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Increasing functionality of electronic control units has enhanced our ability to control engine operation utilizing calibration static maps that provide the values of several controllable variables. State-of-the-art simulation-based calibration methods permit the development of these maps with respect to extensive steady-state and limited transient operation of particular driving cycles. However, each individual driving style is different and rarely meets those test conditions. An alternative approach was recently implemented that considers the derivation of these maps while the engine is running the vehicle. In this approach, a self-learning controller selects in real time the optimum values of the controllable variables for the sequences of engine operating point transitions, corresponding to the driver's driving style.

The development and use of a simulation of an Integrated Starter Alternator (ISA) for a High Mobility Multi-purpose Wheeled Vehicle (HMMWV) is presented here. While the primary purpose of an ISA is to provide electric power for additional accessories, it can also be utilized for mild hybridization of the powertrain. In order to explore ISA's potential for improving HMMWV's fuel economy, an ISA model capable of both producing and absorbing mechanical power has been developed in Simulink. Based on the driver's power request and the State of Charge of the battery (SOC), the power management algorithm determines whether the ISA should contribute power to, or absorb power from the crankshaft. The system is also capable of capturing some of the braking energy and using it to charge the battery. The ISA model and the power management algorithm have been integrated in the Vehicle-Engine SIMulation (VESIM), a SIMULINK-based vehicle model previously developed at the University of Michigan.

This work studies the complex interactions resulting from the application and control of Exhaust Gas Recirculation (EGR) on a production heavy-duty diesel engine system, and its effectiveness in reducing NOx emissions. The coupling between EGR, the Variable Geometry Turbocharger (VGT) and the EGR cooler critically affects boost pressure, air/fuel ratio (A/F), combustion efficiency and pumping work. It is shown that EGR provides an effective means for reducing flame temperatures and NOx emissions, particularly under low A/F ratio conditions. However, engine thermal efficiency tends to decrease with EGR as a result of decreasing indicated work and increasing pumping work. Combustion deterioration is predominant at higher load, low speed and low boost conditions, due to a significant decrease of A/F ratio with increasing EGR.

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.