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This paper seeks to identify key input parameters needed to achieve a production-viable control strategy for spark-assisted compression ignition (SACI) engines. SACI is a combustion strategy that uses a spark plug to initiate a deflagration flame that generates sufficient ignition energy to trigger autoignition in the remaining charge. The flame propagation phase limits the rate of cylinder pressure rise, while autoignition rapidly completes combustion. High dilution within the autoignited charge is generally required to maintain reaction rates feasible for production. However, this high dilution may not be reliably ignited by the spark plug. These competing constraints demand novel mixture preparation strategies for SACI to be feasible in production. SACI with charge stratification has demonstrated sufficiently stable flame propagation to reliably trigger autoignition across much of the engine operating map.

This paper describes the development and simulation of a voice and pointing gesture interaction system for on-route update of autonomous vehicles’ path. The objective of this research is to provide users of autonomous vehicles a human vehicle interaction mode that enables them to make and communicate spontaneous decisions to the autonomous car, modifying its pre-defined autonomous route in real-time. For example, similar to giving directions to a taxi driver, a user will be able to tell the car «Stop there» or «Take that exit». In this way, the user control/spontaneity vs interaction flexibility dilemma that current autonomous vehicle concepts have, could be solved, potentially increasing the user acceptance of this technology. The system was designed following a level structured state machine approach. The simulations were developed using MATLAB and VREP, a robotics simulation platform, which has accurate vehicle and sensor models.

Automotive and truck manufacturers are introducing electric propulsion systems into their ground vehicles to reduce fossil fuel consumption and harmful tailpipe emissions. The mobility shift to electric motors requires a compact thermal management system that can accommodate heat dissipation demands with minimum energy consumption in a confined space. An innovative cooling system design, emphasizing passive cooling methods coupled with a small liquid system, using a thermal bus architecture has been explored. The laboratory experiment features an emulated electric motor interfaced to a thermal cradle and multiple heat rejection pathways to evaluate the transfer of generated heat to the ambient surroundings. The thermal response of passive (e.g., carbon fiber, high thermal conductivity material, thermosyphon) and active cooling systems are investigated for two operating scenarios.

Vehicular control systems are characterized with numerous complex interactions with a steady rise of autonomous functions, which makes it more challenging for designers and safety engineers to identify unexpected failures. These systems tend to be highly integrated and exhibit features like concurrency for which traditional verification and validation techniques (i.e. testing and simulation) are insufficient to provide rigorous and complete assessment. Model Checking, a well-known formal verification technique, can be used to rigorously prove the correctness of such systems according to design Requirements. In particular, Model Checking is a method for formally verifying finite-state concurrent systems. Specifications about the system are expressed as temporal logic formulas, and efficient symbolic algorithms are used to traverse the model defined by the system and check if the specification holds or not.

Automotive simulators offer an immersive environment to operate vehicle systems in a safe and repeatable manner. A fundamental question exists regarding their effectiveness for an identified task. For instance, driving simulators can play a significant role in evaluating vehicle designs, developing safety regulations, supporting human factors engineering research, administering driver training and education, and offering individual entertainment. Some of the driving simulator technology users include automotive manufacturers and suppliers, research laboratories at universities and government agencies, driver education and training programs, and motorsports and racing entertainment venues. In each case, the simulator capabilities and functionality must encompass the expectations of the driver to permit their perception of realistic scenarios for evaluation. This paper investigates three driving simulators in terms of their hardware and software, as well as their applications.

Tires manufactured from polyurethane (PU) have been espoused recently for reduced hysteretic loss, but the material provides poor traction or poor wear resistance in the application, requiring inclusion of a traditional vulcanized rubber tread at the contact surface. The tread can be attached by adhesive methods after the PU body is cured, or the PU can be directly cured to reception sites on the rubber chain molecules unoccupied by crosslinked (vulcanizing) sulfur atoms. This paper provides a study of the two bonding options, both as-manufactured and after dynamic loading representative of tire performance in service. Models of each process are introduced, and an experimental comparison of the bonding strength between each method is made. Results are applied to tire fatigue simulation.

