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A quasi-dimensional computer simulation of the turbocharged spark-ignition engine has been developed in order to study system performance as various design parameters and operating conditions are varied. The simulation is of the “filling and emptying” type. Quasi-steady flow models of the compressor, intercooler, manifolds, turbine, wastegate, and ducting are coupled with a multi-cylinder engine model where each cylinder undergoes the same thermodynamic cycle. A turbulent entrainment model of the combustion process is used, thus allowing for studies of the effects of various combustion chamber shapes and turbulence parameters on cylinder pressure, temperature, NOx emissions and overall engine performance. Valve open areas are determined either based on user supplied valve lift data or using polydyne-generated cam profiles which allow for variable valve timing studies.

The combustion process in a diesel engine was simulated using KIVA-II, a multi-dimensional computer code. The original combustion model in KIVA-II is based on chemical kinetics, and thus fails to capture the effects of turbulence on combustion. A mixing-controlled, eddy break-up combustion model was implemented into the code. Realistic diesel fuel data were also compiled. Subsequently, the sensitivity of the code to a number of parameters related to fuel injection, mixing, and combustion was studied. Spray injection parameters were found to have a strong influence on the model's predictions. Higher injection velocity and shorter injection duration result in a higher combustion rate and peak pressure and temperature. The droplet size specified at injection significantly affects the rate of spray penetration and evaporation, and thus the combustion rate. Contrary to expectation, the level of turbulence at the beginning of the calculation did not affect fuel burning rate.

Connected and automated vehicles (CAVs) provide the most intriguing opportunity to reduce energy consumption and travel delays. In this paper, we propose a two-level control architecture for CAVs to optimize (1) the vehicle’s speed profile, aimed at minimizing stop-and-go driving, and (2) the powertrain efficiency of the vehicle for the optimal speed profile derived in (1). The proposed hierarchical control framework can be implemented onboard the vehicle in real time with minimal computational effort. We evaluate the effectiveness of the efficiency of the proposed architecture through simulation in Mcity using a 100% penetration rate of CAVs. The results show that the proposed approach yields significant benefits in terms of energy efficiency.

The implementation of connected and automated vehicle (CAV) technologies enables a novel computational framework for real-time control aimed at optimizing energy consumption with associated benefits. In this paper, we implement an optimal control framework, developed previously, in an Audi A3 etron plug-in hybrid electric vehicle, and demonstrate that we can improve the vehicle’s efficiency and travel time in a corridor including an on-ramp merging, a speed reduction zone, and a roundabout. Our exposition includes the development, integration, implementation and validation of the proposed framework in (1) simulation, (2) hardware-in-the-loop (HIL) testing, (3) connectivity enabled virtual reality based bench-test, and (4) field test in Mcity. We show that by adopting such inexpensive, yet effective process, we can efficiently integrate and test the control framework, establish proper connectivity and data transmission between different modules of the system, and reduce uncertainty.

Direct injection of natural gas under high pressure conditions has emerged as a promising option for improving engine fuel economy and emissions. However, since the gaseous injection technology is new, limited experience exists as to the optimum configuration of the injection system and associated combustion chamber design. The present study uses KIVA-3 based, multidimensional modeling to improve the understanding and assist the optimization of the gaseous injection process. Compared to standard k-ε models, a Renormalization Group Theory (RNG) based k-ε model [1] has been found to be in better agreement with experiments in predicting gaseous penetration histories for both free and confined jet configurations. Hence, this validated RNG model is adopted here to perform computations in realistic engine geometries.

A detailed chemical kinetic mechanism, consisting of 22 species and 104 elementary reactions, has been used in conjunction with the multi-dimensional reactive flow code KIVA-3 to study autoignition of natural gas injected under compression ignition conditions. Calculations for three different blends of natural gas are performed on a three-dimensional computational grid by modeling both the injection and ignition processes. Ignition delay predictions at pressures and temperatures typical of top-dead-center conditions in compression ignition engines compare well with the measurements of Naber et al. [1] in a combustion bomb. Two different criteria, based on pressure rise and mass of fuel burned, are used to detect the onset of ignition. Parametric studies are conducted to show the effect of additives like ethane and hydrogen peroxide in increasing the fuel consumption rate.

A naturally-aspirated, Miller cycle, Spark-Ignition (SI) engine that controls output with variable intake valve closure is compared to a conventionally-throttled engine using computer simulation. Based on First and Second Law analyses, the two load control strategies are compared in detail through one thermodynamic cycle at light load conditions and over a wide range of loads at 2000 rpm. The Miller Cycle engine can use late intake valve closure (LIVC) to control indicated output down to 35% of the maximum, but requires supplemental throttling at lighter loads. The First Law analysis shows that the Miller cycle increases indicated thermal efficiency at light loads by as much as 6.3%, primarily due to reductions in pumping and compression work while heat transfer losses are comparable.

