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Fuel wall impingement commonly occurs in small-bore diesel engines. Particularly during engine starting, when wall temperatures are low, the evaporation rate of fuel film remaining from previous cycles plays a significant role in the autoignition process that is not fully understood. Pre-injection chemiluminescence (PIC), resulting from low-temperature oxidation of evaporating fuel film and residual gases, was measured over 3200 μsec intervals at the end of the compression strokes, but prior to fuel injection during a series of starting sequences in an optical diesel engine. These experiments were conducted to determine the effect of this parameter on combustion phasing and were conducted at initial engine temperatures of 30, 40, 50 and 60°C, at swirl ratios of 2.0 and 4.5 at 1000 RPM. PIC was determined to increase and be highly correlated with combustion phasing during initial cycles of the starting sequence.

This paper proposes a framework to perform design optimization of a series PHEV and investigates the impact of using real-world driving inputs on final design. Real-World driving is characterized from a database of naturalistic driving generated in Field Operational Tests. The procedure utilizes Markov chains to generate synthetic drive cycles representative of real-world driving. Subsequently, PHEV optimization is performed in two steps. First the optimal battery and motor sizes to most efficiently achieve a desired All Electric Range (AER) are determined. A synthetic cycle representative of driving over a given range is used for function evaluations. Then, the optimal engine size is obtained by considering fuel economy in the charge sustaining (CS) mode. The higher power/energy demands of real-world cycles lead to PHEV designs with substantially larger batteries and engines than those developed using repetitions of the federal urban cycle (UDDS).

This paper investigates the impact of battery cooling ancillary losses on fuel economy, and optimal control strategy for a series hybrid electric truck with consideration of cooling losses. Battery thermal model and its refrigeration-based cooling system are integrated into vehicle model, and the parasitic power consumption from cooling auxiliaries is considered in power management problem. Two supervisory control strategies are compared. First, a rule-based control strategy is coupled with a thermal management strategy; it controls power system and cooling system separately. The second is optimal control strategy developed using Dynamic Programming; it optimizes power flow with consideration of both propulsion and cooling requirement. The result shows that battery cooling consumption could cause fuel economy loss as high as 5%.

Many approaches have been taken to determine the burning velocity in internal combustion engines. Experimentally, the burning velocity has been determined in optically accessible gasoline engines by tracking the propagation of the flame front from the spark plug to the end of the combustion chamber. These experiments are costly as they require special imaging techniques and major modifications in the engine structure. Another approach to determine the burning velocity is from 3D CFD simulation models. These models require basic information about the mechanisms of combustion which are not available for distillate fuels in addition to many assumptions that have to be made to determine the burning velocity. Such models take long periods of computational time for execution and have to be calibrated and validated through experimentation.

This paper presents a new way to evaluate vehicle speed profile aggressiveness, quantify it from the perspective of the rapid speed fluctuations, and assess its impact on vehicle fuel economy. The speed fluctuation can be divided into two portions: the large-scale low frequency speed trace which follows the ongoing traffic and road characteristics, and the small-scale rapid speed fluctuations normally related to the driver's experience, style and ability to anticipate future events. The latter represent to some extent the driver aggressiveness and it is well known to affect the vehicle energy consumption and component duty cycles. Therefore, the rapid speed fluctuations are the focus of this paper. Driving data collected with the GPS devices are widely adopted for study of real-world fuel economy, or the impact on electrified vehicle range and component duty cycles.

Electrification and hybridization show great potential for improving fuel economy and reducing emission in heavy-duty vehicles. However, high battery cost is unavoidable due to the requirement for large batteries capable of providing high electric power for propulsion. The battery size and cost can be reduced with advanced battery control strategies ensuring safe and robust operation covering infrequent extreme conditions. In this paper, the impact of such a battery control strategy on battery sizing and fuel economy is investigated under various military and heavy-duty driving cycles. The control strategy uses estimated Li-ion concentration information in the electrodes to prevent battery over-charging and over-discharging under aggressive driving conditions. Excessive battery operation is moderated by adjusting allowable battery power limits through the feedback of electrode-averaged Li-ion concentration estimated by an extended Kalman filter (EKF).

