Search Results

Since the early 1990’s, commercial vehicles have suffered from repeated vulnerability exploitations that resulted in a need for improved automotive cybersecurity. This paper outlines the strategies and challenges of implementing an automotive Zero Trust Architecture (ZTA) to secure intra-vehicle networks. Zero Trust (ZT) originated as an Information Technology (IT) principle of “never trust, always verify”; it is the concept that a network must never assume assets can be trusted regardless of their ownership or network location. This research focused on drastically improving security of the cyber-physical vehicle network, with minimal performance impact measured as timing, bandwidth, and processing power. The automotive ZTA was tested using a software-in-the-loop vehicle simulation paired with resource constrained hardware that closely emulated a production vehicle network.

Simulation and testing are often done by different engineers in different departments of a company. This can lead to disconnects and unrealistic predictions, especially if the person doing simulations does not have an experimental background. On the other hand, experimental results can also include errors that result in misleading answers. It is important for the engineer doing either testing or simulation to have a good understanding for what results are plausible and what results might be suspect. This paper will provide examples where error crept into testing or simulation that could have been caught and corrected early if a good feel for “reasonable” results had been in place. The importance of understanding how a software package is analyzing the data will be explained, since settings buried deep within a menu structure can drive misleading results.

Trained human raters have been used by organizations such as the Coordinating Research Council (CRC) to assess the vehicle driveability performance effect of fuel volatility. CRC conducts workshops to test fuel effects and their impact on vehicle driveability. CRC commissioned Southwest Research Institute (SwRI) to develop a “Trick Car” vehicle that could trigger malfunctions on-demand that mimic driveability events. This vehicle has been used to train novice personnel on the CRC Driveability Procedure E-28-94. While largely effective, even well-trained human raters can be inconsistent with other raters. Further, CRC rater workshop programs used to train and calibrate raters are infrequent, and there are a limited number of available trained raters. The goal of this program was to augment or substitute human raters with an electronic driveability sensing system.

A physics-based spark ignition model was developed and integrated into a commercial CFD code. The model predicted the spark discharge process based on the electrical parameters of the secondary ignition circuit, tracked the spark motion as it was stretched by in-cylinder gas motion, and determined the resulting energy deposition to the gas. In concert with the existing kinetic solver in the CFD code, the resulting ignition and flame propagation processes were simulated. The model results have been validated against both imaging rig experiments of the spark in moving air and against engine experimental data. The model was able to replicate the key features of the spark and to capture the cyclic variability of high-dilution combustion when multiple engine cycles were simulated.

This project’s objective was to generate experimental data to evaluate the impact of metals doped B20 on diesel particle filter (DPF) ash loading and performance compared to that of conventional petrodiesel. The effect of metals doped B20 vs. conventional diesel on a DPF was quantified in a laboratory controlled accelerated ash loading study. The ash loading was conducted on two DPFs – one using ULSD fuel and the other on B20 containing metals dopants equivalent to 4 ppm B100 total metals. Engine oil consumption and B20 metals levels were accelerated by a factor of 5, with DPFs loaded to 30 g/L of ash. Details of the ash loading experiment and on-engine DPF performance evaluations are presented in the companion paper (Part I). The DPFs were cleaned, and ash samples were taken from the cleaned material. X-ray Fluorescence (XRF), X-Ray Photoelectron Spectroscopy (XPS) and X-Ray Diffraction (XRD) were conducted on the ash samples.

A push for more stringent emissions regulations has resulted in larger, increasingly complex aftertreatment solutions. In particular, oxides of nitrogen (NOX) and particulate matter (PM) have been controlled using two separate systems, selective catalytic reduction (SCR) and the catalyze diesel particulate filter (CDPF), or the functionality has been combined into a single device producing the SCR on filter (SCRoF). The SCRoF forgoes beneficial NO2 production present in the CDPF to avoid NH3 oxidation which occurs when using platinum group metals (PGM) for oxidation. In this study, mixed-metal oxides are shown to oxidize NO to NO2 without appreciable NH3 oxidation. This selectivity leads to enhanced performance when combined with a typical Cu-zeolite catalyst.

