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This paper investigates the effect of the cetane number (CN) of a diesel fuel on the energy balance between a light duty (1.9L) and medium duty (4.5L) diesel engine. The two engines have a similar stroke to bore (S/B) ratio, and all other control parameters including: geometric compression ratio, cylinder number, stroke, and combustion chamber, have been kept the same, meaning that only the displacement changes between the engine platforms. Two Coordinating Research Council (CRC) diesel fuels for advanced combustion engines (FACE) were studied. The two fuels were selected to have a similar distillation profile and aromatic content, but varying CN. The effects on the energy balance of the engines were considered at two operating conditions; a “low load” condition of 1500 rev/min (RPM) and nominally 1.88 bar brake mean effective pressure (BMEP), and a “medium load” condition of 1500 RPM and 5.65 BMEP.

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.

Stringent fuel economy and emissions regulations have driven development of new mixture preparation technologies and increased spark-ignition engine complexity. Additional degrees of freedom, brought about by devices such as cam phasers and charge motion control valves, enable greater range and flexibility in engine control. This permits significant gains in fuel efficiency and emission control, but creates challenges related to proper engine control and calibration techniques. Accurate experimental characterization of high degree of freedom engines is essential for addressing the controls challenge. In particular, this paper focuses on the evaluation of three experimental residual gas fraction measurement techniques for use in a spark ignition engine equipped with dual-independent variable camshaft phasing (VVT).

Homogenous Charge Compression Ignition (HCCI) engines offer a good potential for achieving high fuel efficiency while virtually eliminating NOx and soot emissions from the exhaust. However, realizing the full fuel economy potential at the vehicle level depends on the size of the HCCI operating range. The usable HCCI range is determined by the knock limit on the upper end and the misfire limit at the lower end. Previously proven high sensitivity of the HCCI process to thermal conditions leads to a hypothesis that combustion chamber deposits (CCD) could directly affect HCCI combustion, and that insight about this effect can be helpful in expanding the low-load limit. A combustion chamber conditioning process was carried out in a single-cylinder gasoline-fueled engine with exhaust re-breathing to study CCD formation rates and their effect on combustion. Burn rates accelerated significantly over the forty hours of running under typical HCCI operating conditions.

In the wake of global focus shifting towards the health and conservation of the planet, greater importance is placed upon the hazardous emissions of our fossil fuels, as well as their finite supply. These two areas remain intense topics of research in order to reduce greenhouse gas emissions and increase the fuel efficiency of vehicles, a sector which is a major contributor to society's global CO₂ emissions and consumer of fossil-fuel resources. A particular solution to this problem is the diesel engine, with its inherently fuel-lean combustion, which gives rise to low CO₂ production and higher efficiencies than other potential powertrain solutions. Diesel engines, however, typically exhibit higher nitrogen oxides (NOx) and soot engine-out emissions than their gasoline counterparts. NOx is an ingredient to ground-level ozone production and smoke is a possible carcinogen, both of which are facing stricter emissions regulations.

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.

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.

Medium trucks constitute a large market segment of the commercial transportation sector, and are also used widely for military tactical operations. Recent technological advances in hybrid powertrains and fuel cell auxiliary power units have enabled design alternatives that can improve fuel economy and reduce emissions dramatically. However, deterministic design optimization of these configurations may yield designs that are optimal with respect to performance but raise concerns regarding the reliability of achieving that performance over lifetime. In this article we identify and quantify uncertainties due to modeling approximations or incomplete information. We then model their propagation using Monte Carlo simulation and perform sensitivity analysis to isolate statistically significant uncertainties. Finally, we formulate and solve a series of reliability-based optimization problems and quantify tradeoffs between optimality and reliability.

