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Fe16N2 is one of the promising candidates for rare-earth free magnets. It possesses a giant saturation magnetization (Ms) and reasonably high magnetocrystalline anisotropy. Past efforts made in synthesizing Fe16N2 were mostly on thin films, foils, and fine powders through different processes including sputtering, ion implantation, chemical reactions, and ball milling; this could cause a challenge of scaling up into massive production. The limitation in massive production of Fe16N2 requires intensive investigations to conquer. Compared with our previous endeavor of the low-temperature synthesizing process of Fe16N2 in bulk form, this paper proposes a method of gaseous nitridation with a high-temperature approach that can improve the process efficiency by applying the quenching and tempering treatment to address the challenge.

Extended range electric vehicles (EREVs) are a potential solution for fossil fuel usage mitigation and on-road emissions reduction. The use of EREVs can be shown to yield significant fuel economy improvements when proper energy management strategies (EMSs) are employed. However, many in-use EREVs achieve only moderate fuel reduction compared to conventional vehicles due to the fact that their EMS is far from optimal. This paper focuses on in-use rule-based EMSs to improve the fuel efficiency of EREV last-mile delivery vehicles equipped with two-way Vehicle-to-Could (V2C) connectivity. The method uses previous vehicle data collected on actual delivery routes and machine learning methods to improve the fuel economy of future routes. The paper first introduces the main challenges of the project, such as inherent uncertainty in human driver behavior and in the roadway environment. Then, the framework of our practical physics-model guided data-driven approach is introduced.

Previously, the authors have proposed a novel strategy called trajectory based combustion control for the free piston engine (FPE) where the shape of the piston trajectory between top and bottom dead centers is used as a control input to modulate the chemical kinetics of the fuel-air mixture inside the combustion chamber. It has been shown that in case of a hydraulic free piston engine (HFPE), using active motion control, the piston inside the combustion chamber can be forced to track any desired trajectory, despite the absence of a crankshaft, providing reliable starting and stable operation. This allows the use of optimized piston trajectory for every operating point which minimizes fuel consumption and emissions. In this work, this concept is extended to an electrical free piston engine (EFPE) as a modular power source.

In this work, engine-out particle mass (PM) and particle number (PN) emissions were experimentally examined from a gasoline direct injection (GDI) engine operating in two lean combustion modes and one stoichiometric mode with a fuel of known properties. Ten steady state operating points, two constant speed load steps, and an engine cold start were examined. Results showed that solid particles emitted from the engine under steady state stoichiometric conditions had a uniquely broad size distribution that was relatively flat between the diameters of 10 and 100 nm. In most operating conditions, lean homogenous modes can achieve lower particle emissions than stoichiometric modes while improving engine thermal efficiency. Alternatively, lean stratified operating modes resulted in significantly higher PN and PM emissions than both lean homogeneous and stoichiometric modes with increased efficiency only at low engine load.

A key challenge for the practical introduction of dual-fuel reactivity controlled compression ignition (RCCI) combustion modes in diesel engines is the requirement to store two fuels on-board. This work demonstrates that partially reforming diesel fuel into less reactive products is a promising method to allow RCCI to be implemented with a single stored fuel. Experiments were conducted using a thermally integrated reforming reactor in a reformed exhaust gas recirculation (R-EGR) configuration to achieve RCCI combustion using a light-duty diesel engine. The engine was operated at a low engine load and two reformed fuel percentages over ranges of exhaust gas recirculation (EGR) rate and main diesel fuel injection timing. Results show that RCCI-like emissions of NOx and soot were achieved load using the R-EGR configuration. It was also shown that complete fuel conversion in the reforming reactor is not necessary to achieve sufficiently low fuel reactivity for RCCI combustion.

Fuel reforming during a Negative Valve Overlap (NVO) period is an effective approach to control Low Temperature Gasoline Combustion (LTGC) ignition. Previous work has shown through experiments that primary reference fuels reform easily and produce several species that drastically affect ignition characteristics. However, our previous research has been unable to accurately predict measured reformate composition at the end of the NVO period using simple single-zone models. In this work, we use a stochastic reactor model (SRM) closed cycle engine simulation to predict reformate composition accounting for in-cylinder temperature and mixture stratification. The SRM model is less computationally intensive than CFD simulations while still allowing the use of large chemical mechanisms to predict intermediate species formation rates.

Partially premixed low temperature combustion (LTC) in diesel engines is a strategy for reducing soot and NOX formation, though it is accompanied by higher unburned hydrocarbon (UHC) emissions compared to conventional mixing-controlled diesel combustion. In this work, two independent methods of quantifying light UHC species from a diesel engine operating in early LTC (ELTC) modes were compared: Fourier transform infrared (FT-IR) spectroscopy and gas chromatography-mass spectroscopy (GC-MS). A sampling system was designed to capture and transfer exhaust samples for off-line GC-MS analysis, while the FT-IR sampled and quantified engine exhaust in real time. Three different ELTC modes with varying levels of exhaust gas recirculation (EGR) were implemented on a modern light-duty diesel engine. GC-MS and FT-IR concentrations were within 10 % for C2H2, C2H4, C2H6, and C2H4O. While C3H8 was identified and quantified by the FT-IR, it was not detected by the GCMS.

