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This study uses full drive cycle simulation to compare the fuel consumption of a vehicle with a turbocharged (TC) engine to the same vehicle with an alternative boosting technology, namely, a hybrid supercharger, in which a planetary gear mechanism governs the power split to the supercharger between the crankshaft and a 48 V 5 kW electric motor. Conventional mechanically driven superchargers or electric superchargers have been proposed to improve the dynamic response of boosted engines, but their projected fuel efficiency benefit depends heavily on the engine transient response and driver/cycle aggressiveness. The fuel consumption benefits depend on the closed-loop engine responsiveness, the control tuning, and the torque reserve needed for each technology. To perform drive cycle analyses, a control strategy is designed that minimizes the boost reserve and employs high rates of combustion dilution via exhaust gas recirculation (EGR).

An experimental study is performed for homogeneous charge compression ignition (HCCI) combustion focusing on late phasing conditions with high cyclic variability (CV) approaching misfire. High CV limits the feasible operating range and the objective is to understand and quantify the dominating effects of the CV in order to enable controls for widening the operating range of HCCI. A combustion analysis method is developed for explaining the dynamic coupling in sequences of combustion cycles where important variables are residual gas temperature, combustion efficiency, heat release during re-compression, and unburned fuel mass. The results show that the unburned fuel mass carries over to the re-compression and to the next cycle creating a coupling between cycles, in addition to the well known temperature coupling, that is essential for understanding and predicting the HCCI behavior at lean conditions with high CV.

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 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.

The power management control system development and vehicle test results for a medium-duty hybrid electric truck are reported in this paper. The design procedure adopted is a model-based approach, and is based on the dynamic programming technique. A vehicle model is first developed, and the optimal control actions to maximize fuel economy are then obtained by the dynamic programming method. A near-optimal control strategy is subsequently extracted and implemented using a rapid-prototyping control development system, which provides a convenient environment to adjust the control algorithms and accommodate various I/O configurations. Dynamometer-testing results confirm that the proposed algorithm helps the prototype hybrid truck to achieve a 45% fuel economy improvement on the benchmark (non-hybrid) vehicle. It also compares favorably to a conventional rule-based control method, which only achieves a 31% fuel economy improvement on the same hybrid vehicle.

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.

In this paper, a simulation-based dynamic rollover evaluation procedure is described. This work is based on the worst-case methodology developed at the University of Michigan, and is the result of a collaborated research project between the University of Michigan and TRW Inc. The target vehicle studied in this paper is a large production volume SUV. This vehicle is equipped with a production-intent TRW Vehicle Stability Control (VSC) system. The main goals of this paper are to (i) study the rollover propensity of this SUV, as influenced by vehicle and environment parameters such as vehicle speed, road condition, etc.; and (ii) investigate whether, and by how much, does the VSC system influence the rollover propensity of this SUV. The modeling, evaluation procedure, and preliminary evaluation results are reported.

A hybrid electric vehicle simulation tool (HE-VESIM) has been developed at the Automotive Research Center of the University of Michigan to study the fuel economy potential of hybrid military/civilian trucks. In this paper, the fundamental architecture of the feed-forward parallel hybrid-electric vehicle system is described, together with dynamic equations and basic features of sub-system modules. Two vehicle-level power management control algorithms are assessed, a rule-based algorithm, which mainly explores engine efficiency in an intuitive manner, and a dynamic-programming optimization algorithm. Simulation results over the urban driving cycle demonstrate the potential of the selected hybrid system to significantly improve vehicle fuel economy, the improvement being greater when the dynamic-programming power management algorithm is applied.

This paper investigates the effects of manufacturing variations in fuel injectors on the engine performance with emphasis on emissions. The variations are taken into consideration within a Reliability-Based Design Optimization (RBDO) framework. A reduced version of Multi-Zone Diesel engine Simulation (MZDS), MZDS-lite, is used to enable the optimization study. The numerical noise of MZDS-lite prohibits the use of gradient-based optimization methods. Therefore, surrogate models are developed to filter out the noise and to reduce computational cost. Three multi-objective optimization problems are formulated, solved and compared: deterministic optimization using MZDS-lite, deterministic optimization using surrogate models and RBDO using surrogate models. The obtained results confirm that manufacturing variation effects must be taken into account in the early product development stages.

This paper investigates the opportunities for improving truck fuel economy through the use of a Fuel Cell Auxiliary Power Unit (FC APU) for silent watch, as well as for powering electrified engine accessories during driving. The particular vehicle selected as the platform for this study is a prototype of the Family of Medium Tactical Vehicles (FMTV) capable of carrying a 5 ton payload. Peak stand-by power requirements for on-board power are determined from the projected future digitized battlefield vehicle requirements. Strategic selection of electrified engine accessories enables engine shutdowns when the vehicle is stopped, thus providing additional fuel savings. Proton Exchange Membrane (PEM) fuel cell is integrated with a partial oxidation reformer in order to allow the use of the same fuel (JP8) as for the propulsion diesel engine.