A comprehensive methodology for predicting the transient thermal response of spark-ignition engines subject to time-varying boundary conditions is presented. The approach is based on coupling a cycle-resolved quasi-dimensional simulation of in-cylinder thermodynamic events with a resistor-capacitor (R-C) thermal network of the various component and fluid interactions throughout the engine and exhaust system. The dynamic time step of the thermal solution is limited by either the frequency of the prescribed time-dependent boundary conditions or by the minimum thermal time constant of the R-C network. To demonstrate the need for fully-coupled, transient thermodynamic and heat transfer solutions, model behavior is first explored for step-change and staircase variations of engine operating conditions.

A personal computer-based vehicle powertrain simulation (VPS) is developed to predict fuel economy and performance. This paper summarizes the governing equations used in the model. Then the different simulation techniques are described with emphasis on the more complicated time-dependent simulation. The simulation is validated against constant speed and variable cycle test track data obtained for a 5 ton army truck. Then the simulation is used to compare the performance of the 5 ton truck when powered by a cooled and natually aspirated engine, a cooled and turbocharged engine, and an uncooled and turbocharged engine. Studies of the effect of payload, tire efficiency, and drag coefficient on vehicle performance are also conducted, as well as a performance comparison between manual and automatic transmissions. It is concluded that the VPS code can provide good predictions of vehicle fuel economy, and thus is a useful tool in designing and evaluating vehicle powertrains.

Meeting diesel engine emission standards for heavy-duty vehicles can be achieved by simultaneous injection of fuel and water. An injection system for instantaneous mixing of fuel and water in the combustion chamber has been developed by injecting water in a mixing passage located in the periphery of the fuel spray. The fuel spray is then entrained by water and hot air before it burns. The experimental work was carried out on a Rapid Compression Machine and on a Komatsu direct-injection heavy-duty diesel engine with a high pressure common rail fuel injection system. It was also supported by Computational Fluid Dynamics simulations of the injection and combustion processes in order to evaluate the effect of water vapor distribution on cylinder temperature and NOX formation. It has been concluded that when the water injection is appropriately timed, the combustion speed is slower and the cylinder temperature lower than in conventional diesel combustion.

The thermal conditions of an engine structure, in particular the wall temperatures, have been shown to have a great effect on the HCCI engine combustion timing and burn rates through wall heat transfer, especially during transient operations. This study addresses the effects of thermal inertia on combustion in an HCCI engine. In this study, the control of combustion timing in an HCCI engine is achieved by modulating the residual gas fraction (RGF) while considering the wall temperatures. A multi-cylinder engine simulation with detailed geometry is carried out using a 1-D system model (GT-Power®) that is linked with Simulink®. The model includes a finite element wall temperature solver and is enhanced with original HCCI combustion and heat transfer models. Initially, the required residual gas fraction for optimal BSFC is determined for steady-state operation. The model is then used to derive a map of the sensitivity of optimal residual gas fraction to wall temperature excursions.

In-cylinder heat transfer has strong effects on engine performance and emissions and heat transfer modeling is closely related to the physics of the thermal boundary layer, especially the effects of conductivity and Prandtl number inside the thermal boundary layer. Compressibility effects on the thermal boundary layer are important issues in multi-dimensional in-cylinder heat transfer modeling. Nevertheless, the compressibility effects on kinematic viscosity and the variation of turbulent Prandtl number and eddy viscosity ratio have not been thoroughly investigated. In this study, an in-cylinder heat transfer model is developed by introducing compressibility effects on turbulent Prandtl number, eddy viscosity ratio and kinematic viscosity variation with a power-law approximation. This new heat transfer model is implemented to a spark-ignition engine with a coherent flamelet turbulent combustion model and the RNG k- turbulence model.

A numerical study has been conducted to investigate possible extension of the low load limit of the HCCI operating range by charge stratification using direct injection. A wide range of SOI timings at a low load HCCI engine operating condition were numerically examined to investigate the effect of DI. A multidimensional CFD code KIVA3v with a turbulent combustion model based on a modified flamelet approach was used for the numerical study. The CFD code was validated against experimental data by comparing pressure traces at different SOI’s. A parametric study on the effect of SOI on combustion has been carried out using the validated code. Two parameters, the combustion efficiency and CO emissions, were chosen to examine the effect of SOI on combustion, which showed good agreement between numerical results and experiments. Analysis of the in-cylinder flow field was carried out to identify the source of CO emissions at various SOI’s.

