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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.

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.

Topology of liner finish is critical to the performance of internal combustion engines. Proper liner finish simulation processes lead to efficient engine design and research. Fourier methods have been well studied to numerically generate liner topology. However, three major issues wait to be addressed to make the generation processes feasible and reliable. First, in order to simulate real plateau honed liners, approaches should be developed to calculate accurate liner geometric parameters. These parameters are served as the input of the generation algorithm. Material ratio curve, the common geometry calculation method, should be modified so that accurate root mean square of plateau height distribution could be obtained. Second, the set of geometric parameters used in generating liner finish (ISO 13565-2) is different from the set of parameters used in manufacturing industry (ISO 13565-3). Quantitative relations between these two sets should be studied.

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.

A new multi-scale curved beam based model was developed for piston-ring designs. This tool is able to characterize the behavior of a ring with any cross section design. This paper describes the conformability and ring static twist calculation. The conformability part model the static behavior of the ring in working engine conditions. The model employs the computation scheme that separates the meshing of the structure and local force generation. Additional to the conventional static ring-bore conformability analysis, the conformability model is designed to examine ring-bore and ring-groove interactions in a running engine under varying driving forces and localized lubrication conditions. We made Improvements on the way to handle the effects of the radial temperature gradient compared to the existing models. Examples are given on the effects of ring rotation on the interaction of the ring and a distorted bore as well as the change of local lubrication conditions.

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.

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.

A new ring pack model has been developed based on the curved beam finite element method. This paper describes the first part of this model: simulating gas pressure in different regions above piston skirt and ring dynamic behavior of two compression rings and a twin-land oil control ring. The model allows separate grid divisions to resolve ring structure dynamics, local force/pressure generation, and gas pressure distribution. Doing so enables the model to capture both global and local processes at their proper length scales. The effects of bore distortion, piston secondary motion, and groove distortion are considered. Gas flows, gas pressure distribution in the ring pack, and ring structural dynamics are coupled with ring-groove and ring-liner interactions, and an implicit scheme is employed to ensure numerical stability. The model is applied to a passenger car engine to demonstrate its ability to predict global and local effects on ring dynamics and oil transport.

The piston skirt is an important contributor of friction in the piston assembly. This paper discusses friction contributions from various aspects of the piston skirt. A brief study of piston skirt patterns is presented, with little gains being made by patterning the piston skirt coating. Next the roughness of the piston skirt coating is analyzed, and results show that reducing piston skirt roughness can have positive effects on friction reduction. Finally, an introductory study into the profile of the piston skirt is presented, with the outcome being that friction reduction is possible by optimizing the skirt profile.

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

Rare earths are a group of elements whose availability has been of concern due to monopolistic supply conditions and environmentally unsustainable mining practices. To evaluate the risks of rare earths availability to automakers, a first step is to determine raw material content and value in vehicles. This task is challenging because rare earth elements are used in small quantities, in a large number of components, and by suppliers far upstream in the supply chain. For this work, data on rare earth content reported by vehicle parts suppliers was assessed to estimate the rare earth usage of a typical conventional gasoline engine midsize sedan and a full hybrid sedan. Parts were selected from a large set of reported parts to build a hypothetical typical mid-size sedan. Estimates of rare earth content for vehicles with alternative powertrain and battery technologies were made based on the available parts' data.

In today's highly competitive automotive markets manufacturers must provide high quality products to survive. Manufacturers can achieve higher levels of quality by changing or improving their manufacturing process and/or by product inspection where many strategies with different cost implications are often available. Cost of Quality (CoQ) reconciles the competing objectives of quality maximization and cost minimization and serves as a useful framework for comparing available manufacturing process and inspection alternatives. In this paper, an analytic CoQ framework is discussed and some key findings are demonstrated using a set of basic inspection strategy scenarios. A case of a welded automotive assembly is chosen to explore the CoQ tradeoffs in inspection strategy selection and the value of welding process improvement. In the assembly process, many individual components are welded in series and each weld is inspected for quality.

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 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.

One of the issues in stamping of advanced high strength steels (AHSS) is the stretch bending fracture on a sharp radius (commonly referred to as shear fracture). Shear fracture typically occurs at a strain level below the conventional forming limit curve (FLC). Therefore it is difficult to predict in computer simulations using the FLC as the failure criterion. A modified Mohr-Coulomb (M-C) fracture criterion has been developed to predict shear fracture. The model parameters for several AHSS have been calibrated using various tests including the butter-fly shaped shear test. In this paper, validation simulations are conducted using the modified (M-C) fracture criterion for a dual phase (DP) 780 steel to predict fracture in the stretch forming simulator (SFS) test and the bending under tension (BUT) test. Various deformation fracture modes are analyzed, and the range of usability of the criterion is identified.

Battery packs for Hybrids, Plug-in Hybrids, and Electric Vehicles are assembled from a system of modules (sheets) with a tight sheet metal casing around them. Each module consists of an array of individual cells which vary in the composition of electrodes and separator from one manufacturer to another. In this paper a general procedure is outlined on the development of a constitutive and computational model of a cylindrical cell. Particular emphasis is placed on correct prediction of initiation and propagation of a tearing fracture of the steel can. The computational model correctly predicts rupture of the steel can which could release aggressive chemicals, fumes, or spread the ignited fire to the neighboring cells. The initiation site of skin fracture depends on many factors such as the ductility of the casing material, constitutive behavior of the system of electrodes, and type of loading.

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.