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The rise of Software-Defined Vehicles (SDV) has rapidly advanced the development of Advanced Driver Assistance Systems (ADAS), Autonomous Vehicle (AV), and Battery Electric Vehicle (BEV) technology. While AVs need power to compute data from perception to controls, BEVs need the efficiency to optimize their electric driving range and stand out compared to traditional Internal Combustion Engine (ICE) vehicles. AVs possess certain shortcomings in the current world, but SAE Level 2+ (L2+) Automated Vehicles are the focus of all major Original Equipment Manufacturers (OEMs). The most common form of an SDV today is the amalgamation of AV and BEV technology on the same platform which is prominently available in most OEM’s lineups. As the compute and sensing architectures for L2+ automated vehicles lean towards a computationally expensive centralized design, it may hamper the most important purchasing factor of a BEV, the electric driving range.

Driver Assistance and Autonomous Driving features are becoming nearly ubiquitous in new vehicles. The intent of the Driver Assistant features is to assist the driver in making safer decisions. The intent of Autonomous Driving features is to execute vehicle maneuvers, without human intervention, in a safe manner. The overall goal of Driver Assistance and Autonomous Driving features is to reduce accidents, injuries, and deaths with a comforting driving experience. However, different drivers can react differently to advanced automated driving technology. It is therefore important to consider and improve the adaptability of these advances based on driver behavior. In this paper, a human-centric approach is adopted to provide an enriching driving experience. We perform data analysis of the naturalistic behavior of drivers when performing lane change maneuvers by extracting features from extensive Second Strategic Highway Research Program (SHRP2) data of over 5,400,000 data files.

Rapid adoption of battery electric vehicles means improving the energy consumption and energy efficiency of these new vehicles is a top priority. One method of accomplishing this is regenerative braking, which converts kinetic energy to electrical energy stored in the battery pack while the vehicle is decelerating. Coasting is an alternative strategy that minimizes energy consumption by decelerating the vehicle using only road load. A battery electric vehicle model is refined to assess regenerative braking, coasting, and other deceleration strategies. A road load model based on public test data calculates tractive effort requirements based on speed and acceleration. Bidirectional Willans lines are the basis of a powertrain model simulating battery energy consumption. Vehicle tractive and powertrain power are modeled backward from prescribed linear velocity curves, and the coasting trajectory is forward modeled given zero tractive power.

Structural Health Monitoring (SHM), especially in the field of rotary machinery diagnosis, plays a crucial role in determining the defect category as well as its intensity in a machine element. This paper proposes a new framework for real-time classification of structural defects in a roller bearing test rig using time domain-based classification algorithms. Along with the bearing defects, the effect of eccentric shaft loading has also been analyzed. The entire system comprises of three modules: sensor module – using accelerometers for data collection, data processing module – using time-domain based signal processing algorithms for feature extraction, and classification module – comprising of deep learning algorithms for classifying between different structural defects occurring within the inner and outer race of the bearing.

The significance and the number of vehicle safety features enabled via connectivity continue to increase. OnStar, with its automatic airbag notification, was one of the first vehicle safety features that demonstrate the enhanced safety benefits of connectivity. Vehicle connectivity benefits have grown to include remote software updates, data analytics to aid with preventative maintenance and even to theft prevention and recovery. All of these services require available and reliable connectivity. However, except for the airbag notification, none have strict latency requirements. For example, software updates can generally be postponed till reliable connectivity is available. Data required for prognostic use cases can be stored and transmitted at a later time. A new set of use cases are emerging that do demand continuous, reliable and low latency connectivity. For example, remote control of autonomous vehicles may be required in unique situations.

A new and unique electric vehicle powertrain model based on bidirectional power flow for propel and regenerative brake power capture is developed and applied to production battery electric vehicles. The model is based on a Willans line model to relate power input from the battery and power output to tractive effort, with one set of parameters (marginal efficiency and an offset loss) for the bidirectional power flow through the powertrain. An electric accessory load is included for the propel, brake and idle phases of vehicle operation. In addition, regenerative brake energy capture is limited with a regen fraction (where the balance goes to friction braking), a power limit, and a low-speed cutoff limit. The purpose of the model is to predict energy consumption and range using only tractive effort based on EPA published road load and test mass (test car list data) and vehicle powertrain parameters derived from EPA reported unadjusted UDDS and HWFET energy consumption.

