Search Results

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.

Knock in gasoline engines at higher loads is a significant constraint on torque and efficiency. The anti-knock property of a fuel is closely related to its research octane number (RON). Ethanol has superior RON compared to gasoline and thus has been commonly used to blend with gasoline in commercial gasolines. However, as the RON of a fuel is constant, it has not been used as needed in a vehicle. To wisely use the RON, an On-Board Separation (OBS) unit that separates commercial gasoline with ethanol content into high-octane fuel with high ethanol fraction and a lower octane remainder has been developed. Then an onboard Octane-on-demand (OOD) concept uses both fuels in varying proportion to provide to the engine a fuel blend with just enough RON to meet the ever changing octane requirement that depends on driving pattern.

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 paper describes a post-race analysis of team KOMMIT EVT’s electric motorcycle data collected during the 2016 Pikes Peak International Hill Climb (PPIHC). The motorcycle consumed approximately 4 kWh of battery energy with an average and maximum speed of 107 km/h and 149 km/h, respectively. It was the second fastest electric motorcycle with a finishing time of 11:10.480. Data was logged of the motorcycle’s speed, acceleration, motor speed, power, currents, voltages, temperatures, throttle position, GPS position, rider’s heart rate and the ambient environment (air temperature, pressure and humidity). The data was used to understand the following factors that may have prevented a faster time: physical fitness of the rider, thermal limits of the motor and controller, available battery energy and the sprocket ratio between the motor and rear wheel.

Selective catalytic reduction (SCR) of nitrogen oxides (NOx) is used in diesel-fueled mobile applications where urea is an added reducing agent. We show that the Ultera® dual-stage catalyst, with intercooling aftertreatment system, intrinsically performs the function of the SCR method in nominally stoichiometric gasoline vehicle engines without the need for an added reductant. We present that NOx is reduced during the low-temperature operation of the dual-stage system, benefiting from the typically periodic transient operation (acceleration and decelerations) with the associated swing in the air/fuel ratio (AFR) inherent in mobile applications, as commonly expected and observed in real driving. The primary objective of the dual-stage aftertreatment system is to remove non-methane organic gases (NMOG) and carbon monoxide (CO) slip from the vehicle’s three-way catalyst (TWC) by oxidizing these constituents in the second stage catalyst.

The Cu-zeolite (CuZ) SCR catalyst enables higher NOx conversion efficiency in part because it can store a significant amount of NH3. “NH3 storage control”, where diesel exhaust fluid (DEF) is dosed in accord with a target NH3 loading, is widely used with CuZ catalysts to achieve very high efficiency. The NH3 loading actually achieved on the catalyst is currently estimated through a stoichiometric calculation. With future high-capacity CuZ catalyst designs, it is likely that the accuracy of this NH3 loading estimate will become limiting for NOx conversion efficiency. Therefore, a direct measurement of NH3 loading is needed; RF sensing enables this. Relative to RF sensing of soot in a DPF (which is in commercial production), RF sensing of NH3 adsorbed on CuZ is more challenging. Therefore, more attention must be paid to the “microwave resonance cavity” created within the SCR assembly. The objective of this study was to develop design guidelines to enable and enhance RF sensing.

To meet future particle mass and particle number standards, gasoline vehicles may require particle control, either by way of an exhaust gas filter and/or engine modifications. Soot levels for gasoline engines are much lower than diesel engines; however, non-combustible material (ash) will be collected that can potentially cause increased backpressure, reduced power, and lower fuel economy. The purpose of this work was to examine the ash loading of gasoline particle filters (GPFs) during rapid aging cycles and at real time low mileages, and compare the filter performances to both fresh and very high mileage filters. Current rapid aging cycles for gasoline exhaust systems are designed to degrade the three-way catalyst washcoat both hydrothermally and chemically to represent full useful life catalysts. The ash generated during rapid aging was low in quantity although similar in quality to real time ash. Filters were also examined after a low mileage break-in of approximately 3000 km.

The increasing use of gasoline direct injection (GDI) engines coupled with the implementation of new particulate matter (PM) and particle number (PN) emissions regulations requires new emissions control strategies. Gasoline particulate filters (GPFs) present one approach to reduce particle emissions. Although primarily composed of combustible material which may be removed through oxidation, particle also contains incombustible components or ash. Over the service life of the filter the accumulation of ash causes an increase in exhaust backpressure, and limits the useful life of the GPF. This study utilized an accelerated aging system to generate elevated ash levels by injecting lubricant oil with the gasoline fuel into a burner system. GPFs were aged to a series of levels representing filter life up to 150,000 miles (240,000 km). The impact of ash on the filter pressure drop and on its sensitivity to soot accumulation was investigated at specific ash levels.

