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Often, when assessing the distraction or ease of use of an in-vehicle task (such as entering a destination using the street address method), the first question is “How long does the task take on average?” Engineers routinely resolve this question using computational models. For in-vehicle tasks, “how long” is estimated by summing times for the included task elements (e.g., decide what to do, press a button) from SAE Recommended Practice J2365 or now using new static (while parked) data presented here. Times for the occlusion conditions in J2365 and the NHTSA Distraction Guidelines can be determined using static data and Pettitt’s Method or Purucker’s Method. These first approximations are reasonable and can be determined quickly. The next question usually is “How likely is it that the task will exceed some limit?”

In-vehicle infotainment (IVI) platforms are getting increasingly connected. Besides OEM apps and services, the next generation of IVI platforms are expected to offer integration of third-party apps. Under this anticipated business model, vehicular sensor and event data can be collected and shared with selected third-party apps. To accommodate this trend, Google has been pushing towards standardization among proprietary IVI operating systems with their Android Automotive platform which runs natively on the vehicle’s IVI platform. Unlike Android Auto’s limited functionality of display-projecting certain smartphone apps to the IVI screen, Android Automotive will have access to the in-vehicle network (IVN), and will be able to read and share various vehicular sensor data with third-party apps. This increased connectivity opens new business opportunities for both the car manufacturer as well as third-party businesses, but also introduces a new attack surface on the vehicle.

Privacy has been a rising concern. The European Union has established a privacy standard called General Data Protection Regulation (GDPR) in May 2018. Furthermore, the Facebook-Cambridge Analytica data incident made headlines in March 2018. Data collection from vehicles by OEM platforms is increasingly popular and may offer OEMs new business models but it comes with the risk of privacy leakages. Vehicular sensor data shared with third-parties can lead to misuse of the requested data for other purposes than stated/intended. There exists a relevant regulation document introduced by the Alliance of Automobile Manufacturers (“Auto Alliance”), which classifies the vehicular sensors used for data collection as covered and non-sensitive parameters.

This presentation is an assessment of the turbulence-stress scale-similarity in an IC engine, which is used for modeling subgrid dissipation in LES. Residual stresses and Leonard stresses were computed after applying progressively smaller spatial filters to measured and simulated velocity distributions. The velocity was measured in the TCC-II engine using planar and stereo PIV taken in three different planes and with three different spatial resolutions, thus yielding two and three velocity components, respectively. Comparisons are made between the stresses computed from the measured velocity and stress computed from the LES resolved-scale velocity from an LES simulation. The results present the degree of similarity between the residual stresses and the Leonard stresses at adjacent scales. The specified filters are systematically reduced in size to the resolution limits of the measurements and simulation.

A primary goal of large eddy simulation, LES, is to capture in-cylinder cycle-to-cycle variability, CCV. This is a first step to assess the efficacy of 35 consecutive computed motored cycles to capture the kinetic energy in the TCC-III engine. This includes both the intra-cycle production and dissipation as well as the kinetic energy CCV. The approach is to sample and compare the simulated three-dimensional velocity equivalently to the available two-component two-dimensional PIV velocity measurements. The volume-averaged scale-resolved kinetic energy from the LES is sampled in three slabs, which are volumes equal to the two axial and one azimuthal PIV fields-of-view and laser sheet thickness. Prior to the comparison, the effects of sampling a cutting plane versus a slab and slabs of different thicknesses are assessed. The effects of sampling only two components and three discrete planar regions is assessed.

Over half of the greenhouse gas (GHG) emissions in the United States come from the transportation and electricity generation sectors. To analyze the potential impact of cross-sector cooperation in reducing these emissions, we formulate a bi-level optimization model where the transportation sector can purchase renewable energy certificates (REC) from the electricity generation sector. These RECs are used to offset emissions from transportation in lieu of deploying high-cost fuel efficient technologies. The electricity generation sector creates RECs by producing additional energy from renewable sources. This additional renewable capacity is financed by the transportation sector and it does not impose additional cost on the electricity generation sector. Our results show that such a REC purchasing regime significantly reduces the cost to society of reducing GHG emissions. Additionally, our results indicate that a REC purchasing policy can create electricity beyond actual demand.

