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In comparison to the state of knowledge of standard internal combustion vehicles, there is relatively little known on how to best implement component sub-systems and best integrate these systems together to create a hybrid electric vehicle.

This paper argues the importance of engineering heuristics and introduces an educational data-driven tool to help novice engineers develop their engineering heuristics more effectively. The main objective in engineering practice is to identify opportunities for improvement and apply methods to effect change. Engineers do so by applying ‘how to’ knowledge to make decisions and take actions. This ‘how to’ knowledge is encoded in engineering heuristics. In this paper, we describe a tool that aims to provide heuristic knowledge to users by giving them insight into heuristics applied by experts in similar situations. A repository of automotive data is transformed into a tool with powerful search and data visualization functionalities. The tool can be used to educate novice automotive engineers alongside the current resource intensive practices of teaching engineering heuristics through social methods such as an apprenticeship.

Designing an efficient cooling system with low power consumption is of high interest in the automotive engineering community. Heat generated due to the propulsion system and the on-board electronics in ground vehicles must be dissipated to avoid exceeding component temperature limits. In addition, proper thermal management will offer improved system durability and efficiency while providing a flexible, modular, and reduced weight structure. Traditional cooling systems are effective but they typically require high energy consumption which provides motivation for a paradigm shift. This study will examine the integration of passive heat rejection pathways in ground vehicle cooling systems using a “thermal bus”. Potential solutions include heat pipes and composite fibers with high thermal properties and light weight properties to move heat from the source to ambient surroundings.

This paper describes a computational and experimental effort to document the detailed flow field around a pickup truck. The major objective was to benchmark several different computational approaches through a series of validation simulations performed at Clemson University (CU) and overseen by those performing the experiments at the GM R&D Center. Consequently, no experimental results were shared until after the simulations were completed. This flow represented an excellent test case for turbulence modeling capabilities developed at CU. Computationally, three different turbulence models were employed. One steady simulation used the realizable k-ε model. The second approach was an unsteady RANS simulation, which included a turbulence closure model developed in-house. This simulation captured the unsteady shear layer rollup and breakdown over the front of the hood that was expected and seen in the experiments but unattainable with other off-the-shelf turbulence 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.

Enhanced electric motor performance in transportation vehicles can improve system reliability and durability over rigorous operating cycles. The design of innovative heat rejection strategies in electric motors can minimize cooling power consumption and associated noise generation while offering configuration flexibility. This study investigates an innovative electric motor cooling strategy through bench top thermal testing on an emulated electric motor. The system design includes passive (e.g., heat pipes) cooling as the primary heat rejection pathway with supplemental conventional cooling using a variable speed coolant pump and radiator fan(s). The integrated thermal structure, “cradle”, transfers heat from the motor shell towards an end plate for heat dissipation to the ambient surroundings or transmission to an external thermal bus to remote heat exchanger.

Hybrid electric vehicles offer the advantages of reduced emissions and greater travel range in comparison to conventional and electric ground vehicles. Regardless of propulsion strategy, efficient cooling of electric motors remains an open challenge due to the operating cycles and ambient conditions. The onboard thermal management system must remove the generated heat so that the motors and other vehicle components operate within their designed temperature ranges. In this article, an integrated thermal structure, or cradle, is designed to efficiently transfer heat within the motor housing to the end plates for transmission to an external heat exchanger. A radial array of heat pipes function as an efficient thermal connector between the motor and heat connector, or thermal bus, depending on the configuration. Cooling performance has been evaluated for various driving cycles.

The bending fatigue performance of four heats of carburized, commercially-produced SAE 4320 steel was evaluated. Simulated gear tooth in bending (SGTB) cantilever beam specimens from each heat were identically carburized and fatigue tested in the direct quenched condition after carburizing. The microstructure and fracture surfaces of all specimens were characterized with light and electron microscopy. The four direct quenched sets of specimens performed similarly in low cycle fatigue. Endurance limits among the direct quenched specimens ranged between 1100 and 1170 MPa (160 and 170 ksi) and intergranular cracking dominated fatigue crack initiation. An additional set of specimens from one of the heats was reheated after carburizing. The fatigue performance of the reheated specimens was superior to that of the direct quenched specimens in both the low and high cycle regions. The effects of inclusion content, microstructure, and residual stresses on fatigue performance are discussed.

This study evaluated the bending fatigue performance of a modified SAE 4320 steel as a function of carburizing technique. S-N curves and endurance limits were established by fatigue testing modified Brugger-type specimens that are designed to simulate a single gear tooth. Fractured specimens were examined by light and electron microscopy to determine crack initiation sites, establish the extent of stable crack propagation, and analyze surface oxide types and distributions. Test results show that plasma-carburizing boosted the endurance limit of an oxidation-susceptible gear steel from 1100 MPa to 1375 MPa. Fatigue endurance limits in excess of 1400 MPa had previously been achieved in gas-carburized SAE 4320 steels by reheat treatments and reductions in high-oxidation potential elements. The level of improvement observed in this study suggests that any of these advanced processing techniques can allow significant size reductions and weight savings in automotive transmission gears.

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.

In the ever-evolving landscape of automotive technology, the need for robust security measures and dependable vehicle performance has become paramount with connected vehicles and autonomous driving. The Unified Diagnostic Services (UDS) protocol is the diagnostic communication layer between various vehicle components which serves as a critical interface for vehicle servicing and for software updates. Fuzz testing is a dynamic software testing technique that involves the barrage of unexpected and invalid inputs to uncover vulnerabilities and erratic behavior. This paper presents the implementation of fuzz testing methodologies on the UDS layer, revealing the potential vulnerabilities that could be exploited by malicious entities. By employing both open-source and commercial fuzzing tools and techniques, this paper simulates real-world scenarios to assess the UDS layer’s resilience against anomalous data inputs.