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 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

Piston rings are large contributors to friction losses in internal combustion engines. To achieve higher engine efficiency, low friction ring packs that can maintain good sealing performance must be designed. To support this effort, simulation tools have been developed to model the performance of piston rings during engine operation. However, the challenge of predicting oil consumption, blow by, and ring pack friction with sufficient accuracy remains. This is mostly due to the complexity of this system. Ring dynamics, deformation, interaction with liner and piston, gas and lubricant flow must all be studied together to make relevant predictions. In this paper, a new curved beam finite element model of piston rings is proposed. Ring structural deformation and contact with the liner are treated on two separate grids. A comparison with ring models in the literature and analytical solutions shows that it can provide accurate results efficiently.

1 Downsizing and turbocharging a spark-ignited engine is becoming an important strategy in the engine industry for improving the efficiency of gasoline engines. Through boosting the air flow, the torque is increased, the engine can thus be downsized, engine friction is reduced in both absolute and relative terms, and engine efficiency is increased. However knock onset with a given octane rating fuel limits both compression ratio and boost levels. This paper explores the operating limits of a turbocharged engine, with various gasoline-ethanol blends, and the interaction between compression ratio, boost levels, and spark retard, to achieve significant increases in maximum engine mean effective pressure and efficiency.

Diesel particulate filters (DPF) are a common component in emission-control systems of modern clean diesel vehicles. Several DPF materials have been used in various applications. Silicone Carbide (SiC) is common for passenger vehicles because of its thermal robustness derived from its high specific gravity and heat conductivity. However, a segmented structure is required to relieve thermal stress due to SiC's higher coefficient of thermal expansion (CTE). Cordierite (Cd) is a popular material for heavy-duty vehicles. Cordierite which has less mass per given volume, exhibits superior light-off performance, and is also adequate for use in larger monolith structures, due to its lower CTE. SiC and cordierite are recognized as the most prevalent DPF materials since the 2000's. The DPF traps not only combustible particles (soot) but also incombustible ash. Ash accumulates in the DPF and remains in the filter until being physically removed.

The effects of cooled exhaust gas recirculation (EGR) on a boosted direct-injection (DI) spark ignition (SI) engine operating at stoichiometric equivalence ratio, gross indicated mean effective pressure of 14-18 bar, and speed of 1500-2500 rpm, are studied under constant fuel condition at each operating point. In the presence of EGR, burn durations are longer and combustion is more retard. At the same combustion phasing, the indicated specific fuel consumption improves because of a decrease in heat loss and an increase in the specific heat ratio. The knock limited spark advance increases substantially with EGR. This increase is due partly to a slower combustion which is equivalent to a spark retard, as manifested by a retarded value of the 50% burn point (CA50), and due partly to a slower ignition chemistry of the diluted charge, as manifested by the knock limited spark advance to beyond the value offered by the retarded CA50.

The accumulation of soot and lubrication-derived ash particles in a diesel particulate filter (DPF) increases exhaust flow restriction and negatively impacts engine efficiency. Previous studies have described the macroscopic phenomenon and general effects of soot and ash accumulation on filter pressure drop. In order to enhance the fundamental understanding, this study utilized a novel apparatus that of a dual beam scanning electron microscope (SEM) and focused ion beam (FIB), to investigate microscopic details of soot and ash accumulation in the DPF. Specifically, FIB provides a minimally invasive technique to analyze the interactions between the soot, ash, catalyst/washcoat, and DPF substrate with a high degree of measurement resolution. The FIB utilizes a gallium liquid metal ion source which produces Ga+ ions of sufficient momentum to directionally mill away material from the soot, ash, and substrate layers on a nm-μm scale.

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.

An experimental study was performed to develop a more fundamental understanding of the effects of secondary air injection (SAI) on exhaust gas emissions and catalyst light-off characteristics during cold start of a modern SI engine. The effects of engine operating parameters and various secondary air injection strategies such as spark retardation, fuel enrichment, secondary air injection location and air flow rate were investigated to understand the mixing, heat loss, and thermal and catalytic oxidation processes associated with SAI. Time-resolved HC, CO and CO₂ concentrations were tracked from the cylinder exit to the catalytic converter outlet and converted to time-resolved mass emissions by applying an instantaneous exhaust mass flow rate model. A phenomenological model of exhaust heat transfer combined with the gas composition analysis was also developed to define the thermal and chemical energy state of the exhaust gas with SAI.

The high load limit of a boosted homogeneous-charge-compression-ignition (HCCI) engine operating on negative-valve-overlap (NVO) was assessed. When operating under stoichiometric condition with no external dilution, the load, as measured by the net indicated mean effective pressure (NIMEP), increased with increase in manifold absolute pressure (MAP), and with decrease in trapped amount of residual gas. The maximum pressure rise rate (MPRR), however, also increased correspondingly. When the MAP and the amount of residual gas were adjusted so that the engine operating point could be held at a constant MPRR value, the NIMEP increased with the simultaneous decrease in MAP and residual until the misfire limit was reached. Therefore if a MPRR ceiling is imposed, the high load limit of an HCCI engine is at the intersection of the constraining MPRR line and the misfire line.