Ball nut assemblies (BNAs) are used in a variety of applications, e.g., automotive, aerospace and manufacturing, for converting rotary motion to linear motion (or vice versa). In these application areas, accurate characterization of the dynamics of BNAs using low-order models is very useful for performance simulation and analyses. Existing low-order contact load models of BNAs are inadequate, partly because they only consider the axial deformations of the screw and nut. This paper presents a low-order load distribution model for BNAs which considers the axial, torsional and lateral deformations of the screw and nut. The screw and nut are modeled as finite element beams, while Hertzian Contact Theory is used to model the contact condition between the balls and raceways of the screw and nut. The interactions between the forces and displacements of the screw and nut and those at the ball-raceway contact points are established using transformation matrices.

With increasingly stringent light duty particulate emissions regulations, it is of great interest to better understand particulate matter formation. Helping to build the knowledge base for a thorough understanding of particulate matter formation will be an essential step in developing effective control strategies. It is especially important to do this in such a way as to emulate real driving behaviors, including cold starts and transients. To this end, this study examined particulate emissions during transient operation in a recent model year vehicle equipped with a GDI engine. Three of the major federal test cycles were selected as evaluation schemes: the FTP, the HWFET, and the US06. These cycles capture much of the driving behaviors likely to be observed in typical driving scenarios. Measurements included particle size distributions from a TSI EEPS fast-response particle spectrometer, as well as real-time soot emissions from an AVL MSS soot sensor.

Mahalanobis Distance (MD) is gaining momentum in many fields where classification, statistical pattern recognition, and forecasting are primary focus. It is a multivariate method and considers correlation relationships among parameters for computing generalized distance measure to separate groups or populations. MD is a useful statistic in multivariate analysis to test that an observed random sample is from a multivariate normal distribution. This capability alone enables engineers to determine if an observed sample is an outlier (defect) that falls outside the constructed (good) multivariate normal distribution. In Mahalanobis-Taguchi System (MTS), MD is suitably scaled and used as a measure of severity in abnormality assessment. It is obvious that computed MD depends on values of parameters observed on a random sample. All parameters may not equally impact MD. MD could be highly sensitive with respect to some parameters and less sensitive to some other parameters.

In automotive noise control, the hood liner is an important acoustic part for mitigating engine noise. The random incidence absorption coefficient is used to quantify the component level acoustic performance. Generally, air gaps, type of substrate materials, density of the substrate materials and Air Flow Resistivity (AFR) of the cover scrim are the dominant control factors in the sound absorption performance. This paper describes a systematic experimental investigation of how these control factors affect flat sample performance. The first stage of this study is full factorial measurement based on current available solutions from sound absorber suppliers. The acoustic absorption of different hood liner constructions, with variations in materials, density, air gaps, and scrims was measured.

Rapidly increasing customer, financial, and regulatory pressures are creating clear changes in the calculus of vehicle design for modern automotive OEM's (Original Equipment Manufacturers). Customers continue to demand shorter product lifecycles; the increasingly competitive global market exerts pressure to reduce costs in all stages of development; and environmental regulations drive a continuous need to reduce mass and energy consumption. OEM's must confront these challenges while continuing to satisfy the customer. The foundation to meeting these challenges includes: (1) Continued development of objective metrics to quantify performance; (2) Frontloading vehicle design content and performance synthesis; (3) A precise understanding of the customer and their performance preferences under diverse usage conditions. These combined elements will enable products better optimized amongst competing (and often contradictory) imperatives.

Emission compliance at the production level has been a challenge for vehicle manufacturers. Diesel oxidation catalyst (DOC) plays a very important role in controlling the emissions for the diesel vehicles. Vehicle manufacturers tend to ‘over design’ the diesel oxidation catalyst to ‘absorb’ the production variations which seems an easier and faster solution. However this approach increases the DOC cost phenomenally which impacts the overall vehicle cost. The main objective of this paper is to address the high variation in CO tail pipe emissions which were observed on a diesel passenger car during development. This variation was posing a challenge in consistently meeting the internal product requirement/specification.

This study documented the position and orientation of child restraint systems (CRS) installed in the second rows of vehicles, creating a database of 486 installations. Thirty-one different CRS were evaluated, selected to provide a range of manufacturers, sizes, types, and weight limits. Eleven CRS were rear-facing only, fourteen were convertibles, five were combination restraints, and one was a booster. Ten top-selling vehicles were selected to provide a range of manufacturers and body styles: four sedans, four SUVS, one minivan, and one wagon. CRS were marked with three reference points on each moving component. The contours and landmarks of each CRS were first measured in the laboratory. Vehicle interior contours, belt anchors, and LATCH anchors were measured using a similar process. Then each CRS was installed in a vehicle using LATCH according to manufacturers' directions, and the reference points of each CRS component were measured to document the installed orientation.

