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To meet the target of the CO2 regulations, it is mandatory to replace high-carbon fossil fuels with low-carbon fuels. Diesel/Natural Gas (NG) reactivity-controlled compression ignition (RCCI) can reduce CO2 emission, which stratifies two types of fuels with different reactivity. And also, RCCI produces less NOx and particulate matter emissions by reducing the in-cylinder temperature. However, RCCI must still be enhanced in terms of the thermal and combustion efficiencies at low and medium loads. In this work, a modified piston geometry was applied to improve the RCCI combustion. The piston geometry was designed to minimize heat loss and reduce flame quenching in an RCCI engine. Experiments were conducted using a single-cylinder engine with a displacement volume of 1,000 cc. Diesel was directly injected into the cylinder, and NG was fed through the intake port.

Spark ignition knock is highly sensitive to changes in intake air temperature. Hot surface temperatures due to ceramic thermal barrier coatings increase knock propensity by elevating the incoming air temperature, thus mitigating the positive impacts of low heat transfer losses by requiring spark retard to avoid knock. Low thermal inertia coatings (i.e. Temperature swing coatings) have been proposed as a means of reducing or eliminating the open cycle charge heating penalty of traditional TBCs through a combination of low thermal conductivity and low volumetric heat capacity materials. However, in order to achieve a meaningful gain in efficiency, a significant fraction of the combustion chamber must be coated. In this study, a coated piston and intake and exhaust valves with coated combustion faces, backsides, and stems are installed in a single-cylinder research engine to evaluate the effect of high coated fractions of the combustion chamber in a knock-sensitive architecture.

In military applications, diesel engines are required to achieve high power outputs and therefore must operate at high loads. This high load operation leads to high piston component temperatures and heat rejection rates limiting the packaged power density of the powertrain. To help predict and understand these constraints, as well as their effects on performance, a thermodynamic engine model coupled to a finite element heat conduction solver is proposed and validated in this work. The finite element solver is used to calculate crank angle resolved, spatially averaged piston temperatures from in-cylinder heat transfer calculations. The calculated piston temperatures refine the heat transfer predictions as well requiring iteration between the thermodynamic model and finite element solver.

In marine or stationary engines, consistent engine performance must be guaranteed for long-haul operations. A dual-fuel combustion strategy was used to reduce the emissions of particulates and nitrogen oxides in marine engines. However, in this case, the combustion stability was highly affected by environmental factors. To ensure consistent engine performance, the in-cylinder pressure measured by piezoelectric pressure sensors is generally measured to analyze combustion characteristics. However, the vulnerability to thermal drift and breakage of sensors leads to additional maintenance costs. Therefore, an indirect measurement via a reconstruction model of the in-cylinder pressure from engine block vibrations was developed. The in-cylinder pressure variation is directly related to the block vibration; however, numerous noise sources exist (such as, valve impact, piston slap, and air flowage).

Opposed-piston 2-stroke (OP-2S) engines have the potential to achieve higher thermal efficiency than a typical diesel engine. However, the uniflow scavenging process is difficult to control over a wide range of speeds and loads. Scavenging performance is highly sensitive to pressure dynamics, port timings, and port design. This study proposes an analysis of the effects of port vane angle on the scavenging performance of an opposed-piston 2-stroke engine via simulation. A CFD model of a three-cylinder opposed-piston 2-stroke was developed and validated against experimental data collected by Achates Power Inc. One of the three cylinders was then isolated in a new model and simulated using cycle-averaged and cylinder-averaged initial/boundary conditions. This isolated cylinder model was used to efficiently sweep port angles from 12 degrees to 29 degrees at different pressure ratios.

The application of dual-fuel combustion in the freight transportation sectors has received considerable attention due to the capability of achieving higher fuel efficiency and less pollutant emissions than the conventional diesel engines. In this study, high-speed flame visualization was used to investigate the phenomena of natural gas/diesel dual-fuel combustion in a single-cylinder heavy-duty engine with optical access. To implement diverse fuel blending conditions, diesel injection timing and natural gas substitution ratio were varied under constant fuel energy input. A novel flame regime separation method was implemented based on color segmentation in HSV color space to characterize the spatial distributions of premixed and non-premixed flame regimes. Flame images for larger natural gas substitution showed a significant reduction in the non-premixed flame regime accompanied by flame propagation along the vaporized diesel sprays.

