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Ducted Fuel Injection (DFI) engines have emerged as a promising technology in the pursuit of a clean and efficient combustion process. This article aims at elucidating the effect of piston geometry on the engine performance and emissions of a metal DFI engine. Three different types of pistons were investigated and the main piston design features including the piston bowl diameter, piston bowl slope angle, duct angle and the injection nozzle position were examined. To achieve the target, computational fluid dynamics (CFD) simulations were conducted coupled to a reduced chemical kinetics mechanism. Extensive validations were performed against the measured data from a conventional diesel engine. To calibrate the soot model, genetic algorithm and machine learning methods were utilized. The simulation results highlight the pivotal role played by piston bowl diameter and fuel injection angle in controlling soot emissions of a DFI engine.

Testing of ducted fuel injection (DFI) in a single-cylinder engine with production-like hardware previously showed that adding a duct structure increased soot emissions at the full load, rated speed operating point [1]. The authors hypothesized that the DFI flame, which travels faster than a conventional diesel combustion (CDC) flame, and has a shorter distance to travel, was being re-entrained into the on-going fuel injection around the lift-off length (LOL), thus reducing air entrainment into the on-going injection. The engine operating condition and the engine combustion chamber geometry were duplicated in a constant pressure vessel. The experimental setup used a 3D piston section combined with a glass fire deck allowing for a comparison between a CDC flame and a DFI flame via high-speed imaging. CH* imaging of the 3D piston profile view clearly confirmed the re-entrainment hypothesis presented in the previous engine work.

Low temperature combustion (LTC) modes are among the advanced combustion technologies which offer thermal efficiencies comparable to conventional diesel combustion and produce ultra-low NOx and particulate matter (PM) emissions. However, combustion timing control, excessive pressure rise rate and high cyclic variations are the common challenges encountered by the LTC modes. These challenges can be addressed by developing model-based control framework for the LTC engine. In the current study, in-cylinder pressure data for dual-fuel LTC engine operation is analyzed for 636 different operating conditions and the heat release rate (HRR) traces are classified into three distinct classes based on their distinct shapes. These classes are named as Type-1, Type-2 and Type-3, respectively.

A numerical investigation of a six-stroke direct injection compression ignition engine operation in a low temperature combustion (LTC) regime is presented. The fuel employed is a gasoline-like oxygenated fuel consisting of 90% isobutanol and 10% diethyl ether (DEE) by volume to match the reactivity of conventional gasoline with octane number 87. The computational simulations of the in-cylinder processes were performed using a high-fidelity multidimensional in-house 3D CFD code (MTU-MRNT) with improved spray-sub models and CHEMKIN library. The combustion chemistry was described using a two-component (isobutanol and DEE) fuel model whose oxidation pathways were given by a reaction mechanism with 177 species and 796 reactions.

Eco Approach and Departure (Eco-AnD) is a Connected Automated Vehicle (CAV) technology aiming to reduce energy consumption for crossing a signalized intersection or set of intersections in a corridor that features vehicle-to-infrastructure (V2I) communication capability. This research focuses on developing a Dynamic Programming (DP) based algorithm for a PHEV operating in Charge Depleting mode. The algorithm used the Reduced Order Energy Model (ROM) to capture the vehicle powertrain characteristics and road grade to capture the road dynamics. The simulation results are presented for a real-world intersection and 20-25% energy benefits are shown by comparing against a simulated human driver speed profile. The vehicle-level validation of the developed algorithm is carried out by performing closed-course track testing of the optimized speed solutions on a real CAV vehicle.

The AutoDrive Challenge competition sponsored by General Motors and SAE gives undergraduate and graduate students an opportunity to get hands-on experience with autonomous vehicle technology and development as they work towards their degree. Michigan Technological University has participated in the AutoDrive Challenge since its inception in 2017 with students participating through MTU’s Robotic System Enterprise. The MathWorks Simulation Challenge has been a component of the competition since its second year, tasking students with the development of perception, control and testing algorithms using MathWorks software products. This paper presents the pedagogical approach graduate student mentors used to enable students to build their understanding of autonomous vehicle concepts using familiar tools. This approach gives undergraduate students a productive experience with these systems that they may not have encountered in coursework within their academic program.

Hydrogen exhibits the notable attribute of lacking carbon dioxide emissions when used in internal combustion engines. Nevertheless, hydrogen has a very low energy density per unit volume, along with large emissions of nitrogen oxides and the potential for backfire. Thus, stratified charge combustion (SCC) is used to reduce nitrogen oxides and increase engine efficiency. Although SCC has the capacity to expand the lean limit, the stability of combustion is influenced by the mixture formation time (MFT), which determines the equivalence ratio. Therefore, quantifying the equivalence ratio under different MFT is critical since it determines combustion characteristics. This study investigates the viability of using a Laser Induced Breakdown Spectroscopy (LIBS) for measuring the jet equivalence ratio. Furthermore, study was conducted to analyze the effect of MFT and the double injection parameter, namely the dwell time and split ratio, on the equivalence ratio.