As a result of recent focus on the control of Low Temperature Combustion (LTC) modes, dual-fuel combustion strategies such as Reactivity Controlled Compression Ignition (RCCI) have been developed. Reactivity stratification of the auto-igniting mixture is thought to be responsible for the increase in allowable engine load compared to other LTC combustion modes such as Homogenous Charge Compression Ignition (HCCI). The current study investigates the effect of ethanol intake fuel injection on in-cylinder formaldehyde formation and stratification within an optically accessible engine operated with n-heptane direct injection using optical measurements and zero-dimensional chemical kinetic models. Images obtained by Planar Laser Induced Fluorescence (PLIF) of formaldehyde using the third harmonic of a pulsed Nd:YAG laser indicate an increase in formaldehyde heterogeneity as measured by the fluorescence signal standard deviation.

Electrification and hybridization have great potential for improving fuel economy and reducing visual signature or soot emissions in military vehicles. Specific challenges related to military applications include severe duty cycles, large and uncertain energy flows through the system and high thermal loads. A novel supervisory control strategy is proposed to simultaneously mitigate severe engine transients and to reduce high electric current in the battery without oversizing the battery. The described objectives are accomplished by splitting the propulsion power demand through filtering in the frequency domain. The engine covers only low frequency power demand profile while the battery covers high frequency components. In the proposed strategy, the separation filter is systematically designed to identify different frequency components with the consideration of fuel consumption, aggressive engine transients, and battery electric loads.

This paper presents a low-cost path for extending the range of small urban pure electric vehicles by hydraulic hybridization. Energy management strategies are investigated to improve the electric range, component efficiencies, as well as battery usable capacity. As a starting point, a rule-based control strategy is derived by analysis of synergistic effects of lead-acid batteries, high efficient operating region of DC motor and the hydraulic pump/motor. Then, Dynamic Programming (DP) is used as a benchmark to find the optimal control trajectories for DC motor and Hydraulic Pump/Motor. Implementable rules are derived by studying the optimal control trajectories from DP. With new improved rules implemented, simulation results show electric range improvement due to increased battery usable capacity and higher average DC motor operating efficiency.

Combustion in a diesel engine during cold starting under normal and border-line conditions was investigated. Experiments were conducted on a single cylinder, air-cooled, 4-stroke-cycle engine in a cold room. Tests covered different fuels, injection timings and ambient temperatures. Motoring tests, without fuel injection indicated that the compression pressure and temperature are dependent on the ambient temperature and cranking speeds. The tests with JP-5, with a static injection timing of 23° BTDC indicated that the engine may operate on the regular 4-stroke-cycle at normal operating ambient temperatures or may skip one cycle before each firing at moderately low temperatures, i.e. operate on an 8-stroke-cycle mode. At lower temperatures the engine may skip two cycles before each firing cycle, i.e. operate on a 12-stroke-cycle mode. These modes were reproducible and were found to depend mainly on the ambient temperature.

This paper presents an experimental investigation conducted to determine the parameters that control the behavior of autoignition in a small-bore, single-cylinder, optically-accessible diesel engine. Depending on operating conditions, three types of autoignition are observed: a single ignition, a two-stage process where a low temperature heat release (LTHR) or cool flame precedes the main premixed combustion, and a two-stage process where the LTHR or cool flame is separated from the main heat release by an apparent negative temperature coefficient (NTC) region. Experiments were conducted using commercial grade low-sulfur diesel fuel with a common-rail injection system. An intensified CCD camera was used for ultraviolet imaging and spectroscopy of chemiluminescent autoignition reactions under various operating conditions including fuel injection pressures, engine temperatures and equivalence ratios.