In this work, a novel opposed piston architecture is proposed where one crankshaft rotates at twice the speed of the other. This results in one piston creating a 2-stroke profile and another with a 4-stroke profile. In this configuration, the slower piston operates in the 2-stroke CAD domain, while the faster piston completes 2 reciprocating cycles in the same amount of time (4-stroke). The key benefit of this cycle is that the 4-stroke piston increases the rate of compression and expansion (dV/dθ), which lowers the combustion-induced pressure rise rate after top dead center (crank angle location of minimum volume). Additionally, it lowers in-cylinder temperatures and pressures more rapidly, resulting in a lower residence time at high temperatures, which reduces residence time for thermal NOx formation and reduces the temperature differential between the gas and the wall, thereby reducing heat transfer.

Lean stratified combustion is a mean to dilute the fuel-air mixture leaner than stoichiometric ratio, by using stratification of fuel gradient in a spark ignition engine. Under the lean stratified combustion, differed from the stoichiometric homogeneous charge combustion, flame could propagate through extremely rich air-fuel mixture, while the global air-fuel mixture is under lean condition. The rich mixture causes considerable amount of particulate matter, but, due to large effect of efficiency improvement, the attractive point is on fuel economy compare to homogeneous charge SI combustion. The easiest way to reduce particulate matter is changing fuel to gaseous hydrocarbon, to minimize evaporating and mixing period.

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.

Lean stratified combustion shows high potential to reduce fuel consumption because it operates without the intervention of a throttle valve. Despite its high fuel economy potential, it emits large amounts of particulate matter (PM) because the locally rich mixture is formed at the periphery of a spark plug. Furthermore, the combustion phasing angle is not realized at MBT ignition timing, which can bring high work conversion efficiency. Since PM emission and work conversion efficiency are in a trade-off relation, this research focused on reducing PM emission through achieving high work conversion efficiency. Two intake air control strategies were examined in this research; throttle operation and late intake valve closing (LIVC). The experiment was conducted in a single cylinder spray-guided direct injection spark ignition (SG-DISI) engine with liquefied petroleum gas (LPG). The injected fuel amount was fixed so as to investigate the effect of each strategy.

Most studies on supervisory controllers of hybrid electric vehicles consider only fuel economy in the objective function. Taking into consideration the importance of the energy storage system health and its impact on the vehicle’s functionality, cost, and warranty, recent studies have included battery degradation as the second objective function by proposing different energy management strategies and battery life estimation methods. In this paper, a rule-based supervisory controller is proposed that splits the torque demand based not only on fuel consumption, but also on the battery capacity fade using the concept of severity factor. For this aim, the severity factor is calculated at each time step of a driving cycle using a look-up table with three different inputs including c-rate, working temperature, and state of charge of the battery. The capacity loss of the battery is then calculated using a semi-empirical capacity fade model.

Most internal combustion engine makers have adopted after-treatment systems, such as selective catalytic reduction (SCR), diesel particulate filter (DPF), and diesel oxidation catalyst (DOC), to meet emission regulations. However, as the emission regulations become stricter, the size of the after-treatment systems become larger. This aggravates the price competitiveness of engine systems and causes fuel efficiency to deteriorate due to the increased exhaust pressure. Dual-fuel premixed charge compression ignition (DF-PCCI) combustion, which is one of the advanced combustion technologies, makes it possible to reduce nitrogen oxides (NOx) and particulate matter (PM) during the combustion process, while keeping the combustion phase controllability as a conventional diesel combustion (CDC). However, DF-PCCI combustion produces high amounts of hydrocarbon (HC) and carbon monoxide (CO) emissions due to the bulk quenching phenomenon under low load conditions as a huddle of commercialization.

Knocking combustion limits the downsized gasoline engines’ potential for improvement with regard to fuel economy. The high in-cylinder pressure and temperature caused by the adaptation of a turbocharger aggravates the tendency of the end-gas to autoignite. Thus, the knocking combustion does not allow for further advancing of the combustion phase. In this research, the effects of the ignition and valve timings on knocking combustion were investigated under steady-state conditions. Moreover, the optimal ignition and valve timings for the transient operations were derived with the aim of a greater fuel economy improvement, based on the steady-state analysis. A 2.0 liter turbocharged gasoline direct injection engine with continuously variable valve timing (CVVT), was utilized for this experiment. 2, 10, and 18 bar brake mean effective pressure (BMEP) load conditions were used to represent the low, medium, and high load operations, respectively.

Fuel atomization and air-fuel mixing processes play a dominant role on engine performance and emission characteristics in a direct injection compression ignition engine. Understanding of microscopic spray characteristics is essential to predict combustion phenomena. The present work investigated near nozzle flow and atomization characteristics of biodiesel fuels in a constant volume chamber. Waste cooking oil, Jatropha, and Karanja biodiesels were applied and the results were compared with those of conventional diesel fuel. The tested fuels were injected by a solenoid injector with a common-rail injection system. A high-speed camera with a long distance microscopic lens was utilized to capture the near nozzle flow. Meanwhile, Sauter mean diameter (SMD) was measured by a phase Doppler particle analyzer to compare atomization characteristics.

