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A phenomenological description, or “conceptual model,” of how direct-injection (DI) diesel combustion occurs has been derived from laser-sheet imaging and other recent optical data. To provide background, the most relevant of the recent imaging data of the author and co-workers are presented and discussed, as are the relationships between the various imaging measurements. Where appropriate, other supporting data from the literature is also discussed. Then, this combined information is summarized in a series of idealized schematics that depict the combustion process for a typical, modern-diesel-engine condition. The schematics incorporate virtually all of the information provided by our recent imaging data including: liquid- and vapor-fuel zones, fuel/air mixing, autoignition, reaction zones, and soot distributions.

The fidelity of the hybrid electric vehicle simulation is increased with the integration of a computationally-efficient finite-element based electric machine model, in order to address optimization of component design for system level goals. In-wheel electric motors are considered because of the off-road military application which differs significantly from commercial HEV applications. Optimization framework is setup by coupling the vehicle simulation to the constrained optimization solver. Utilizing the increased design flexibility afforded by the model, the solver is able to reshape the electric machine's efficiency map to better match the vehicle operation points. As the result, the favorable design of the e-machine is selected to improve vehicle fuel economy and reduce cost, while satisfying performance constraints.

This paper investigates series plug-in hybrid electric vehicle (PHEV) behavior during one-day with synthesized representative one-day missions. The amounts of electric energy and fuel consumption are predicted to assess the PHEV impact on the grid with respect to the driving distance and different charging scenarios: (1) charging overnight, (2) charging whenever possible. The representative cycles are synthesized using the extracted information from the real-world driving data in Southeast Michigan gathered through the Field Operational Tests (FOT) conducted by the University of Michigan Transportation Research Institute (UMTRI). The real-world driving data include 4,409 trips covering 830 independent days and temporal distributions of departure and arrival times. The sample size is large enough to represent real-world driving.

To gain a better understanding of how the onset of incomplete bulk-gas reactions changes with engine speed and fuel-type, a parametric study of HCCI combustion and emissions has been conducted. The experimental part of the study was performed at naturally aspirated conditions and included fueling sweeps at four engine speeds (600, 1200, 1800 and 2400 rpm) for research grade gasoline, pure iso-octane and two mixtures of the primary reference fuels (i.e. n-heptane and iso-octane) with octane numbers of 80 and 60. Additionally, single-zone CHEMKIN computations with a detailed mechanism for iso-octane were conducted. The results show that there is a strong coupling between the ignition quality of the fuel and the required intake temperature to phase the combustion at TDC. There is also a direct influence of intake temperature on the completeness of combustion. This is the case because the CO-to-CO2 reactions are highly sensitive to the peak combustion temperatures.

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.

Over the past decade, laser diagnostics have improved our understanding of many aspects of diesel combustion. However, interactions between the combusting fuel jet and the piston-bowl wall are not well understood. In heavy-duty diesel engines, with typical fuels, these interactions occur with the combusting vapor-phase region of the jet, which consists of a central region containing soot and other products of rich-premixed combustion, surrounded by a diffusion flame. Since previous work has shown that the OH radical is a good marker of the diffusion flame, planar laser-induced fluorescence (PLIF) imaging of OH was applied to an investigation of the diffusion flame during wall interaction. In addition, simultaneous OH PLIF and planar laser-induced incandescence (PLII) soot imaging was applied to investigate the likelihood for soot deposition on the bowl wall.

Reaching for higher loads and improving combustion-phasing control are important challenges for HCCI research. Although HCCI engines can operate with a variety of fuels, recent research has shown that fuels with two-stage autoignition have some significant advantages for overcoming these challenges. Because the amount of low-temperature heat release (LTHR) is proportional to the local equivalence ratio (ϕ), fuel stratification can be used to adjust the combustion phasing (CA50) and/or burn duration using various fuel-injection strategies. Two-stage ignition fuels also allow stable combustion even for extensive combustion-phasing retard, which reduces the knocking propensity. Finally, the LTHR reduces the required intake temperature, which increases the inducted charge mass for a given intake pressure, allowing higher fueling rates before knocking and NOx emissions become a problem. However, the amount of LTHR is normally highly dependent on the engine speed.

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.

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.