The number of control actuators available on spark-ignition engines is rapidly increasing to meet demand for improved fuel economy and reduced exhaust emissions. The added complexity greatly complicates control strategy development because there can be a wide range of potential actuator settings at each engine operating condition, and map-based actuator calibration becomes challenging as the number of control degrees of freedom expand significantly. Many engine actuators, such as variable valve actuation and flow control valves, directly influence in-cylinder combustion through changes in gas exchange, mixture preparation, and charge motion. The addition of these types of actuators makes it difficult to predict the influences of individual actuator positioning on in-cylinder combustion without substantial experimental complexity.

This paper reports the development of a model of diesel combustion and NO emissions, based on a modified eddy dissipation concept (EDC), and its implementation into the KIVA-3V multidimensional simulation. The EDC model allows for more realistic representation of the thin sub-grid scale reaction zone as well as the small-scale molecular mixing processes. Realistic chemical kinetic mechanisms for n-heptane combustion and NOx formation processes are fully incorporated. A model based on the normalized fuel mass fraction is implemented to transition between ignition and combustion. The modeling approach has been validated by comparison with experimental data for a range of operating conditions. Predicted cylinder pressure and heat release rates agree well with measurements. The predictions for NO concentration show a consistent trend with experiments. Overall, the results demonstrate the improved capability of the model for predictions of the combustion process.

Adjusting the Residual Gas Fraction (RGF) by means of Variable Valve Actuation (VVA) is a strong candidate for controlling the ignition timing in Homogeneous Charge Compression Ignition (HCCI) engines. However, at high levels of residual gas fraction, insufficient mixing can lead to the presence of considerable temperature and composition variations. This paper extends previous modeling efforts to include the effect of RGF distribution on the onset of ignition and the rate of combustion using a multi-dimensional fluid mechanics code (KIVA-3V) sequentially with a multi-zone code with detailed chemical kinetics. KIVA-3V is used to simulate the gas exchange processes, while the multi-zone code computes the combustion event. It is shown that under certain conditions the effect of composition stratification is significant and cannot be captured by a single-zone model or a multi-zone model using only temperature zones.

Variable geometry turbines (VGT) are of particular interest to advanced diesel powertrains for future conventional trucks, since they can dramatically improve system transient response to sudden changes in speed and load, characteristic of automotive applications. VGT systems are also viewed as the key enabler for the application of the EGR system for reduction of heavy-duty diesel emissions. This paper applies an artificial neural network methodology to VGT modeling in order to enable representation of the VGT characteristics for any blade (nozzle) position. Following validation of the ANN model of the baseline, fixed geometry turbine, the VGT model is integrated with the diesel engine system. The latter is linked to the driveline and the vehicle dynamics module to form a complete, high-fidelity vehicle simulation.

The need for a rigorous systems engineering approach to automotive powertrains has been addressed in this work from the perspective of the diesel engine. A high-fidelity engine simulation has been integrated with a total vehicle model for the purpose of reverse engineering the optimal powerplant for a given vehicle mission. Engine parameters have been coordinated between the simulations to develop a framework for total vehicle design. The design strategies discussed in this paper allow engine researchers to set targets for individual system components and to analyze the tradeoffs associated with different vehicle mission objectives. A detailed case study employing these techniques is presented for a conventional vehicle where the most fuel-efficient engine is found that simultaneously conforms to the desired performance criteria.

A quasi-dimensional, multi-zone, direct injection (DI) diesel combustion model has been developed and implemented in a full cycle simulation of a turbocharged engine. The combustion model accounts for transient fuel spray evolution, fuel-air mixing, ignition, combustion and NO and soot pollutant formation. In the model, the fuel spray is divided into a number of zones, which are treated as open systems. While mass and energy equations are solved for each zone, a simplified momentum conservation equation is used to calculate the amount of air entrained into each zone. Details of the DI spray, combustion model and its implementation into the cycle simulation of Assanis and Heywood [1] are described in this paper. The model is validated with experimental data obtained in a constant volume chamber and engines. First, predictions of spray penetration and spray angle are validated against measurements in a pressurized constant volume chamber.

The Homogeneous Charge Compression Ignition (HCCI) combustion concept is currently under widespread investigation due to its potential to increase thermal efficiency while greatly decreasing harmful exhaust pollutants. Simulation tools have been developed to explore the implications of initial mixture thermodynamic state on engine performance and emissions. In most cases these modeling efforts have coupled a detailed fuel chemistry mechanism with empirical descriptions of the in-cylinder heat transfer processes. The primary objective of this paper is to present a fundamentally based boundary layer heat transfer model. The two-zone combustion model couples an adiabatic core zone with a boundary layer heat transfer model. The model predicts film coefficient, with approximately the same universal shape and magnitudes as an existing global model.