The target cascading methodology is applied to the conceptual design of an advanced heavy tactical truck. Two levels are defined: an integrated truck model is represented at the top (vehicle) level and four independent suspension arms are represented at the lower (system) level. Necessary analysis models are developed, and design problems are formulated and solved iteratively at both levels. Hence, vehicle design variables and system specifications are determined in a consistent manner. Two different target sets and two different propulsion systems are considered. Trade-offs between conflicting targets are identified. It is demonstrated that target cascading can be useful in avoiding costly design iterations late in the product development process.

A program to explore the effects of natural and additive-derived cetane on various aspects of diesel performance and combustion has been carried out. Procedures have been developed to measure diesel engine fuel consumption and power to a high degree of precision. These methods have been used to measure fuel consumption and power in three heavy-duty direct-injection diesel engines. The fuel matrix consisted of three commercial fuels of cetane number (CN) of 40-42, the same fuels raised to CN 48-50 with a cetane improver additive, and three commercial fuels of base CN 47-50. The engines came from three different U.S. manufacturers and were of three different model years and emissions configurations. Both fuel economy and power were found to be significantly higher for the cetane-improved fuels than for the naturally high cetane fuels. These performance advantages derive mainly from the higher volumetric heat content inherent to the cetane-improved fuels.

Experimental results on an automatic lane keeping control study are presented in this paper. A magnetic reference system was used to provide the vehicle lateral tracking error as well as future road curvature information and vehicle speed measurement to the vehicle steering controller. The front wheels of the vehicle are steered according to vehicle lateral displacement, future road curvature, vehicle yaw rate and lateral acceleration, and vehicle speed. The control algorithm used to design the feedback and feedforward controllers is known as the Frequency-Shaped-Linear-Quadratic Preview (FSLQ-preview) optimal control design method. The closed loop response of the vehicle was examined under a wide variety of test conditions, including low tire pressure, measurement noise, perturbed reference system, hard braking, and snowy road.

This paper describes the concept and a practical implementation of piston-compounding. First, a detailed computer simulation of the piston-compounded engine is used to shed light into the thermodynamic events associated with the operation of this engine, and to predict the performance and fuel economy of the entire system. Starting from a baseline design, the simulation is used to investigate changes in system performance as critical parameters are varied. The latter include auxiliary cylinder and interconnecting manifold volumes for a given main cylinder volume, auxiliary cylinder valve timings in relation to main cylinder timings, and degree of heat loss to the coolant. Optimum designs for either highest power density or highest thermal efficiency (54%) are thus recommended. It is concluded that a piston-compounded adiabatic engine concept is a promising future powerplant.

The finite volume, three-dimensional, turbulent flow code ARIS-3D is applied to the study of the complex flow field through the inlet port and within the cylinder of a uniflow-scavenged engine. The multiblock domain decomposition technique is used to accommodate this complex geometry. In this technique, the domain is decomposed into two blocks, one block being the cylinder and the other being the inlet duct. The effects of inlet duct length, geometric port swirl angle, and number of ports on swirl generating capability are explored. Trade-offs between swirl level and inherent pressure drop can thus be identified, and inlet port design can be optimized.

A comprehensive model for sprays emerging from high-pressure swirl injectors in DISI engines has been developed accounting for both primary and secondary atomization. The model considers the transient behavior of the pre-spray and the steady-state behavior of the main spray. The pre-spray modeling is based on an empirical solid cone approach with varying cone angle. The main spray modeling is based on the Liquid Instability Sheet Atomization (LISA) approach, which is extended here to include the effects of swirl. Mie Scattering, LIF, PIV and Laser Droplet Size Analyzer techniques have been used to produce a set of experimental data for model validation. Both qualitative comparisons of the evolution of the spray structure, as well as quantitative comparisons of spray tip penetration and droplet sizes have been made. It is concluded that the model compares favorably with data under atmospheric conditions.

An early-design methodology for predicting both expected fuel economy and catalyst-out CO, HC and NOx concentrations during arbitrarily-defined transient cycles is presented. The methodology is based on utilizing a vehicle-powertrain model with embedded maps of fully warmed up engine-out performance and emissions, and appropriate temperature-dependent correction factors to account for not fully warmed up conditions during transients. Similarly, engine-out emissions are converted to catalyst-out emissions using conversion efficiencies based on the catalyst brick temperature. A crucial element of the methodology is hence the ability to predict heat flows and component temperatures in the engine and the exhaust system during transients, consistent with the data available during concept definition and early design phases.

This paper describes a test cell setup for concurrent running of a real engine and a vehicle system simulation, and its use for evaluating engine performance when integrated with a conventional and a hybrid electric driveline/vehicle. This engine-in-the-loop (EIL) system uses fast instruments and emission analyzers to investigate how critical in-vehicle transients affect engine system response and transient emissions. Main enablers of the work include the highly dynamic AC electric dynamometer with the accompanying computerized control system and the computationally efficient simulation of the driveline/vehicle system. The latter is developed through systematic energy-based proper modeling that tailors the virtual model to capture critical powertrain transients while running in real time. Coupling the real engine with the virtual driveline/vehicle offers a chance to easily modify vehicle parameters, and even study two different powertrain configurations.