This research investigates the energy savings achieved through eco-driving controls in connected and automated vehicles (CAVs), with a specific focus on the influence of powertrain characteristics. Eco-driving strategies have emerged as a promising approach to enhance efficiency and reduce environmental impact in CAVs. However, uncertainty remains about how the optimal strategy developed for a specific CAV applies to CAVs with different powertrain technologies, particularly concerning energy aspects. To address this gap, on-track demonstrations were conducted using a Chrysler Pacifica CAV equipped with an internal combustion engine (ICE), advanced sensors, and vehicle-to-infrastructure (V2I) communication systems, compared with another CAV, a previously studied Chevrolet Bolt electric vehicle (EV) equipped with an electric motor and battery.

Methanol is one of the most promising fuels for the decarbonization of the off-road and transportation sectors. Although methanol is typically seen as an alternative fuel for spark ignition engines, mixing-controlled compression ignition (MCCI) combustion is typically preferred in most off-road and medium-and heavy-duty applications due to its high reliability, durability and high-efficiency. In this paper, the potential of using ignition enhancers to enable methanol MCCI combustion was investigated. Methanol was blended with 2-ethylhexyl nitrate (EHN) and experiments were performed in a single-cylinder production-like diesel research engine, which has a displacement volume of 0.83 L and compression ratio of 16:1. The effect of EHN has been evaluated with three different levels (3%vol, 5%vol, and 7%vol) under low- and part-load conditions. The injection timing has been swept to find the stable injection window for each EHN level and load.

This paper presents a methodology to optimize the blending of charge-depleting (CD) and charge-sustaining (CS) modes in a multi-mode plug-in hybrid electric vehicle (PHEV). The objective of the optimization is to best utilize onboard energy for minimum overall energy consumption based on speed and elevation profile. The optimization reduces overall energy consumption when the selected route cannot be completely driven in all-electric mode. The optimization method splits drive cycles into constant distance segments and then uses a reduced-order model to sort the segments by the best use of battery energy vs. fuel energy. The PHEV used in this investigation is the Stellantis Pacifica. Results support energy savings up to 20% which depend on the route and initial battery State of Charge (SOC). Initial optimization takes 1 second for 38 km and 3 seconds for 154 km.

This paper details testing for torque converter clutch (TCC) characterization during steady state and dynamic operation under controlled slip conditions on a dynamometer setup. The subject torque converter under test is a twin plate clutch with a dual stage turbine damper without a centrifugal pendulum absorber. An overview is provided of the dynamometer setup, hydraulic system and control techniques for regulating the apply pressure to the torque converter and clutch. To quantify the performance of the clutch in terms of control stability, pressure to torque relationship and the dynamic behavior during apply and release, a matrix of oil temperatures, output speeds, input torques, and clutch apply pressures were imposed upon the torque converter.

Ethanol blending is one method that can be used to reduce knock in spark ignition engines by decreasing the autoignition reactivity of the fuel and modifying its laminar flame speed. In this paper, the effects of ethanol blending on knock propensity and flame speed of petroleum and low-carbon gasoline fuels is analyzed. To do so, surrogate fuels were formulated for methanol-to-gasoline (MTG) and ethanol-to-gasoline (ETG) based on the fuels’ composition, octane number, and select physical properties; and 0-D and 1-D chemical kinetics simulations were performed to investigate reactivity and laminar flame speed, respectively. Results of MTG and ETG were compared against those of PACE-20, a well-characterized surrogate for regular E10 gasoline. Similarly to PACE-20, blending MTG and ETG with ethanol increases the fuel’s research octane number (RON) and sensitivity.

Low-temperature gasoline combustion (LTGC) engines can provide high efficiencies with very low NOx and soot emissions, but rapid control of the combustion timing remains a challenge. Partial Fuel Stratification (PFS) was demonstrated to be an effective approach to control combustion in LTGC engines. PFS is produced by a double-direct injection (DI) strategy with most of the fuel injected early in the cycle and the remainder of the fuel supplied by a second injection at a variable time during the compression stroke to vary the amount of stratification. Adjusting the stratification changes the combustion phasing, and this can be done on cycle-to-cycle basis by adjusting the injection timing. In this paper, the ability of PFS to control the combustion during wide engine load sweeps is assessed for regular gasoline and gasoline doped with 2-ethylhexyl nitrate (EHN). For PFS, the load control range is limited by combustion instability and poor combustion efficiency at low loads.

