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The transportation sector in the United States is a major contributor to global energy consumption and carbon dioxide emission. To assess the future potentials of different technologies in addressing these two issues, we used a family of simulation programs to predict fuel consumption for passenger cars in 2020. The selected technology combinations that have good market potential and could be in mass production include: advanced gasoline and diesel internal combustion engine vehicles with automatically-shifting clutched transmissions, gasoline, diesel, and compressed natural gas hybrid electric vehicles with continuously variable transmissions, direct hydrogen, gasoline and methanol reformer fuel cell hybrid electric vehicles with direct ratio drive, and battery electric vehicle with direct ratio drive.

Computer simulation of extravehicular activity (EVA) is increasingly being used in planning and training for EVA. A space suit model is an important, but often overlooked, component of an EVA simulation. Because of the inherent difficulties in collecting angle and torque data for space suit joints in realistic conditions, little data exists on the torques that a space suit’s wearer must provide in order to move in the space suit. A joint angle and torque database was compiled on the Extravehicular Maneuvering Unit (EMU), with a novel measurement technique that used both human test subjects and an instrumented robot. Using data collected in the experiment, a hysteresis modeling technique was used to predict EMU joint torques from joint angular positions. The hysteresis model was then applied to EVA operations by mapping out the reach and work envelopes for the EMU.

Research conducted at the Supercritical (SC) facility of MIT's Energy Laboratory provided visual confirmation of a single phase, homogeneous water/fuel mixture near the critical temperature and pressure of water. Equal volumes of water and diesel fuel were observed to be completely miscible, and high temperature polymerization of fuel molecules was not found. This is believed to be the first observation of a solution of diesel fuel and water. This mixture was subsequently burned under atmospheric spray conditions with very low NOx, smoke, CO, and HC. The results suggested that in-cylinder combustion in a compression ignition engine was warranted. Tests were conducted in a single cylinder, air-cooled, naturally aspirated, 3.5 horsepower Yanmar diesel engine. The compressibility of this new fuel composition necessitated a modified injector to provide smooth operation.

A method is presented for predicting the viable operating range of homogeneous-charge compression-ignition (HCCI) engines. A fundamental criterion for predicting HCCI knock is described and used to predict the minimum air/fuel ratio (and hence maximum torque) available from the engine. The lean (misfire) limit is computed using a modification of the multi-zone method of Aceves et al. [1]. Numerical improvements are described which allow even very complex fuel chemistry to be rapidly modeled on a standard PC. The viable operating range for an HCCI engine burning a primary reference fuel (PRF 95) is predicted and compared with literature experimental data. The new ability to accurately predict the operating range for any given HCCI engine/fuel combination should considerably simplify the tasks of designing a robust engine and identifying suitable fuels for HCCI.

Efficient aftertreatment management requires accurate sensing of both particulate filter soot and ash levels for optimized feedback control. Currently a combination of pressure drop measurements and predictive models are used to indirectly estimate the loading state of the filter. Accurate determination of filter soot loading levels is challenging under certain operating conditions, particularly following partial regeneration events and at low flow rate (idle) conditions. This work applied radio frequency (RF)-based sensors to provide a direct measure of the particulate filter soot levels in situ. Direct measurements of the filter loading state enable advanced feedback controls to optimize the combined engine and aftertreatment system for improved DPF management. This study instrumented several cordierite and aluminum titanate diesel particulate filters with RF sensors. The systems were tested on a range of light- and heavy-duty applications, which included on- and off-road engines.

This paper presents the results of a study of how people interacted with a production voice-command based interface while driving on public roadways. Tasks included phone contact calling, full address destination entry, and point-of-interest (POI) selection. Baseline driving and driving while engaging in multiple-levels of an auditory-vocal cognitive reference task and manual radio tuning were used as comparison points. Measures included self-reported workload, task performance, physiological arousal, glance behavior, and vehicle control for an analysis sample of 48 participants (gender balanced across ages 21-68). Task analysis and glance measures confirm earlier findings that voice-command interfaces do not always allow the driver to keep their hands on the wheel and eyes on the road, as some assume.

The challenge of developing a robust, real-time driver gaze classification system is that it has to handle difficult edge cases that arise in real-world driving conditions: extreme lighting variations, eyeglass reflections, sunglasses and other occlusions. We propose a single-camera end-toend framework for classifying driver gaze into a discrete set of regions. This framework includes data collection, semi-automated annotation, offline classifier training, and an online real-time image processing pipeline that classifies the gaze region of the driver. We evaluate an implementation of each component on various subsets of a large onroad dataset. The key insight of our work is that robust driver gaze classification in real-world conditions is best approached by leveraging the power of supervised learning to generalize over the edge cases present in large annotated on-road datasets.