Many dual fuel technologies have been proposed for diesel engines. Implementing dual fuel modes can lead to emissions reductions or increased efficiency through using partially premixed combustion and fuel reactivity control. All dual fuel systems have the practical disadvantage that a secondary fuel storage and delivery system must be included. Reforming the primary diesel to a less reactive vaporized fuel on-board has potential to overcome this key disadvantage. Most previous research regarding on-board fuel reforming has been focused on producing significant quantities of hydrogen. However, only partially reforming the primary fuel is sufficient to vaporize and create a less volatile fuel that can be fumigated into an engine intake. At lower conversion efficiency and higher equivalence ratio, reforming reactors retain higher percentage of the inlet fuel’s heating value thus allowing for greater overall engine system efficiency.

In-cylinder reforming of injected fuel during an auxiliary negative valve overlap (NVO) period can be used to optimize main-cycle auto-ignition phasing for low-load Low-Temperature Gasoline Combustion (LTGC), where highly dilute mixtures can lead to poor combustion stability. When mixed with fresh intake charge and fuel, these reformate streams can alter overall charge reactivity characteristics. The central issue remains large parasitic heat losses from the retention and compression of hot exhaust gases along with modest pumping losses that result from mixing hot NVO-period gases with the cooler intake charge. Accurate determination of total cycle energy utilization is complicated by the fact that NVO-period retained fuel energy is consumed during the subsequent main combustion period. For the present study, a full-cycle energy analysis was performed for a single-cylinder research engine undergoing LTGC with varying NVO auxiliary fueling rates and injection timing.

Negative Valve Overlap (NVO) is a potential control strategy for enabling Low-Temperature Gasoline Combustion (LTGC) at low loads. While the thermal effects of NVO fueling on main combustion are well-understood, the chemical effects of NVO in-cylinder fuel reforming have not been extensively studied. The objective of this work is to examine the effects of fuel molecular structure on NVO fuel reforming using gas sampling and detailed speciation by gas chromatography. Engine gas samples were collected from a single-cylinder research engine at the end of the NVO period using a custom dump-valve apparatus. Six fuel components were studied at two injection timings: (1) iso-octane, (2) n-heptane, (3) ethanol, (4) 1-hexene, (5) cyclohexane, and (6) toluene. All fuel components were studied neat except for toluene - toluene was blended with 18.9% nheptane by liquid volume to increase the fuel reactivity.

A continuing topic of interest is how to best use information from Event Data Recorders (EDR) to reconstruct crashes. If one has a model which can predict EDR data from values of the target variables of interest, such as vehicle speeds at impact, then in principle one can invert this model to estimate the target values from EDR measurements. In practice though this can require solving a system of nonlinear equations and a reasonably flexible method for carrying this out involves replacing the inverse problem with nonlinear least-squares (NLS) minimization. NLS has been successfully applied to two-vehicle planar impact crashes in order to estimate impact speeds from different combinations of EDR, crush, and exit angle measurements, but an open question is how to assess the uncertainty associated with these estimates. This paper describes how Markov Chain Monte Carlo (MCMC) simulation can be used to quantify uncertainty in planar impact crashes.

The impact of compression ratio on engine efficiency is well known. A plethora of mechanical concepts have been proposed for altering engine compression ratio in real time. Some of these, like free-piston configurations or complex crank-slider mechanisms have the added ability to alter piston trajectory along with compression ratio. This secondary modality raises the question: Is there a more optimal piston position versus crank-angle profile for spark-ignition (SI) engines than the near-sinusoidal motion produced by a traditional four-bar crank-slider mechanism? Very little published literature directly addresses this question. This work presents the results of a quasi-dimensional SI engine model using piston trajectory as an input. Specific trajectory traits including increased dwell at top dead center and asymmetric compression and expansion strokes were swept. The trajectory also was optimized using a single objective genetic algorithm with 60 individuals and 40 generations.

Control of vehicular platoons has been a problem of interest in the controls domain for the past 40 years. This problem gained a lot of popularity when the California PATH (Partners for Advanced Transportation Technology) program was operational. String stability is an important design criterion in this problem and it has been shown that lead vehicle information is essential to achieve it. This work builds upon the existing framework and presents a controller form for each follower in the string where the lead vehicle information is used explicitly to analytically demonstrate string stability. The discussion is focused on using information from immediate neighbors to achieve string stability. Recent developments in distributed control are an attractive framework for control design where each agent has access to states of the neighbors and not all agents in the network. In this work, the aim is to design sparse H2 controllers and then perform a check on string stability.