A regenerative braking model for a parallel Hybrid Electric Vehicle (HEV) is developed in this work. This model computes the line and pad pressures for the front and rear brakes, the amount of generator use depending on the state of deceleration (i.e. the brake pedal position), and includes a wheel lock-up avoidance algorithm. The regenerative braking model has been developed in the symbolic programming environment of MATLAB/SIMULINK/STATEFLOW for downloadability to an actual HEV's control system. The regenerative braking model has been incorporated in NREL's HEV system simulation called ADVISOR. Code modules that have been changed to implement the new regenerative model are described. Resulting outputs are compared to the baseline regenerative braking model in the parent code. The behavior of the HEV system (battery state of charge, overall fuel economy, and emissions characteristics) with the baseline and the proposed regenerative braking strategy are first compared.

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.

Modern diesel engines manufactured for commercial vehicles are calibrated to meet EPA emissions regulations. Many of the technologies and strategies typically incorporated to meet emissions targets compromise engine performance and efficiency. When used in military applications, however, engine performance and efficiency are of utmost importance in combat conditions or in remote locations where fuel supplies are scarce. This motivates the study of the potential to utilize the flexibility of emissions-reduction technologies toward optimizing engine performance while still keeping the emissions within tolerable limits. The study was conducted on a modern medium-duty International V-8 diesel engine with variable geometry turbocharger (VGT) and exhaust gas recirculation (EGR). The performance-emissions tradeoffs were explored using design of experiments and response surface methodology.

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 effects of lubricating oil on friction and engine-out emissions in a light-duty 2.2L compression ignition direct injection (CIDI) engine were investigated. A matrix of test oils varying in viscosity (SAE 5W-20 to 10W-40), friction modifier (FM) level and chemistry (MoDTC and organic FM), and basestock chemistry (mineral and synthetic) was investigated. Tests were run in an engine dynamometer according to a simulated, steady state FTP-75 procedure. Low viscosity oils and high levels of organic FM showed benefits in terms of fuel economy, but there were no significant effects observed with the oils with low MoDTC concentration on engine friction run in this program. No significant oil effects were observed on the gaseous emissions of the engine. PM emissions were analyzed for organic solubles and insolubles. The organic soluble fraction was further analyzed for the oil and fuel soluble portions.

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.

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.

The homogeneous charge, compression-ignition (HCCI) combustion process has the potential to significantly reduce NOx and particulate emissions, while achieving high thermal efficiency and the capability of operating with a wide variety of fuels. This makes the HCCI engine an attractive technology that can ostensibly provide diesel-like fuel efficiency and very low emissions, which may allow emissions compliance to occur without relying on lean aftertreatment systems.

Conventional spark plugs ignite a fuel-air mixture via an electric-to-plasma energy transfer; the effectiveness of which can be described by an electric-to-plasma energy efficiency. Although conventional spark plug electric-to-plasma efficiencies have historically been viewed as adequate, it might be wondered how an increase in such an efficiency might translate (if at all) to improvements in the flame initiation period and eventual engine performance of a spark-ignition engine. A modification can be made to the spark plug that places a peaking capacitor in the path of the electrical current; upon coil energizing, the stored energy in the peaking capacitor substantially increases the energy delivered by the spark. A previous study has observed an improvement in the electric-to-plasma energy efficiency to around 50%, whereas the same study observed conventional spark plug electric-to-plasma energy efficiency to remain around 1%.

Advanced engine combustion strategies, such as HCCI and SACI, allow engines to achieve high levels of thermal efficiency with low levels of engine-out NOx emissions. To maximize gains in fuel efficiency, HCCI combustion is often run at lean operating conditions. However, lean engine operation prevents the conventional TWC after-treatment system from reaching legislated tailpipe emissions due to oxygen saturation. One potential solution for handling this challenge without the addition of costly NOx traps or on-board systems for urea injection is the passive TWC-SCR concept. This concept includes the integration of an SCR catalyst downstream of a TWC and the use of periods of rich or stoichiometric operation to generate NH3 over the TWC to be stored on the SCR catalyst until it is needed for NOx reduction during subsequent lean operation.

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.

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.