Methanol emerges as a compelling renewable fuel for decarbonizing engine applications due to a mature industry with high production capacity, existing distribution infrastructure, low carbon intensity and favorable cost. Methanol’s high flame speed and high autoignition resistance render it particularly well-suited for spark-ignition (SI) engines. Previous research showed a distinct phenomenon, known deflagration-based knock in methanol combustion, whereby knocking combustion was observed albeit without end-gas autoignition. This work studies the implications of deflagration-based knock on noise emissions by investigating the knock intensity and combustion noise at knock-limited operation of methanol in a single-cylinder direct-injection SI engine operated at both stoichiometric and lean (λ = 2.0) conditions. Results are compared against observations from a premium-grade gasoline.

Vehicle navigation in off-road environments is challenging due to terrain uncertainty. Various approaches that account for factors such as terrain trafficability, vehicle dynamics, and energy utilization have been investigated. However, these are not sufficient to ensure safe navigation of optionally manned ground vehicles that are prone to detection using thermal infrared (IR) seekers in combat missions. This work is directed towards the development of a vehicle IR signature aware navigation stack comprised of global and local planner modules to realize safe navigation for optionally manned ground vehicles. The global planner used A* search heuristics designed to find the optimal path that minimizes the vehicle thermal signature metric on the map of terrain’s apparent temperature. The local planner used a model-predictive control (MPC) algorithm to achieve integrated motion planning and control of the vehicle to follow the path waypoints provided by the global planner.

Optimizing fuel injection spray is essential to comply with stringent future emission regulations for hybrid vehicles and internal combustion engine vehicles, and the spray characteristics and geometry must be robust for various engine operating conditions. This study presents experimental and numerical assessments of spray for lateral-mounted gasoline direct injection (GDI) sprays with different plume arrangements to analyze collapse characteristics, which can significantly deteriorate the geometry and characteristics of fuel sprays. Novel spray characterization methods are applied to analyze complex spray collapse behaviors using LED-based diffusive back-illuminated extinction imaging (DBIEI) and 3D computed tomographic (CT) image reconstruction. High-fidelity computational fluid dynamics (CFD) simulations are performed to analyze the detailed spray characteristics besides experimental characterization.

Surrogate fuels that reproduce the characteristics of full-boiling range fuels are key tools to enable numerical simulations of fuel-related processes and ensure reproducibility of experiments by eliminating batch-to-batch variability. Within the PACE initiative, a surrogate fuel for regular-grade E10 (10%vol ethanol) gasoline representative of a U.S. market gasoline, termed PACE-20, was developed and adopted as baseline fuel for the consortium. Although extensive testing demonstrated that PACE-20 replicates the properties and combustion behavior of the full-boiling range gasoline, several concerns arose regarding the purity level required for the species that compose PACE-20. This is particularly important for cyclo-pentane, since commercial-grade cyclo-pentane typically shows 60%–85% purity. In the present work, the effects of the purity level of cyclo-pentane on the properties and combustion characteristics of PACE-20 were studied.

For 2D surface temperature monitoring applications, a variant of Electrical Impedance Tomography (EIT) was evaluated computationally in this study. Literature examples of poor sensor performance in the center of the 2D domains away from the side electrodes motivated these efforts which seek to overcome some of the previously noted shortcomings. In particular, the use of ‘sensing skins’ with novel tailored baseline conductivities was examined using the EIDORS package for EIT. It was found that the best approach for detecting a temperature hot spot depends on several factors such as the current injection (stimulation) patterns, the measurement patterns, and the reconstruction algorithms. For well-performing combinations of these factors, customized baseline conductivities were assessed and compared to the baseline uniform conductivity.

Molecular decomposition is a key chemical process in combustion systems. Particularly, the spatio-temporal information related to a fuel’s molecular breakdown is of high-importance regarding the development of combustion models and more specifically about chemical kinetic mechanisms. Most experiments rely on a variety of ultraviolet or infrared techniques to monitor the fuel breakdown process in 0-D type experiments such as those performed in shock-tubes or rapid compression machines. While the information provided by these experiments is necessary to develop and adjust kinetic mechanisms, they fail to provide the necessary data for applied combustion models to be predictive regarding the fuel’s molecular breakdown. In this work, we investigated the molecular decomposition of a fuel by applying high-speed planar laser Rayleigh scattering (PLRS).

Knock in spark-ignition (SI) engines has been a subject of many research efforts and its relationship with high efficiency operating conditions keeps it a contemporary issue as engine technologies push classical limits. Despite this long history of research, literature is lacking coherent and generalized descriptions of how knock is affected by changes in the full cylinder temperature field, residence time (engine speed), and air/fuel ratio. In this work, two dimensionless numbers are applied to fully 3D SI conditions. First, the characteristic time of autoignition (ignition delay) is compared against the characteristic time of end-gas deflagration, which was used to predict knocking propensity. Second, the temperature gradient of the end-gas is compared against a critical detonation-based temperature gradient, which predicts the knock intensity.