and takes into account pipe wall flexibility based on a quasi-dynamic thick-shell model. Multi-body dynamics are solved using an adaptive step-size Runge-Kutta based solver, and the structural thermal solution is based on a fast-executing finite element solver. The code, GT-Fuel, has been validated using experimental measurements from both high and low-pressure fuel injection systems.

An integrated simulation tool has been developed, which is applicable to a wide range of design issues. A key feature introduced for the first time by this new tool is that it is truly a single code, with identical handling of engine, powertrain, vehicle, hydraulics, electrical, thermal and control elements. Further, it contains multiple levels of engine models, so that the user can select the appropriate level for the time scale of the problem (e.g. real-time operation). One possible example of such a combined simulation is the present study of engine block vibration in the mounts. The simulation involved a fully coupled model of performance, thermodynamics and combustion, with the dynamics of the cranktrain, engine block and the driveline. It demonstrated the effect of combustion irregularity on engine shaking in the mounts.

The V-Cycle is a well accepted and commonly implemented process model for systems engineering. The concept phase is represented by the upper-left portion of the V, in which very high level system simulations are the predominant modeling activity. Traveling down the V toward the vertex, sub-system level and component level simulations are employed as one enters the development phase. Finally, the test and validation phase is completed, and is represented by the right side of the V. Simulation tools have historically been used throughout some phases of the V-cycle, and with the ever increasing computing power, and the increasingly accurate and predictive simulation tools available to the engineer, today it is common that simulation is used in every phase of the cycle, from concept straight through the test and validation phases.

A great part of the projects in the powertrain area is focused on the development of more efficient thermal applications. In the end, efficiency is pursued, since the aim is to achieve a sustainable design with low fuel consumption. Thus, vehicles which present lower fuel consumption are demanded by customers. Additionally the emission standards have been reducing the limits of CO₂ emissions to very low levels, which drive engineers to develop vehicles with lower fuel consumption. In summary, the product should now please a more demanding worldwide customer profile as the global economy grows. Vehicle design processes should consider fuel consumption sensitivity taking into account the combined engine and drive train systems at early stages. Frequently the actual fuel consumption can only be confirmed when the first prototype is assembled in order to validate the adopted solutions.

Changing and more stringent emissions norms and fuel economy requirements often call for modifications in the fuel injection system of a Diesel engine. There exists a strong interaction between the injection system hydraulics and the dynamics of mechanical components within the unit injector and the camshaft-driven mechanical system used to pressurize it. Hence, accurate predictive analysis of design issues or evaluation of design changes requires highly coupled and integrated hydro-mechanical simulations, combining analysis of fuel injection hydraulics and the dynamics of all mechanical parts, including the cam-drive system. This paper presents an application of such an integrated model to the study and alleviation of an observed increase in mechanical vibration and related noise levels associated with a proposed design change in unit injectors and valve-train of a 6-cylinder truck diesel engine.

A new model of spur gear contact and gear dynamics was developed for use in studies of dynamic response of mechanical systems involving geartrains. The model is general; in this paper it is applied to geartrain dynamics in valvetrain gear drives. The model dynamically uses a gear contact formulation based on exact involute geometries of gear teeth and can therefore account for varying, non-linear mesh stiffness. It can also account for gear torsional stiffness as well as shaft stiffness at gear centers. The paper further proposes an alternative to dynamic calculation of instantaneous gear tooth contact conditions. The proposed method uses a varying effective mesh stiffness pre-computed through static calculation of contact conditions between teeth of a gear pair, for one mesh, or tooth engagement-disengagement, period. The technique is shown to significantly reduce computational time, while closely matching the predictions of the full model.

A model of roller chain and sprocket dynamics was developed, aimed at analyses of dynamic effects of chain drive systems in automotive valvetrains. Each chain link is modeled as a rigid body with planar motion, with three degrees of freedom and connected to adjacent links by means of a springs and dampers. The kinematics of roller-sprocket contacts are modeled in full detail. Sprocket motions in the chain's plane, resulting from torsional and bending motions of attached camshafts are also taken into account. One or two-sided guides can be treated as well as stationary, sliding or pivoting tensioners operated mechanically or hydraulically. The model also takes into account the contact kinematics between chain link rollers and guides or tensioners, allowing for guides/tensioners of arbitrary shape, or simpler (flat and circular) geometries. The model is first applied to study the chain drive and valvetrain of a 1-cylinder motorcycle engine.

Coupled system modeling is increasingly advantageous as the consideration for vehicle system interactions intensifies. Significant interactions can occur between an engine and cooling system. Vehicle cooling systems can be coupled to the vehicle powertrain in many locations, including the cylinder structure, oil cooler, mechanical coolant pump, mechanical fan, EGR cooler, and charge-air-cooler. To enable the analysis of coupled systems, a linking capability was added to a cooling system simulation tool, GT-COOL, to tie it into an engine simulation tool. The paper describes the linkage methodology and its application. This coupled simulation was applied to the study of a new concept, where the engine exhaust back pressure (and thus engine load) was artificially increased, in order to speed up the engine warm-up. The simulation was used to predict the effect of this concept on the rate of warm-up of the coolant and of the cylinder structure.

A structured, semi-automatic method for reducing a high-fidelity engine model to a fast running one has been developed. The principle of this method rests on the fact that, under certain assumptions, the computationally expensive components of the simulation can be substituted with simpler ones. Thus, the computation speed increases substantially while the physical representation of the engine is retained to a large extent. The resulting model is not only suitable for fast running simulations, but also usable and updatable in later stages of the development process. The thrust of the method is that the calibration of the fast running components is achieved by use of automatically selected neural networks. Two illustrative examples demonstrate the methodology. The results show that the methodology achieves substantial increase in computation speed and satisfactory accuracy.