Collaborative robots are more and more used in smart manufacturing because of their capability to work beside and collaborate with human workers. With the deployment of these robots, manufacturing tasks are more inclined to be accomplished by multiple humans and multiple robots (MH-MR) through teaming effort. In such MH-MR collaboration scenarios, the task distribution among the multiple humans and multiple robots is very critical to efficiency. It is also more challenging due to the heterogeneity of different agents. Existing approaches in task distribution among multiple agents mostly consider humans with assumed or known capabilities. However human capabilities are always changing due to various factors, which may lead to suboptimal efficiency. Although some researches have studied several human factors in manufacturing and applied them to adjust the robot task and behaviors.

A state of the art proprietary method for aluminum-to-aluminum joining in the automotive industry is Resistance Spot Welding. However, with spot welding (1) structural performance of the joint may be degraded through heat-affected zones created by the high temperature thermal joining process, (2) achieving the double-sided access necessary for the spot welding electrodes may limit design flexibility, and (3) variability with welds leads to production inconsistencies. Self-piercing rivets have been used before; however they require different rivet/die combinations depending on the material being joined, which adds to process complexity. In recent years the introductions of screw products that combine the technologies of friction drilling and thread forming have entered the market. These types of screw products do not have these access limitations as through-part connections are formed by one-sided access using a thermo-mechanical flow screwdriving process with minimal heat.

Several emerging technologies hold great promise to improve the 360-degree awareness of the heavy vehicle driver. However, current industry-standard evaluation methods do not measure all the comprehensive factors contributing to the overall effectiveness of such systems. As a result, industry is challenged to evaluate new technologies in a way that is objective and allows the comparison of different systems in a consistent manner. This research aims to explore the methods currently in use, identify relevant factors not presently incorporated in standard procedures, and recommend best practices to accomplish an overall measurement system that can quantify performance beyond simply the field of view of a driver visibility system. We introduce a new metric, “Clarity of View,” that incorporates several important factors for visibility systems including: gap acceptance accuracy, image detection time, and distortion.

The strain-induced diffusionless shear transformation of retained austenite to martensite during straining of transformation induced plasticity (TRIP) assisted steels increases strain hardening and delays necking and fracture leading to exceptional ductility and strength, which are attractive for automotive applications. A novel technique that provides the retained austenite volume fraction variation with strain with improved precision is presented. Digital images of the gauge section of tensile specimens were first recorded up to selected plastic strains with a stereo digital image correlation (DIC) system. The austenite volume fraction was measured by synchrotron X-ray diffraction from small squares cut from the gage section. Strain fields in the squares were then computed by localizing the strain measurement to the corresponding region of a given square during DIC post-processing of the images recorded during tensile testing.

The Deep Orange program immerses automotive engineering students into the world of an OEM as part of their 2-year graduate education. In support of developing the program’s seventh vehicle concept, the students studied the sponsoring brand essence, conducted market research, and made a heuristic assessment of competitor vehicles. The upfront research lead to the definition of target customers and setting vehicle level targets that were broken down into requirements to develop various vehicle sub-systems. The powertrain team was challenged to develop a scalable propulsion concept enabled by a common vehicle architecture that allowed future customers to select (at the point of purchase) among various levels of electrification best suiting their needs and personal desires. Four different configurations were identified and developed: all-electric, two plug-in hybrid electric configurations, and an internal combustion engine only.

This paper describes the development of test equipment for determining the wear viability of various lunar wheel tread materials with service lives of up to ten years and 10,000 km. The problem is defined, and concepts are proposed, evaluated, and selected. An abrasive turntable is chosen for simplicity and accuracy of modeling the original wheel configuration. Additionally, the limitations of the test are identified, such as the sensitivity to off-vertical loading, and future work is projected in order to more effectively continue testing. Finally, this paper presents the challenges of collaborative research effort between an undergraduate research team and industry, with government lab representatives as customers

Determining the validity of the design space early in the conceptualization of a project can make the difference between project success and failure. Early assessment of technical feasibility, project risk, technical readiness and realistic performance expectations based on models with different levels of fidelity, uncertainty, and technical robustness is a challenging mission critical task for large procurement projects. Tradespace exploration uses model-based engineering analysis, design exploration methods, and multi-objective optimization techniques to enable project stakeholders to make informed decisions and tradeoffs concerning the scope, schedule, budget, performance and risk profile of a project. As the intersection with a number of project stakeholders, tradespace studies can provide a significant impact upon the direction and decision-making in a project.