Four crash modes are overrepresented in traffic fatalities: run-off-road crashes, non-tracking run-off-road crashes, head-on crashes, and pedestrian crashes. Two advanced driver assist systems developed to help prevent tracking run-off-road crashes and head-on crashes are lane departure warning (LDW) and lane keeping assist (LKA). LDW acts to warn the driver when they are encroaching the lane boundary, whereas LKA performs automatic steering to prevent the vehicle from departing the lane. The objective of this research was to use real-world crash data to estimate current LDW and LKA system effectiveness in reducing run-off-road crashes and cross-centerline head-on crashes. All passenger vehicles that experienced a lane departure from 2017 to 2019 in the Crash Investigation Sampling System (CISS) were analyzed.

One of the biggest challenges for mobility engineers today is the reduction of fuel consumption while keeping or even improving the automobiles propulsion system performance. A great part of the current powertrain components is developed to work at high engine loads and extreme environmental conditions, among which the engine cooling system, for example. As the overall vehicle efficiency depends directly on the thermal system design, it is important to make a careful investigation of the external ambient to develop this system on the best possible way, seeking to minimize the negative impacts at normal driving situations, which represents the most of the vehicle's life cycle. In this regard, the present paper reports a numerical study about the impacts of different cooling system hardware configurations on the fuel consumption of a turbocharged flex-fuel engine.

Vehicle headlamps and roadway lighting are the major sources of illumination at night. These sources affect contrast - defined as the luminance difference of an object from its background - which drives visibility at night. However, the combined effect of vehicle headlamps and intersection lighting on object contrast has not been reported previously. In this study, the interactive effects of vehicle headlamps and overhead lighting on object contrast were explored based on earlier work that examined drivers’ visibility under three intersection lighting designs (illuminated approach, illuminated box, and illuminated approach + box). The goals of this study were to: 1) quantify object luminance and contrast as a function of a vehicle’s headlamps and its distance to an intersection using the three lighting designs; and, 2) to assess whether contrast influences visual performance and perceived visibility in a highly dynamic intersection environment.

Diesel engines have been used on the aeronautical market for a long time. Despite this fact, there are few studies showing the potential cost savings of using this type of technology. In this way, the goal of this paper is to find out whether or not it is advantageous to use an Otto or Diesel cycle engine on general aviation light aircraft. It is well known that both of them have pros and cons, however, the possibility of using Jet A-1 (kerosene) as fuel gives the Diesel engine a clear advantage in a market like Brazil, where the price of the regular piston fuel (AvGas) keeps rising to astonishing values. Throughout this paper, a detailed study of the fixed and variable costs of two similar aircraft, both Cessnas 172 equipped with Otto and Diesel cycle engines is conducted, comparing fuel consumption, performance levels, and other factors.

Intersection collisions currently account for approximately one-fifth of all crashes and one-sixth of all fatal crashes in the United States. One promising method of mitigating these crashes and fatalities is to develop and install Intersection Advanced Driver Assistance Systems (I-ADAS) on vehicles. When an intersection crash is imminent, the I-ADAS system can either warn the driver or apply automated braking. The potential safety benefit of I-ADAS has been previously examined based on real-world cases drawn from the National Motor Vehicle Crash Causation Survey (NMVCCS). However, these studies made the idealized assumption of full installation in all vehicles of a future fleet. The objective of this work was to predict the reduction in Straight Crossing Path (SCP) crashes due to I-ADAS systems in the United States over time. The proportion of new vehicles with I-ADAS was modeled using Highway Loss Data Institute (HLDI) fleet penetration predictions.

Environmental policies and fuel costs have driven the development of new technologies for internal combustion engines. In this sense, the use of mixtures with small portions of fuel allows lower fuel consumption and pollutants emissions, emerging as a promising strategy. Despite the advantages, lean burn requires a larger energy source to provide satisfactory flame propagation speed and consequently a stable combustion. The use of pre-chamber ignition systems (PCIS) has been used in SI engines to assist the start of combustion of lean mixtures, in which a supplementary fuel system can stratify the amount of either liquid or gaseous fuels supplied to the pre-chamber. In this context, this paper aims to evaluate combustion characteristics of a commercial engine with the use of stratified PCIS operating with impoverished mixtures of ethanol-air in main-chamber and hydrogen assistance in pre-chamber.

Extensive studies of pre-chamber ignition systems in internal combustion engines have proven its effectiveness in reduction of fuel consumption and improvement in several combustion parameters. Considering the different types of pre-chamber configurations, this paper aims to compare the combustion in a SI engine with both homogeneous and stratified pre-chamber ignition systems. To achieve this objective a system with the ability to control the hydrogen injection in the pre-chamber was built. This system was installed in a multi-cylinder Ford Sigma 1.6L engine and tested in a dynamometric room. Tests consisted in imposing a constant rotation and IMEP to test three conditions: standard spark ignition, pre-chamber ignition system without fuel injection (homogenous) and with hydrogen injection (stratified). It was possible to identify that with the use of pre-chamber ignition system there is a reduction in specific fuel consumption and in the combustion duration.