Advanced driver assistance systems (ADAS) are an increasingly common feature of modern vehicles. The influence of such systems on driver behavior, particularly in regards to the effects of intermittent warning systems, is sparsely studied to date. This paper examines dynamic changes in physiological and operational behavior during lane departure warnings (LDW) in two commercial automotive systems utilizing on-road data. Alerts from the systems, one using auditory and the other haptic LDWs, were monitored during highway driving conditions. LDW events were monitored during periods of single-task driving and dual-task driving. Dual-task periods consisted of the driver interacting with the vehicle’s factory infotainment system or a smartphone to perform secondary visual-manual (e.g., radio tuning, contact dialing, etc.) or auditory-vocal (e.g. destination address entry, contact dialing, etc.) tasks.

This paper evaluates the lag time in a turbocharged single cylinder engine in order to determine its viability in transient applications. The overall goal of this research is to increase the power output, reduce the fuel economy, and improve emissions of single cylinder engines through turbocharging. Due to the timing mismatch between the exhaust stroke, when the turbocharger is powered, and the intake stroke, when the engine intakes air, turbocharging is not conventionally used in commercial single cylinder engines. Our previous work has shown that it is possible to turbocharge a four stroke, single cylinder, internal combustion engine using an air capacitor, a large volume intake manifold in between the turbocharger compressor and engine intake. The air capacitor stores compressed air from the turbocharger during the exhaust stroke and delivers it during the intake stroke.

The combustion process after auto-ignition is investigated. Depending on the non-uniformity of the end gas, auto-ignition could initiate a flame, produce pressure waves that excite the engine structure (acoustic knock), or result in detonation (normal or developing). For the “acoustic knock” mode, a knock intensity (KI) is defined as the pressure oscillation amplitude. The KI values over different cycles under a fixed operating condition are observed to have a log-normal distribution. When the operating condition is changed (over different values of λ, EGR, and spark timing), the mean (μ) of log (KI/GIMEP) decreases linearly with the correlation-based ignition delay calculated using the knock-point end gas condition of the mean cycle. The standard deviation σ of log(KI/GIMEP) is approximately a constant, at 0.63. The values of μ and σ thus allow a statistical description of knock from the deterministic calculation of the ignition delay using the mean cycle properties

The ability to make accurate decisions concerning early body-in-white architectures is critical to an automaker since these decisions often have long term cost and weight impacts. We address this need with a methodology which can be used to assist in body architecture decisions using process-based technical cost modeling (TCM) as a filter to evaluate alternate designs. Despite the data limitations of early design concepts, TCM can be used to identify key trends for cost-effectiveness between design variants. A compact body-in-white architecture will be used as a case study to illustrate this technique. The baseline steel structure will be compared to several alternate aluminum intensive structures in the context of production volume.

Ethanol and acetaldehyde emissions from a direct ignition spark ignition were measured using mass spectrometry. Previous methods focused on eliminating or minimizing interference from exhaust species with identical atomic mass and fragment ions created in ionization process. This paper describes a new technique which exploits the fragment ions from ethanol and acetaldehyde. A survey of mass spectra of all major species of exhaust gas was conducted. It was found that ethanol contributes most ions in mass number 31 and that no other gas species produces ions at this mass number. Acetaldehyde detection suffers more interference. Nevertheless, it was estimated that detection at mass number 43 is possible with 10% error from 2-methylbutane. This new technique was validated in an engine experiment. By running the engine with pure gasoline and E85, the validity of the technique can be checked.

The fuel effects on HCCI operation in a spark assisted direct injection gasoline engine are assessed. The low load limit has been extended with a pilot fuel injection during the negative valve overlap (NVO) period. The fuel matrix consists of hydrocarbon fuels and various ethanol blends and a butanol blend, plus fuels with added ignition improvers. The hydrocarbon fuels and the butanol blend do not significantly alter the high or the low limits of operation. The HCCI operation appears to be controlled more by the thermal environment than by the fuel properties. For E85, the engine behavior depends on the extent that the heat release from the pilot injected fuel in the NVO period compensates for the evaporative cooling of the fuel.

The increasingly stringent regulations for fuel economy and emissions require better optimization and control of oil consumption. One of the primary mechanisms of oil consumption is vaporization from the liner; we consider this as the “minimum oil consumption (MOC).” This paper presents a physical-mathematical cycle model for predicting the MOC. The numerical simulations suggest that the MOC is markedly sensitive to oil volatility, liner temperature, engine load and speed but less sensitive to oil film thickness. A one-line correlation is proposed for quick MOC estimations. It is shown to have <15% error compared to the cycle MOC computation. In the “dry region” (between top ring and OCR at the TDC), oil is depleted due to high heat and continual exposure to the combustion chamber.