This paper entails the design and development of a NASA testing system used to simulate wheel operation in a lunar environment under different loading conditions. The test system was developed to test the design of advanced nonpneumatic wheels to be used on the NASA All-Terrain Hex-Legged Extra-Terrestrial Explorer (ATHLETE). The ATHLETE, allowing for easy maneuverability around the lunar surface, provides the capability for many research and exploration opportunities on the lunar surface that were not previously possible. Each leg, having six degrees of freedom, allows the ATHLETE to accomplish many tasks not available on other extra-terrestrial exploration platforms. The robotic vehicle is expected to last longer than previous lunar rovers.

This paper is a review of turbulence models and computational methods that have been produced at Clemson University's Advanced Computational Research Laboratory. The goal of the turbulence model development has been to create physics-based models that are economically feasible and can be used in a competitive environment, where turnaround time is a critical factor. Given this goal, all of the work has been focused on Reynolds-Averaged Navier-Stokes (RANS) simulations in the eddy-viscosity framework with the majority of the turbulence models having three transport equations in addition to mass, momentum, and energy. Several areas have been targeted for improvement in turbulence modeling for complex flows such as those found in motorsports aerodynamics: the effects of streamline curvature and rotation on the turbulence field, laminar-turbulent transition, and separated shear layer rollup and breakdown.

The Michelin Tweel tire structure has recently been developed as an innovative non-pneumatic tire which has potential for improved handling, grip, comfort, low energy loss when impacting obstacles and reduced rolling resistance when compared to a traditional pneumatic tire. One of the potential sources of vibration during rolling of a non-pneumatic tire is the buckling phenomenon and snapping back of the spokes in tension when they enter and exit the contact zone. Another source of noise was hypothesized due to a flower petal ring vibration effect due to discrete spoke interaction with the ring and contact with the ground during rolling as the spokes cycle between tension and compression. Transmission of vibration between the ground force, ring and spokes to the hub was also considered to be a significant contributor to vibration and noise characteristics of the Tweel.

Understanding the effects of tire and vehicle properties on the rollover propensity of tractor semi-trailer trucks is essential. The major objective of the project described by this paper was to develop a simplified computational tool that can be used to understand and predict the effects of various tire characteristics and truck design parameters on rollover under steady cornering and non-tripped conditions. In particular, this tool may be used to help understand the basic mechanisms governing rollover propensity of trucks equipped with New Generation Wide Single tires as contrasted with conventional tires. Effects of tire flexibility, roll-compliant suspensions, fifth - wheel lash and nonlinear suspension characteristics are included in the model and are presented below. Design parameter data used as input to the model were obtained from Michelin Americas Research and Development Corporation.

Strategies for evaluating the impact of mission requirements on the design of mission-specific vehicles are needed to enable project managers to assess potential benefits and associated costs of changes in requirements. Top-level requirements that cause significant cascaded difficulties on lower-level requirements should be identified and presented to decision-makers. This paper aims to introduce formal methods and computational tools to enable the analysis and allocation of mission requirements.

This paper presents a cohesive set of engine-in-the-loop (EIL) studies examining the use of hierarchical model-predictive control for fuel consumption minimization in a class-8 heavy-duty truck intended to be equipped with Level-1 connectivity/automation. This work is motivated by the potential of connected/automated vehicle technologies to reduce fuel consumption in both urban/suburban and highway scenarios. The authors begin by presenting a hierarchical model-predictive control scheme that optimizes multiple chassis and powertrain functionalities for fuel consumption. These functionalities include: vehicle routing, arrival/departure at signalized intersections, speed trajectory optimization, platooning, predictive optimal gear shifting, and engine demand torque shaping. The primary optimization goal is to minimize fuel consumption, but the hierarchical controller explicitly accounts for other key objectives/constraints, including operator comfort and safe inter-vehicle spacing.

Since 1989, ISO has published procedures for developing and testing public information symbols (ISO 9186), while the SAE standard for in-vehicle icon comprehension testing (SAE J2830) was first published in 2008. Neither testing method was designed to evaluate the comprehension of symbols in modern vehicles that offer digital instrument cluster interfaces that afford new levels of flexibility to further improve drivers’ understanding of symbols. Using a driving simulator equipped with an eye tracker, this study investigated drivers’ understanding of six automotive symbols presented on in-vehicle displays. Participants included 24 teens, 24 adults, and 24 senior drivers. Symbols were presented in a symbol-only, symbol + short text descriptions, and symbol + long text description conditions. Participants’ symbol comprehension, driving performance, reaction times, and eye glance times were measured.