This study was designed to investigate how the spectral power distribution (SPD) of LED headlamps (including correlated color temperature, CCT) affects both objective driving performance and subjective responses of drivers. The results of this study are not intended to be the only considerations used in choosing SPD, but rather to be used along with results on how SPD affects other considerations, including visibility and glare. Twenty-five subjects each drove 5 different headlamps on each of 5 experimental vehicles. Subjects included both males and females, in older (64 to 85) and younger (20 to 32) groups. The 5 headlamps included current tungsten-halogen (TH) and high-intensity discharge (HID) lamps, along with three experimental LED lamps, with CCTs of approximately 4500, 5500, and 6500 K. Driving was done at night on public roads, over a 21.5-km route that was selected to include a variety of road types.

Available methodologies for model bias identification are mainly regression-based approaches, such as Gaussian process, Bayesian inference-based models and so on. Accuracy and efficiency of these methodologies may degrade for characterizing the model bias when more system inputs are considered in the prediction model due to the curse of dimensionality for regression-based approaches. This paper proposes a copula-based approach for model bias identification without suffering the curse of dimensionality. The main idea is to build general statistical relationships between the model bias and the model prediction including all system inputs using copulas so that possible model bias distributions can be effectively identified at any new design configurations of the system. Two engineering case studies whose dimensionalities range from medium to high will be employed to demonstrate the effectiveness of the copula-based approach.

With the ever increasing pressure to improve the fuel economy of vehicles, there has been a corresponding interest in reducing the mass and size of vehicles. While mass is easily quantifiable, vehicle size, particularly the notion of “interior space” as perceived by the customer, is not. This paper explores different ways in which vehicle spaciousness can be quantified and explores new metrics based on customer verbatims. A novel ‘spaciousness calculator’ combines individual metrics to provide a singular holistic rating for spaciousness, useful during vehicle development. Beyond spaciousness, the paper discusses techniques to quantify the ‘packaging efficiency’ of a vehicle; this allows engineers to maximize the interior space for a given exterior size.

AUTOSAR(AUTomotive Open System ARchitecture) establishes an industry standard for OEMs and the supply chain to manage growing complexity to the automotive electronics domain. Increased focus on software based features will prove to be a key differentiator between vehicle platforms. AUTOSAR serves to standardize automotive serial data communication protocols, interaction with respect to hardware peripherals within an ECU and allow ECU implementer to focus on development of unique customer focused features that distinguish product offerings. Adoption strategy and impact assessment associated with leveraging AUTOSAR for an E/E Architecture and the potential challenges that need to be considered will be described in this publication. This publication will also illustrate development strategies that need to be considered w.r.t deploying AUTOSAR like data exchange, consistency to BSW software implementation, MCAL drivers etc.

Discuss the basics of posturing and positioning of the full range of occupants necessary to cover the required anthropometric demographics in combat vehicles, both ground and air, since there are similarities to both and that they are both very different than the traditional automotive packaging scenarios. It is based on the Eye Reference Point and the Design Eye Point. Discuss the three Reach Zones: Primary, Secondary and Tertiary. Discuss Vision Zones and potentially ground intercepts. Discuss body clearances, both static and dynamic. Discuss the basic effects of packaging occupants with body armor with respect to SRP's and MSRP's.

Refinements were made to a post-processing technique, termed the Thermal Stratification Analysis (TSA), that couples the mass fraction burned data to ignition timing predictions from the autoignition integral to calculate an apparent temperature distribution from an experimental HCCI data point. Specifically, the analysis is expanded to include all of the mass in the cylinder by fitting the unburned mass with an exponential function, characteristic of the wall-affected region. The analysis-derived temperature distributions are then validated in two ways. First, the output data from CFD simulations are processed with the Thermal Stratification Analysis and the calculated temperature distributions are compared to the known CFD distributions.

In the vehicle development process, one important step is to set a component performance target from the vehicle level performance. Conventional barrier-decoupler dash mats and floor trim underlayment systems typically provide sound transmission loss (STL) with minimal absorption. Thus the performance of such components can be relatively easily specified as either STL or Insertion Loss. Lightweight dissipative or multi-layered acoustic materials provide both STL and significant absorption. The net performance is a combination of two parameters instead of one. The target for such components needs to account for this combined effect, however different suppliers use unique formulations and manufacturing methods, so it is difficult and time consuming to judge one formulation against another. In this paper, a unique process is presented to set a component target as a combined effect of STL and absorption.