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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.

The influence of driver modeling and drive cycle target speed trace modification on vehicle dynamics within energy consumption simulations is studied. EPA dynamometer speed error criteria and the SAE J2951 Drive Quality Evaluation for Chassis Dynamometer Testing standard are applied to simulation outputs as proposed components of simulation validation, providing guidelines for acceptable vehicle speed outputs and allowing comparison of simulation results to reported EPA dynamometer test statistics. The combined effect of driver model tuning and drive cycle interpolation methods is investigated for the UDDS, HwFET and US06 drive cycles, with EPA-specified linearly interpolated speed trace and a PI controller driver as a baseline result.

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.

Pedal misapplication (PM) crashes, i.e., crashes caused by a driver pressing one pedal while intending to press another pedal, have historically been identified by searching unstructured crash narratives for keywords and verified via labor-intensive manual inspection. This study proposes an alternative method to identify PM crashes using event data recorders (EDRs). Since drivers in emergency braking situations are motivated to hit the brake hard, it follows that drivers in emergency braking situations that commit a PM would likewise hit the accelerator hard, likely harder than accelerator pedal application during normal driving. Thus, the time-series accelerator pedal position and the derived accelerator pedal application rate were used to isolate accelerator misapplications. Additional strategic filters were applied based on characteristics observed from previous PM analyses to reduce false positive PM identifications.

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.

Due to the large negative impact of combustion gas emissions on air quality and the more stringent environmental legislation, research on internal combustion engines (ICE) are being developed to reduce emissions of pollutant gases to the atmosphere. One of the research fronts is the use of lean mixtures with the pre-chamber ignition system (PCIS). This system consists of a pre-chamber (PC) connected to the main chamber by one or more interconnecting holes. A spark plug initiates combustion of the mixture present in the pre-chamber, which is propagated as gas jet into the main chamber, igniting the lean mixture present therein. The gas jets have high thermal and kinetic energy, which promote faster combustion duration, making the system less prone to knock and with lower cyclic variability of the IMEP, enabling the lean limit extension. The pre-chamber system can be assisted with a supplementary liquid or gaseous fuel injection, enabling the charge stratification.

Atmospheric pollution is the major public health issue in many cities around the world. Internal combustion engines (ICE) and industries are common sources of pollutants that aggravate this situation. Aiming to overcome this problem, increasingly restrictive legislation on combustion pollutant emissions has been formulated and new technologies are being developed to ensure compliance with such restrictions. In this scenario, the lean mixtures appear as a possible alternative, but also bring some inconveniences such as combustion instabilities. Pre-chamber ignition systems (PCIS) enable a more stable combustion process due to high kinetic, thermal and chemical energy of the gases from the pre-chamber (PC), which pass through nozzles and begin the combustion process of the air-fuel mixture contained in the main combustion chamber (MC). However, some challenges still have to be overcome in the development of these systems, one of the main ones being hydrocarbon (HC) emissions.

The work focuses on studying ethanol spray behavior injected directly inside a spark ignited internal combustion engine in the compression stroke. An experimental procedure for measuring spray penetration and spray overall cone angle produced by a multi-hole direct injector was developed by means of computational codes written in Matlab environment for working with images of spray injections and to acquire calculated results in an automatic way. The shadowgraph technique with back continuous illumination associated with a high speed recording image process was used in a single cylinder optical research engine for acquiring images of Brazilian ethanol fuel injected at 120° before the top dead center of compression stroke. The process of spray injections occurred with engine speeds of 1000 rpm, 2000 rpm and 3000 rpm. The results showed that spray penetrations decrease and spray cone angle increase when the engine speed is raised.

An unconventional conceptual design of truck chassis with multi-functional cross-members is proposed, and an optimization framework is developed to optimize its structure to minimize mass while satisfying stiffness and modal frequency constraints. The side rails are C-sectional channels of variable height and were divided into six sections, each with different thickness distribution for the flanges and the web. The gearbox cross-member and the intermediate cross-members are compressed-air cylinders, and hence they act as multi-functional components. The dimensions and thickness of the side rails and the air-tank cross members are defined by a set of parameters which are considered as design variables in the optimization problem. The structure consists of three additional fixed cross-members which are modeled using beam elements. The limits of the design variables are decided while considering manufacturing limits.

When analyzing vibrations in internal combustion engines, it is noticed that the greatest sources of vibrations are generated by combustion and mechanical forces. These forces occur over a wide frequency range and are transmitted to the outer surface of the engine through several paths, such as through the piston mechanism, connecting rod, crankshaft and engine block. As a result of the action of these forces, the external surfaces of the engine are subjected to vibrations of various amplitudes. Vibration problems in internal combustion engines are common due to the wide variety of parts and components that make up such engines. The crankshaft undergoes transverse, longitudinal and torsional vibrations due to the dynamics of the stresses sustained mainly during the combustion phase of the engine.

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.