Diesel particulate filter (DPF) technology has proven performance and reliability. However, the addition of a DPF adds significant cost and packaging constraints leading some manufacturers to design engines that reduce particulate matter in-cylinder. Such engines utilize high fuel injection pressure, moderate exhaust gas recirculation and modified injection timing to mitigate soot formation. This study examines such an engine designed to meet US EPA Interim Tier 4 standards for off-highway applications without a DPF. The engine was operated at four steady state modes and aerosol measurements were made using a two-stage, ejector dilution system with a scanning mobility particle sizer (SMPS) equipped with a catalytic stripper (CS) to differentiate semi-volatile versus solid components in the exhaust. Gaseous emissions were measured using an FTIR analyzer and particulate matter mass emissions were estimated using SMPS data and an assumed particle density function.

The critical speed method uses measurements of the radii of yawmarks left by vehicles, together with values for centripetal acceleration, to estimate the speeds of the vehicles when the yawmarks were made. Several field studies have indicated that equating the centripetal force with braking friction produced biased estimates, but that the biases tended to be small (e.g. within 10%-15% on average) and led to underestimates, suggesting that the method can be useful for forensic purposes. Other studies, however, have challenged this conclusion. The critical speed method has also seen use in safety-related research, where it is important to have a reliable assessment of the uncertainty associated with a speed estimate. This paper describes a variant of the critical speed method, where data from field tests lead to an informative prior probability distribution for the centripetal acceleration.

Diesel fuel injection systems are operating at increasingly higher pressure (up to 250 MPa) with smaller clearances, making them more sensitive to diesel fuel contaminants. Most liquid particle counters have difficulty detecting particles <4 μm in diameter and are unable to distinguish between solid and semi-solid materials. The low conductivity of diesel fuel limits the use of the Coulter counter. This raises the need for a new method to characterize small (<4 μm) fuel contaminants. We propose and evaluate an aerosolization method for characterizing solid particulate matter in diesel fuel that can detect particles as small as 0.5 μm. The particle sizing and concentration performance of the method were calibrated and validated by the use of seed particles added to filtered diesel fuel. A size dependent correction method was developed to account for the preferential atomization and subsequent aerosol conditioning processes to obtain the liquid-borne particle concentration.

Cruise control is one of the most critical issues that manufacturers concern about. But last many researches just focused on engine side control with general step transmission. Continuously Variable Transmissions (CVT) can cover a wide range of ratios continuously. This makes it possible to operate a combustion engine in more efficient working points than stepped transmission. With this merit, fuel optimal cruise control by CVT ratio control is possible with precise longitudinal dynamic model. Estimation of longitudinal load such as road slope and rolling resistance is essential for precise cruise control of automotive vehicle. In this paper, using model based road slope estimation method with gravity sensor, precise longitudinal dynamic model of automotive vehicle is presented. Real-time adaptive algorithm is also implemented for detecting external driving condition change and compensating bias of g-sensor.

In statistical modeling, cross-validation refers to the practice of fitting a model with part of the available data, and then using predictions of the unused data to test and improve the fitted model. In accident reconstruction, cross-validation is possible when two different measurements can be used to estimate the same accident feature, such as when measured skidmark length and pedestrian throw distance each provide an estimate of impact speed. In this case a Bayesian cross-validation can be carried out by (1) using one measurement and Bayes theorem to compute a posterior distribution for the impact speed, (2) using this posterior distribution to compute a predictive distribution for the second measurement, and then (3) comparing the actual second measurement to this predictive distribution. An actual measurement falling in an extreme tail of the predictive distribution suggests a weakness in the assumptions governing the reconstruction.

Ethanol, used widely as a spark-ignition (SI) engine fuel, has seen minimal success as a compression ignition (CI) engine fuel. The lack of success of ethanol in CI engines is mainly due to ethanol's very low cetane number and its poor lubricity properties. Past researchers have utilized nearly pure ethanol in a CI engine by either increasing the compression ratio which requires extensive engine modification and/or using an expensive ignition improver. The objective of this work was to demonstrate the ability of a hydrogen port fuel injection (PFI) system to facilitate the combustion of ethanol in a CI engine. Non-denatured anhydrous ethanol, mixed with a lubricity additive, was used in a variable compression ratio CI engine. Testing was conducted by varying the amount of bottled hydrogen gas injected into the intake manifold via a PFI system. The hydrogen flowrates were varied from 0 - 10 slpm.

The subjective aspects of comfort in three different cooling garments, the MACS-Delphi, Russian Orlan, and LCVG were evaluated. Six subjects (4 males and 2 females) were tested in separate sessions in each garment and in one of two environmental chamber conditions: 24°C and 35°C. Subjects followed a staged exercise/rest protocol with different levels of physical exertion at different stages. Thermal comfort and heat perception were assessed by ratings on visual analog scales. Ratings of physical comfort of the garment and also garment flexibility in positions simulating movements during planetary exploration were also obtained. The findings indicated that both overall thermal comfort and head thermal comfort were rated highest in the MACS-Delphi at 24°C. The Orlan was rated lowest on physical comfort and less flexible in different body positions.