Higher compression ratio and turbocharging, with engine downsizing can enable significant gains in fuel economy but require engine operating conditions that cause engine knock under high load. Engine knock can be avoided by supplying higher-octane fuel under such high load conditions. This study builds on previous MIT papers investigating Octane-On-Demand (OOD) to enable a higher efficiency, higher-boost higher compression-ratio engine. The high-octane fuel for OOD can be obtained through On-Board-Separation (OBS) of alcohol blended gasoline. Fuel from the primary fuel tank filled with commercially available gasoline that contains 10% by volume ethanol (E10) is separated by an organic membrane pervaporation process that produces a 30 to 90% ethanol fuel blend for use when high octane is needed. In addition to previous work, this paper combines modeling of the OBS system with passenger car and medium-duty truck fuel consumption and octane requirements for various driving cycles.

The performance of an extended stroke spark ignition engine has been assessed by cycle simulation. The base engine is a modern turbo-charged 4-stroke passenger car spark-ignition engine with 10:1 compression ratio. A complex crank mechanism is used so that the intake stroke remains the same while the expansion-to-intake stroke ratio (SR) is varied by changing the crank geometry. The study is limited to the thermodynamic aspect of the extended stroke; the changes in friction, combustion characteristic, and other factors are not included. When the combustion is not knock limited, an efficiency gain of more than 10 percent is obtained for SR = 1.5. At low load, however, there is an efficiency lost due to over-expansion. At the same NIMEP, the extended stroke renders the engine more resistant to knock. At SR of 1.8, the engine is free from knock up to 14 bar NIMEP at 2000 rpm. Under knocking condition, the required spark retard to prevent knocking is less with the extended stroke.

Comparisons have been made between dual-fuel (80% port-injection gasoline and 20% direct-injection diesel by mass) Highly Premixed Charge Combustion (HPCC) and blended-fuel (80% gasoline and 20% diesel) Low Temperature Combustion (LTC) modes on a 1-L single-cylinder test engine. In the HPCC mode, both early-injection (E-HPCC) and late-injection (L-HPCC) of diesel have been used. The comparisons have been conducted with a fixed fuel injection rate of 50 mg/cycle at 1500 rpm, and with the combustion phasing fixed (by adjusting the injection timing) so that the 50% heat release point (CA50) is at 8° ATDC. The rapid heat release process of LTC leads to the highest maximum pressure rise rate (MPRR). A two-peak heat release process is observed in L-HPCC, resulting in a lower MPRR. The heat release rate and MPRR values for the E-HPCC are comparable to the L-HPCC values. The EHPCC mode provides the lowest NOX emission. The soot emissions for all three modes are low.

A Multi-Objective Optimization (MOO) problem concerning the thermal control problem of Multifunctional Structures (MFSs) is here addressed. In particular the use of Multi-Objective algorithms from an optimization tool and Self-Organizing Maps (SOM) is proposed for the identification of the optimal topological distribution of the heating components for a multifunctional test panel, the Advanced Bread Board (ABB). MFSs are components that conduct many functions within a single piece of hardware, shading the clearly defined boundaries that identify traditional subsystems. Generally speaking, MFSs have already proved to be a disrupting technology, especially in aeronautics and space application fields. The case study exploited in this paper refers to a demonstrator breadboard called ABB. ABB belongs to a particular subset of an extensive family of MFS, that is, of thermo-structural panels with distributed electronics and a health monitoring network.

To manage the function of a vehicle's engine, transmission, and related subsystems, almost all modern vehicles make use of one or more electronic controllers running embedded software, henceforth referred to as a Powertrain Controller System or PCS. Fully validating this PCS is a necessary step of vehicle development, and the validation process requires extensive amounts of testing. Within the automotive industry, more and more of this validation testing is being performed using Hardware-in-the-Loop (HIL) simulators to automate the extensive test sequences. A HIL simulation typically mates the physical PCS to a closed-loop real time computer simulation of a powertrain. Interfacing the physical PCS hardware to a powertrain simulation requires the HIL simulator to have extensive signal input/output (I/O) electronics and simulated actuator electrical loading.

Initial measurements of water vapor temperature using a Fourier domain mode locking (FDML) laser were performed in a carefully controlled homogenous charge compression ignition engine with optical access. The gas temperature was inferred from water absorption spectra that were measured each 0.25 crank angle degrees (CAD) over a range of 150 CAD. Accuracy was tested in a well controlled shock tube experiment. This paper will validate the potential of this FDML laser in combustion applications.