Ultraviolet chemiluminescence has been observed in a diesel engine cyclinder during compression, but prior to fuel injection under engine starting conditions. During a portion of the warm-up sequence, the intensity of this emission exhibits a strong correlation to the phasing of the subsequent combustion. Engine exhaust measurements taken from a continuously misfiring, motored engine confirm the generation of formaldehyde (HCHO) in such processes. Fractions of this compound are expected to be recycled as residual to participate in the following combustion cycle. Spectral measurements taken during the compression period prior to fuel injection match the features of Emeleus' cool flame HCHO bands that have been observed during low temperature heat release reactions occurring in lean HCCI combustion. That the signal from the OH* bands is weak implies a buildup of HCHO during compression.

The effect of biodiesel on the Particulate emissions is gaining significant attention particularly with the drive for the use of alternative fuels. The particulate matter (PM), especially having a diameter less than 50 nm called the Nanoparticles or Nucleation mode particles (NMPs), has been raising concerns about its effect on human health. To better understand the effect of biodiesel and its blends on particulate emissions, steady state tests were conducted on a small-bore single-cylinder high-speed direct-injection research diesel engine. The engine was fueled with Ultra-Low Sulfur Diesel (ULSD or B-00), a blend of 20% soy-derived biodiesel and 80% ULSD on volumetric basis (B-20), B-40, B-60, B-80 and 100% soy-derived biodiesel (B-100), equipped with a common rail injection system, EGR and swirl control systems at a load of 5 bar IMEP and constant engine speed of 1500 rpm.

This paper proposes a simulation based methodology to assess plug-in hybrid vehicle (PHEV) behavior over 24-hour periods. Several representative 24-hour missions comprise naturalistic cycle data and information about vehicle resting time. The data were acquired during Filed Operational Tests (FOT) of a fleet of passenger vehicles carried out by the University of Michigan Transportation Research Institute (UMTRI) for safety research. Then, PHEV behavior is investigated using a simulation with two different charging scenarios: (1) Charging overnight; (2) Charging whenever possible. Charging/discharging patterns of the battery as well as trends of charge depleting (CD) and charge sustaining (CS) modes at each scenario were assessed. Series PHEV simulation is generated using Powertrain System Analysis Toolkit (PSAT) developed by Argonne National Laboratory (ANL) and in-house Matlab codes.

This paper proposes a methodology to develop a nonlinear model predictive control (NMPC) of a dual-independent variable valve timing (di-VVT) engine using discretized nonlinear engine models. In multiple-input-multiple-output (MIMO) systems, model based control methodologies are critical for realizing the full potential of complex hardware. Fast and accurate control oriented models (COM) that capture combustion physics, actuator and system dynamics are prerequisites for developing NMPC. We propose a multi-scale simulation approach to generate the non-linear combustion model, where the high-fidelity engine cycle simulation is utilized to characterize effects of turbulence, air-to-fuel ratio, residual fraction, and nitrogen oxide (NOx) emissions. The input-to-output relations are subsequently captured with artificial neural networks (ANNs). Manifold and actuator dynamics are discretized to reduce computation efforts.

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.

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.

Combustion instability and white smoke emissions are serious problems during cold starting of diesel engines. In this investigation, a model has been applied to predict misfiring based on an analysis of the autoignition process. The effect of injection timing on combustion instability during the cold start transient, at different ambient temperatures is investigated, both theoretically and experimentally. Maps have been developed to show the zones where misfiring would occur. The experimental work was conducted on a direct injection heavy-duty diesel engine in a cold room. The room temperature covered a range from 21 ° C to -10 ° C. The cycle-by-cycle data analysis was made and results plotted on the developed maps. The experimental results correlated fairly well with the model prediction. Based on the analysis, a new strategy for cold starting can be developed to reduce combustion instability and white smoke emissions.

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 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.