This paper focuses on the analysis of an EcoRouting system with minimum and maximum number of conditional stops. The effect on energy consumption with the presence and absence of road-grade information along a route is also studied. An EcoRouting system has been developed that takes in map information and converts it to a graph of nodes containing route information such as speed limits, stop lights, stop signs and road grade. A variable acceleration rate synthesis methodology is also introduced in this paper that takes into consideration distance, acceleration, cruise speed and jerk rate as inputs to simulate driver behavior on a given route. A simulation study is conducted in the town of Blacksburg, Virginia, USA to analyze the effects of EcoRouting in different driving conditions and to examine the effects of road grade and stop lights on energy consumption.

One of the principal goals of modern vehicle control systems is to ensure passenger safety during dangerous maneuvers. Their effectiveness relies on providing appropriate parameter inputs. Tire-road contact forces are among the most important because they provide helpful information that could be used to mitigate vehicle instabilities. Unfortunately, measuring these forces requires expensive instrumentation and is not suitable for commercial vehicles. Thus, accurately estimating them is a crucial task. In this work, two estimation approaches are compared, an observer method and a neural network learning technique. Both predict the lateral and longitudinal tire-road contact forces. The observer approach takes into account system nonlinearities and estimates the stochastic states by using an extended Kalman filter technique to perform data fusion based on the popular bicycle model.

Resistive forces are a great source of fuel consumption in vehicles. In particular, rolling resistance represent the major resistance force at low speeds. It is highly influenced by the inflation pressure of the tire and vertical load over it. In the present work, a computer model is created with the objective of investigating the influence of tire inflation pressure on fuel consumption and rolling resistance force. Pressure is varied and parameters analyzed at different vehicle speeds for two different calculation methods. Results show significant decrease in fuel consumption and rolling resistance force as inflation pressure is augmented.

The present study introduces a proposal to improve the longitudinal performance of a land vehicle through the adoption of an unusual traction control system. The system is capable of improving the transfer of engine power to the ground and reduces the complexity of the task being performed by the driver. High-performance vehicles are able to achieve high levels of longitudinal acceleration and, sometimes, the power excess leads to the spinoff of the drive wheels, which decrease the ability of the tires to generate force, and consequently the vehicle acceleration. The proposed system acts in addition with the motor control, through the derivation of the motor speed signal, and its control by comparison with a predefined value. The control can delay or even suppress the ignition of the engine. Thus, the rate at which the engine gains speed, and consequently, the rate at which the vehicle accelerates, is limited.

Global trends in the development of spark ignition internal combustion engines lead to the adoption of solutions that reduce CO2 emissions and fuel consumption. Downsizing is a well-established path for this reduction, but it is necessary to use other technologies in order to achieve these ever more rigorous levels. A homogeneous torch ignition system is a viable alternative for reducing CO2 emissions with a combined reduction in specific fuel consumption and increased thermal efficiency. Thus a prototype adapted from an Otto engine with four cylinders is used for analysis. The performance and CO2 emission reference data were initially obtained with the baseline engine operating with a stoichiometric mixture. Then for the same conditions of BMEP, angular velocity and gradual lean of the mixture from the stoichiometry, the results of the adapted system are obtained.

Environmental issues and energy security are critical concerns of the most countries. According researchers, excessive growth of land vehicles is one of the biggest contributors to global air pollution and oil reserves reduction. In this context, the use of lean burn technologies emerges as a promising strategy, allowing lower fuel consumption and pollutants emissions. Present work aims to analyze the behavior of a current commercial engine, gasoline fueled, varying the air-fuel ratio without the use of lean burn ignitions technologies. Analysis was performed through bench dynamometer tests, evaluating cylinder pressure, exhaust gas temperature, fuel conversion efficiency, cycle thermal efficiency, coefficient of variation in indicated mean effective pressure, apparent heat release rate, flame development angle and burn duration.

Tire-pavement interaction noise (TPIN) is a dominant source for passenger cars and trucks above 40 km/h and 70 km/h, respectively. TPIN is mainly generated from the interaction between the tire and the pavement. In this paper, twenty-two passenger car radial (PCR) tires of the same size (16 in. radius) but with different tread patterns were tested on a non-porous asphalt pavement. For each tire, the noise data were collected using an on-board sound intensity (OBSI) system at five speeds in the range from 45 to 65 mph (from 72 to 105 km/h). The OBSI system used an optical sensor to record a once-per-revolution signal to monitor the vehicle speed. This signal was also used to perform order tracking analysis to break down the total tire noise into two components: tread pattern-related noise and non-tread pattern-related noise.