SCR-on-filter, or SCRoF, is an emerging technology for different market segments and vehicle applications. The technology enables simultaneous particulate matter trapping and NOX reduction, and provides thermal management and aftertreatment packaging benefits. However, there is little information detailing the lubricant derived exposure effects on functional SCR performance. A study was conducted to evaluate the impact of various oil consumption pathways on a light duty DOC and SCRoF aftertreatment system. This aftertreatment system was aged utilizing an engine test bench modified to enable increased oil consumption rates via three unique oil consumption pathways. The components were characterized for functional SCR performance, ash morphology, and ash deposition characteristics. This included utilizing techniques, such as SEM / EDS, to evaluate the ash structures and quantify the ash elemental composition.

The process of developing, parameterizing, validating, and maintaining models occurs within a wide variety of tools, and requires significant time and resources. To maximize model utilization, models are often shared between various toolsets and experts. One common example is sharing aircraft engine models with airframers. The functionality of a given model may be utilized and shared with a secondary model, or multiple models may run collaboratively through co-simulation. There are many technical challenges associated with model sharing and co-simulation. For example, data communication between models and tools must be accurate and reliable, and the model usage must be well-documented and perspicuous for a user. This requires clear communication and understanding between computer scientists and engineers. Most often, models are developed by engineers, whereas the tools used to share the models are developed by computer scientists.

Several wireless systems such as Dedicated Short Range Communication (DSRC), cellular, Wi-Fi, Bluetooth, and the Tire Pressure Monitoring System (TPMS) can be found on modern vehicles. In the future, Software Defined Radio (SDR) technology could be integrated into automobiles to increase the efficiency and adaptability of wireless communications systems. SDR is also a powerful tool for designing and testing new communications protocols. However there are also some security considerations associated with SDR. This paper will review some advantages of using SDR technology in the automotive domain as well as potential security issues. The authors are currently conducting research into the use of SDR technology to model wireless systems and investigate security threats in modern vehicular systems.

The State of Florida initiated the SunGuide® Advanced Traffic Management System (ATMS) software development program in October 2003; that software is deployed in over 15 Traffic Management Centers (TMCs) throughout the major cities in Florida. One of SunGuide's biggest strengths is a software architecture that allows for short development times for new functionality. This paper describes the system design, implementation, and lessons learned from the development of the SunGuide Connected Vehicle Subsystem (CVS). The SunGuide CVS receives real-time speed, location, and heading data from instrumented vehicles and uses that data in a manner similar to its use of traffic detector data to provide information to the TMC. In addition to the vehicle providing data to the TMC, the TMC may create and publish Traveler Advisory Messages to the vehicle as part of the SunGuide Event Management response plans.

The general benefits of automation are well documented. Order of magnitude improvements are achievable in processing speeds, production rates, and efficiency. Other benefits include improved process consistency (inversely, reduced process variation), reduced waste and energy consumption, and risk reduction to operators. These benefits are especially true for the automation of the aerospace paint removal (or "depaint") processes. Southwest Research Institute® (SwRI®) developed and implemented two systems in the early 1990s for depainting full-body fighter aircraft at Robins Air Force Base (AFB) at Warner Robins, Georgia, and Hill AFB at Ogden, Utah. These systems have been in production use, almost continuously for approximately 20 years, for the depainting of the F-15 Eagle and the F-16 Falcon fighter aircraft, respectively.

Southwest Research Institute developed an Autonomous Ground Vehicle (AGV) capable of navigating in urban environments. The paper first gives an overview of hardware and software onboard the vehicle. The systems onboard are classified into perception, intelligence, and command and control modules to mimic a human driver. Perception deals with sensing from the world and translating it into situation awareness. This awareness is then fed into intelligence modules. Intelligence modules take inputs from the user to understand the need to navigate from its current location to another destination and, then, generate a path between them on urban, drivable surfaces using its internal urban database. Situational awareness helps intelligence to update the path in real time by avoiding any static/moving obstacles while following traffic rules.

This paper describes a hybrid robust nonlinear control approach for modern diesel engines running low temperature combustion and conventional diesel combustion modes. Using alternative combustion modes has become a promising approach to reduce engine emissions. However, due to very different in-cylinder conditions and fueling parameters for different combustion modes, control of engines operating multiple combustion modes is very challenging. It becomes difficult for conventional calibration / mapping based approaches to produce satisfactory results in terms of engine torque responses and emissions. Advanced control techniques are then demanded to accomplish the tasks. An innovative hybrid control system is designed to track different key engine operating variables at different combustion modes as well as avoid singularity which is inherent for turbocharged diesel engines running multiple combustion modes.