The spray and combustion of diesel fuel were investigated to provide a better understanding of the evaporation and combustion process under the simulated cold-start condition of a diesel engine. The experiment was conducted in a constant volume combustion chamber and the engine cranking period was selected as the target ambient condition. Mie scattering and shadowgraph techniques were used to visualize the liquid- and vapor-phase of the fuel under evaporating non-combustion conditions (oxygen concentration=0%). In-chamber pressure and direct flame visualization were acquired for spray combustion conditions (oxygen concentration=21%). The fuel was injected at an injection pressure of 30 MPa, which is the typical pressure during the cranking period.

This paper presents the transient power optimization of an organic Rankine cycle waste heat recovery (ORC-WHR) system operating on a heavy-duty diesel (HDD). The optimization process is carried on an experimentally validated, physics-based, high fidelity ORC-WHR model, which consists of parallel tail pipe and EGR evaporators, a high pressure working fluid pump, a turbine expander, etc. Three different ORC-WHR mixed vapor temperature (MVT) operational strategies are evaluated to optimize the ORC system net power: (i) constant MVT; (ii) constant superheat temperature; (iii) fuzzy logic superheat temperature based on waste power level. Transient engine conditions are considered in the optimization. Optimization results reveal that adaptation of the vapor temperature setpoint based on evaporation pressure strategy (ii) provides 1.1% mean net power (MNP) improvement relative to a fixed setpoint strategy (i).

This paper presents the development of an electrochemical aging model of LiFePO4-Graphite battery based on single particle (SP) model. Solid electrolyte interphase (SEI) growth is considered as the aging mechanism. It is intended to provide both sufficient fidelity and computational efficiency required for integration within the HEV power management optimization framework. The model enables assessment of the battery aging rate by considering instantaneous lithium ion surface concentration rather than average concentration, thus enhancing the fidelity of predictions. In addition, an approximate analytical method is applied to speed up the calculation while preserving required accuracy. Next, this aging model are illustrated two applications. First is hybrid electric powertrain system model integration and simulation.

This paper investigated the influence of the injector nozzle geometry on fuel consumption and exhaust emission characteristics of a light-duty diesel engine with 250 MPa injection. The engine used for the experiment was the 0.4L single-cylinder compression ignition engine. The diesel fuel injection equipment was operated under 250MPa injection pressure. Three injectors with nozzle hole number of 8 to 10 were compared. As the nozzle number of the injector increased, the orifice diameter decreased 105 μm to 95 μm. The ignition delay was shorter with larger nozzle number and smaller orifice diameter. Without EGR, the particulate matter(PM) emission was lower with larger nozzle hole number. This result shows that the atomization of the fuel was improved with the smaller orifice diameter and the fuel spray area was kept same with larger nozzle number. However, the NOx-PM trade-offs of three injectors were similar at higher EGR rate and higher injection pressure.

In this study, macroscopic spray characteristics of Waste cooking oil (WCO), Jatropha oil, Karanja oil based biodiesels and baseline diesel were compared under simulated engine operating condition in a constant volume spray chamber (CVSC). The high pressure and high temperature ambient conditions of a typical diesel engine were simulated in the CVSC by performing pre-ignition before the fuel injection. The spray imaging was conducted under absence of oxygen in order to prevent the fuels from igniting. The ambient pressure and temperature for non-evaporating condition were 3 MPa and 300 K. Meanwhile, the spray tests were performed under the ambient pressure and temperature of 4.17 MPa and 804 K under evaporating condition. The fuels were injected by a common-rail injection system with injection pressure of 80 MPa. High speed Mie-scattering technique was employed to visualize the evaporating sprays.

This paper develops a methodology to optimize the supervisory controller for a heavy-duty series hybrid electric vehicle, with consideration of battery aging and cooling loss. Electrochemistrybased battery aging model is integrated into vehicle model. The side reaction, reductive electrolyte decomposition, is modeled to determine battery aging rate, and the thermal effect on this reaction rate is considered by Arrhenius Law. The resulting capacity and power fading is included in the system-level study. Sensitivity analysis shows that battery aging could cause fuel economy loss by 5.9%, and increasing temperature could improve fuel economy at any given state-of-health, while accelerating battery aging. Stochastic dynamic programming algorithm is applied to a modeled system to handle the tradeoff between two objectives: maximizing fuel economy and minimizing battery aging.