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Accurately predicting real-world vehicle energy consumption is essential for optimizing vehicle designs, enhancing energy efficiency, and developing effective energy management strategies. This paper presents a data-driven approach that utilizes machine learning techniques and a comprehensive dataset of vehicle parameters and environmental factors to create precise energy consumption prediction models. The methodology involves recording real-world vehicle data using data loggers to extract information from the CAN bus systems for ICE and hybrid electric, as well as hydrogen and battery fuel cell vehicles. Data cleaning and cycle-based analysis are employed to process the dataset for accurate energy consumption prediction. This includes cycle detection and analysis using methods from statistics and signal processing, and then pattern recognition based on these metrics.

Eigenvalues of a simple rotating flexible disk-shaft system are obtained using different methods. The shaft is supported radially by non-rigid bearings, while the disk is situated at one end of the shaft. Eigenvalues from a finite element and a multi-body dynamic tool are compared against an established analytical formulation. The Campbell diagram based on natural frequencies obtained from the tools differ from the analytical values because of oversimplification in the analytical model. Later, detailed whirl analysis is performed using AVL Excite multi-body tool that includes understanding forward and reverse whirls in absolute and relative coordinate systems and their relationships. Responses to periodic force and base excitations at a constant rotational speed of the shaft are obtained and a modified Campbell diagram based on this is developed. Whirl of the center of the disk is plotted as an orbital or phase plot and its rotational direction noted.

Gear profile deviation is the difference in gear tooth profile from the ideal involute geometry. There are many causes that result in the deviation. Deflection under load, manufacturing, and thermal effects are some of the well-known causes that have been reported to cause deviation of the gear tooth profile. The profile deviation caused by gear tooth profile deformation due to interference-fit assembly has not been discussed previously. Engine timing gear trains, transmission gearboxes, and wind turbine gearboxes are known to use interference-fit to attach the gear to the rotating shaft. This paper discusses the interference-fit joint design and the mechanism of tooth profile deformation due to the interference-fit assembly in gear trains. A new analytical method to calculate the profile slope deviation change due to interference-assembly of parallel axis spur gears is presented.

The goal of this interview analysis was to explore and document the perceptions of two unique lane centering systems (S90’s Pilot Assist and CT6’s Super Cruise). Both systems offer a similar type of functionality (adaptive cruise control and lane centering), but have significantly different design philosophies and HMI (Human-Machine Interface) implementations. Twenty-four drivers drove one of the two vehicle models for a month as part of a field operational test (FOT) study. Upon vehicle return, drivers took part in a 60-minute semi-structured interview covering their perceptions of the vehicle’s various advanced driver-assistance systems (ADAS). Transcripts of the interviews were coded by two researchers, who tagged each statement with relevant system and perception code labels. For analysis, the perception codes were grouped into larger thematic bins of safety, comfort, driver attention, and system performance.

This article reports on the potential of negative valve overlap (NVO) for improving the net indicated thermal efficiency (η NIMEP) of gasoline engines during part load. Three fixed fuel flow rates, resulting in indicated mean effective pressures of up to 6 bar, were investigated. At low load, NVO significantly reduces the pumping loses during the gas exchange loop, achieving up to 7% improvement in indicated efficiency compared to the baseline. Similar efficiency improvements are achieved by positive valve overlap (PVO), with the disadvantage of worse combustion stability from a higher residual gas fraction (xr). As the load increases, achieving the wide-open throttle limit, the benefits of NVO for reducing the pumping losses diminish, while the blowdown losses from early exhaust valve opening (EVO) increase.

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.

A new multi-scale curved beam based model was developed for piston-ring designs. This paper describes the free-shape, force in circular bore and closed shape within a flexible band (ovality) related parts. Knowing any one of these distributions, this model determines the other two. This tool is useful in the sense that the characterization of the ring is carried out by measuring its closed shape within a flexible band which is more accurate than measuring its free shape or force distribution in circular bore. Thus, having a model that takes the closed shape within a flexible band as an input is more convenient and useful based on the experiments carried out to characterize the ring.

This work examines the effect of valve timing during cold crank-start and cold fast-idle (1200 rpm, 2 bar NIMEP) on the emissions of hydrocarbons (HC) and particulate mass and number (PM/PN). Four different cam-phaser configurations are studied in detail: 1. Baseline stock valve timing. 2. Late intake opening/closing. 3. Early exhaust opening/closing. 4. Late intake phasing combined with early exhaust phasing. Delaying the intake valve opening improves the mixture formation process and results in more than 25% reduction of the HC and of the PM/PN emissions during cold crank-start. Early exhaust valve phasing results in a deterioration of the HC and PM/PN emissions performance during cold crank-start. Nevertheless, early exhaust valve phasing slightly improves the HC emissions and substantially reduces the particulate emissions at cold fast-idle.