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 paper describes the approach, addresses integration challenges and discusses capabilities of the Hybrid Powertrain-in-the-Loop (H-PIL) facility for the series/hydrostatic hydraulic hybrid system. We describe the simulation of the open-loop and closed-loop hydraulic hybrid systems in H-PIL and its use for concurrent engineering and development of advanced supervisory strategies. The configuration of the hydraulic-hybrid system and details of the hydraulic circuit developed for the H-PIL integration are presented. Next, software and hardware interfaces between the real components and virtual systems are developed, and special attention is given to linking component-level controllers and system-level supervisory control. The H-PIL setup allows imposing realistic dynamic loads on hydraulic pump/motors and accumulator based on vehicle driving schedule.

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).

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.

An integrated vehicle system simulation has been developed to take advantage of advances in physical process and component models, flexibility of graphical programming environments (such as MATLAB-SIMULINK), and ever increasing capabilities of engineering workstations. A comprehensive, transient model of the multi-cylinder engine is linked with models of the torque converter, transmission, transfer case and differentials. The engine model is based on linking the appropriate number of single-cylinder modules, with the latter being thermodynamic models of the in-cylinder processes with built-in physical sub-models and transient capabilities to ensure high fidelity predictions. Either point mass or multi-body vehicle dynamics models can be coupled with the powertrain module to produce the ground vehicle simulation.

A series hydraulic hybrid concept (SHHV) has been explored as a potential pathway to an ultra-efficient city vehicle. Intended markets would be congested metropolitan areas, particularly in developing countries. The target fuel economy was ~100 mpg or 2.4 l/100km in city driving. Such an ambitious target requires multiple measures, i.e. low mass, favorable aerodynamics and ultra-efficient powertrain. The series hydraulic hybrid powertrain has been designed and analyzed for the selected light and aerodynamic platform with the expectation that (i) series configuration will maximize opportunities for regeneration and optimization of engine operation, (ii) inherent high power density of hydraulic propulsion and storage components will yield small, low-cost components, and (iii) high efficiency and high power limits for accumulator charging/discharging will enable very effective regeneration.

Tracer-based PLIF temperature diagnostics have been used to study the distribution and evolution of naturally occurring thermal stratification (TS) in an HCCI engine under fired and motored operation. PLIF measurements, performed with two excitation wavelengths (277, 308 nm) and 3-pentanone as a tracer, allowed investigation of TS development under relevant fired conditions. Two-line PLIF measurements of temperature and composition were first performed to track the mixing of the fresh charge and hot residuals during intake and early compression strokes. Results showed that mixing occurs rapidly with no measureable mixture stratification remaining by early compression (220°CA aTDC), confirming that the residual mixing is not a leading cause of thermal stratification for low-residual (4-6%) engines with conventional valve timing.

This work investigates the potential of in-cylinder thermal stratification for reducing the pressure-rise rate in HCCI engines, and the coupling between thermal stratification and combustion-phasing retard. A combination of computational and experimental results is employed. The computations were conducted using both a custom multi-zone version and the standard single-zone version of the Senkin application of the CHEMKIN III kinetics-rate code, and kinetic mechanisms for iso-octane. This study shows that the potential for extending the high-load operating limit by adjusting the thermal stratification is very large. With appropriate stratification, even a stoichiometric charge can be combusted with low pressure-rise rates, giving an output of 16 bar IMEPg for naturally aspirated operation. For more typical HCCI fueling rates (ϕ = 0.38 - 0.45), the optimal charge-temperature distribution is found to depend on both the amount of fuel and the combustion phasing.

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.

Energy management of hybrid vehicle has been a widely researched area. Strategies like dynamic programming (DP), equivalent consumption minimization strategy (ECMS), Pontryagin’s minimum principle (PMP) are well analyzed in literatures. However, the adaptive optimization work is still lacking, especially for reinforcement learning (RL). In this paper, Q-learning, as one of the model-free reinforcement learning method, is implemented in a mid-size 48V mild parallel hybrid electric vehicle (HEV) framework to optimize the fuel economy. Different from other RL work in HEV, this paper only considers vehicle speed and vehicle torque demand as the Q-learning states. SOC is not included for the reduction of state dimension. This paper focuses on showing that the EMS with non-SOC state vectors are capable of controlling the vehicle and outputting satisfactory results. Electric motor torque demand is chosen as action.

Refinements were made to a post-processing technique, termed the Thermal Stratification Analysis (TSA), that couples the mass fraction burned data to ignition timing predictions from the autoignition integral to calculate an apparent temperature distribution from an experimental HCCI data point. Specifically, the analysis is expanded to include all of the mass in the cylinder by fitting the unburned mass with an exponential function, characteristic of the wall-affected region. The analysis-derived temperature distributions are then validated in two ways. First, the output data from CFD simulations are processed with the Thermal Stratification Analysis and the calculated temperature distributions are compared to the known CFD distributions.