Tests were conducted on a variety of commercially available spark plugs to determine the influence of igniter design on initial kernel formation and overall performance. Flame kernel formation was investigated using high-speed schlieren visualization. The flame growth rate was quantified using the area of the burned gas region. The results showed that kernel growth rate was heavily influenced by electrode geometry and configuration. The igniters were also tested in a bomb calorimeter to determine the levels of supplied and delivered energy. The typical ratio of supplied to delivered energy was 20% and igniters with a higher internal resistance delivered more energy and had faster kernel formation rates. The exception was plugs with large amounts of conductive mass near the electrodes, which had very slow kernel formation rates despite relatively high delivered energy levels.

Swirl plane Particle Image Velocimetry (PIV) measurements were performed in a single-cylinder optically accessible gasoline direct injection (DISI) engine using a borescope introduced through the spark plug hole. This allowed the use of a contoured piston and the visualization of the flow field in and around the piston bowl. The manifold absolute pressure (MAP) was fixed at 90 kPa and the engine speed was varied in increments of 250 rpm from 750 rpm to 2000 rpm. Images were taken from 270° to 320° bTDC of compression at 10° intervals to study the evolution of the velocity fluctuations. Measurements were performed with and without fuel injection to study its effect on the in-cylinder flow fields. Fuel was injected at 10 MPa and 5 MPa. The 2-D spatial mean velocities of individual flow fields and their decompositions were averaged over 100 cycles and used to investigate the effects of engine speed and image timing on the flow field.

During the past couple of years, a committee under the auspices of the ASME Codes and Standards division has been formed and are meeting regularly. The purpose of the committee is to develop and publish a set of documents that describe a common process for verification and validation of computational solid mechanics models. There are many issues under discussion and many concepts under debate. In this paper we will present some the major concepts and the differing viewpoints focusing on the concept of validation and relate this to the automotive industry in particular.

This paper describes the development of a generic test cell software designed to overcome many vehicle-component testing difficulties by introducing modern, real-time control and simulation capabilities directly to laboratory test environments. Successfully demonstrated in a transmission test cell system, this software eliminated the need for internal combustion engines (ICE) and test-track vehicles. It incorporated the control of an advanced AC induction motor that electrically simulated the ICE and a DC dynamometer that electrically replicated vehicle loads. Engine behaviors controlled by the software included not only the average crankshaft torque production but also engine inertia and firing pulses, particularly during shifts. Vehicle loads included rolling resistance, aerodynamic drag, grade, and more importantly, vehicle inertia corresponding to sport utility, light truck, or passenger cars.

Atmospheric corrosion of steels, aluminum alloys, and Al-clad aluminum alloys is a problem for many civil engineering structures, commercial and military vehicles, and aircraft. Paint is usually the primary means to prevent the corrosion of steel bridge components, automobiles, trucks, and aircraft. Under ideal conditions, the coating provides a continuous layer that is impervious to moisture. At present, maintenance cycles for commercial and military aircraft and ground vehicles, as well as engineered structures, is based on experience and appearance rather than a quantitative determination of coating integrity. To improve the maintenance process and reduce costs, sensors are often used to monitor corrosion. The present suite of sensors designed to detect corrosion and marketed to predict the lifetime of the engineered components, however, are not useful for determining the condition of the protective paint coatings.

Excessive interior noise and vibration in propeller driven general aviation aircraft can result in poor pilot communications with ground control personnel and passengers, and, during extended flights, can lead to pilot and passenger fatigue. Noise source/path identification technology applicable to single engine propeller driven aircraft were employed to identify interior noise sources originating from structure-borne engine/propeller vibration, airborne propeller transmission, airborne engine exhaust noise, and engine case radiation. The approach taken was first to conduct a Principal Value Analysis (PVA) of an in-flight noise and vibration database acquired on a single engine aircraft to obtain a correlated data set as viewed by a fixed set of cabin microphones.

Control of structure borne noise transmission into an aircraft cabin generated from component excitation, such as rotor/engine vibration imbalance or firing excitations or from auxiliary equipment induced vibrations, can be studied empirically via impedance characterization of the system components and application of appropriate component coupling procedures. The present study was aimed at demonstrating the usefulness of such impedance modeling techniques as applied to a Bell 206B rotorcraft and a Cessna TR182 general aviation aircraft. Simulated rotor/engine excitations were applied to the assembled aircraft systems to provide baseline structure borne noise transmission data. Thereafter, impedance tests of the system components were carried out to provide a data base from which system component coupling studies were carried out.