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.

The Wankel rotary engine is more compact than conventional piston engines, but its oil and fuel consumption must be reduced to satisfy emission standards and customer expectations. A key step toward this goal is to develop a better understanding of the apex seal lubrication to reduce oil injection while reducing friction and maintaining adequate wear. This paper presents an apex seal dynamics model capable of estimating relative wear and predicting friction, by modeling the gas and oil flows at the seal interfaces with the rotor housing and groove flanks. Model predictions show that a thin oil film can reduce wear and friction, but to a limited extent as the apex seal running face profile is sharp due to the engine kinematics.

The rotary engine provides high power density compared to piston engine, but one of its downside is higher oil consumption. A model of the oil seals is developed to calculate internal oil consumption (oil leakage from the crankcase through the oil seals) as a function of engine geometry and operating conditions. The deformation of the oil seals trying to conform to housing distortion is calculated to balance spring force, O-ring and groove friction, and asperity contact and hydrodynamic pressure at the interface. A control volume approach is used to track the oil over a cycle on the seals, the rotor and the housing as the seals are moving following the eccentric rotation of the rotor. The dominant cause of internal oil consumption is the non-conformability of the oil seals to the housing distortion generating net outward scraping, particularly next to the intake and exhaust port where the housing distortion valleys are deep and narrow.

The rotary engine provides high power density compared to piston engine, but one of its downside is higher oil consumption. In order to better understand oil transport, a laser induced fluorescence technique is used to visualize oil motion on the side of the rotor during engine operation. Oil transport from both metered oil and internal oil is observed. Starting from inside, oil accumulates in the rotor land during inward motion of the rotor created by its eccentric motion. Oil seals are then scraping the oil outward due to seal-housing clearance asymmetry between inward and outward motion. Cut-off seal does not provide an additional barrier to internal oil consumption. Internal oil then mixes with metered oil brought to the side of the rotor by gas leakage. Oil is finally pushed outward by centrifugal force, passes the side seals, and is thrown off in the combustion chamber.

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.

The fuel energy consumption of subsonic air transportation is examined. The focus is on identification and quantification of fundamental engineering design tradeoffs which drive the design of subsonic tube and wing transport aircraft. The sensitivities of energy efficiency to recent and forecast technology developments are also examined.

The aim of this study was to explore if fingernail delamination injury following EMU glove use may be caused by compression-induced blood flow occlusion in the finger. During compression tests, finger blood flow decreased more than 60%, however this occurred more rapidly for finger pad compression (4 N) than for fingertips (10 N). A pressure bulb compression test resulted in 50% and 45% decreased blood flow at 100 mmHg and 200 mmHg, respectively. These results indicate that the finger pad pressure required to articulate stiff gloves is more likely to contribute to injury than the fingertip pressure associated with tight fitting gloves.

The windage tray effect on aeration in the engine sump was assessed by replacing much of the windage tray materials with wire meshes of various blockages. The mesh was to prevent direct impact of the oil drops spinning off the crank shaft onto the sump oil, and simultaneously, to provide sufficient drainage so that there was no significant build up of windage tray oil film that would interact with these droplets. Aeration at the oil pump inlet was measured by X-ray absorption in a production V-6 SI engine motoring at 2000 to 6000 rpm. Within experimental uncertainty, these windage tray changes had no effect on aeration. Thus activities in the sump such as the interaction of the oil drops spun from the crank shaft with the sump oil or with the windage tray, and the agitation of the sump oil by the crank case gas, were not major contributors to aeration at the pump inlet.

The nearly 77 million baby boomers, born between 1946 and 1964, can say that they are the automobile generation. Now turning 60 one every seven seconds, what are the new safety challenges and opportunities posed by the next generation of older adults? This paper presents a modified Haddon matrix to identify key product development, design and liability issues confronting the automobile industry and related stakeholders. The industry is now at a critical juncture to address the development of key technological innovations as well as the changing policy and liability environments being reshaped by an aging population.

Rotary valves should pose a credible threat to other mechanical valve systems-such as poppet valves-but they have been unable to infiltrate the automotive market. Using Axiomatic Design we have identified significant design problems with existing rotary valves which have prevented their wide-spread use. In addition, we have proposed an innovative solution which removes some couplings in existing rotary valve systems and could potentially be used in automotive applications, although further work must still be performed.