The bending fatigue performance of gears, cantilever beam specimens, and notched-axial specimens were evaluated and compared. Specimens were machined from a modified SAE-4118 steel, gas-carburized, direct-quenched and tempered. Bending fatigue specimens were characterized by light metallography to determine microstructure and prior austenite grain size, x-ray analysis for residual stress and retained austenite measurements, and scanning electron microscopy to evaluate fatigue crack initiation, propagation and overload. The case and core microstructures, prior austenite grain sizes and case hardness profiles from the various types of specimens were similar. Endurance limits were determined to be about 950 MPa for both the cantilever beam and notched-axial fatigue specimens, and 1310 MPa for the single gear tooth specimens.

Very large scale, 3D, viscous, turbulent flow simulations, involving 840,000 finite volume cells and the complete form of the time-averaged Navier-Stokes equations, were conducted to study the mechanisms responsible for total pressure losses in the entire intake system (inlet duct, plenum, ports, valves, and cylinder) of a straight-six diesel engine. A unique feature of this paper is the inclusion of physical mechanisms responsible for cylinder-to-cylinder variation of flows between different cylinders, namely, the end-cylinder (#1) and the middle cylinder (#3) that is in-line with the inlet duct. Present results are compared with cylinder #2 simulations documented in a recent paper by the Clemson group, Taylor, et al. (1997). A validated comprehensive computational methodology was used to generate grid independent and fully convergent results.

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

Capacitance sensing is the technology that detects the presence of nearby objects by measuring the change in capacitance. A change in capacitance is triggered either by a change in dielectric constant, area of overlap or distance of separation between the electrodes of the capacitor. It is a technology that finds wide use in applications such as touch screens, proximity sensing etc. Drawing motivation from such applications, this paper investigates how capacitive sensing can be employed to detect the presence and posture of occupants inside vehicles. Compared to existing solutions, the proposed approach is low-cost, easy to deploy and highly efficient. The sensing system consists of a capacitance-sensing mat that is embedded with copper foils and an associated sensing circuitry. Inside the mat the foils are arranged in rows and columns to form several touch-nodes across the surface of the mat.

The development of next-generation ground vehicle systems relies on modeling and simulation to predict vehicle performance and conduct trade studies in the design and acquisition process. In this paper, we describe the development of an ontology suite to support modeling and simulation of next generation military ground vehicles. The ontology suite is intended to address model reuse challenges and increase the shared understanding of ground vehicle system simulations. The ontology suite consists of four domain ontologies: Vehicle operations (VehOps), Operational environment (Env), Ground vehicle architecture (VehArch), and Simulation model ontology (SimMod) and one integration ontology. The separate domain ontologies allow for extensibility, while the integration ontology establishes semantic relationships across the domains ontologies.

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.

Emissions of six 32 passenger transit buses were characterized using one of the West Virginia University (WVU) Transportable Heavy Duty Emissions Testing Laboratories, and the fixed base chassis dynamometer at the Colorado Institute for Fuels and High Altitude Engine Research (CIFER). Three of the buses were powered with 1997 ISB 5.9 liter Cummins diesel engines, and three were powered with the 1997 5.9 liter Cummins natural gas (NG) counterpart. The NG engines were LEV certified. Objectives were to contrast the emissions performance of the diesel and NG units, and to compare results from the two laboratories. Both laboratories found that oxides of nitrogen and particulate matter (PM) emissions were substantially lower for the natural gas buses than for the diesel buses. It was observed that by varying the rapidity of pedal movement during accelerations in the Central Business District cycle (CBD), CO and PM emissions from the diesel buses could be varied by a factor of three or more.

Driving inattention caused by drowsiness has been a significant reason for vehicle crash accidents, and there is a critical need to augment driving safety by monitoring driver drowsiness behaviors. For real-time drowsy driving awareness, we propose a vision-based driver drowsiness monitoring system (DDMS) for driver drowsiness behavior recognition and analysis. First, an infrared camera is deployed in-vehicle to capture the driver’s facial and head information in naturalistic driving scenarios, in which the driver may or may not wear glasses or sunglasses. Second, we propose and design a multi-modal features representation approach based on facial landmarks, and head pose which is retrieved in a convolutional neural network (CNN) regression model. Finally, an extreme learning machine (ELM) model is proposed to fuse the facial landmark, recognition model and pose orientation for drowsiness detection. The DDMS gives promptly warning to the driver once a drowsiness event is detected.

The effect of diesel cetane number, total aromatic content T90, and fuel nitrogen content on regulated emissions (HC, CO, NOx, and PM) from a 1991 DDC Series 60 engine were measured Emissions tests were conducted using the EPA heavy-duty transient test (CFR 40 Part 86 Subpart N) at a laboratory located 5,280 feet (1609 m) above sea level. The objective of this work was to determine if the effect of fuel chemistry at high altitude is similar to what is observed at sea level and to examine the effect of specific fuel chemistry variables on emissions. An initial tea series was conducted to examine the effect of cetane number and aromatics. Transient emissions for this test series indicated much higher (50 to 75%) particulate emissions at high altitude than observed on the same model engine and similar fuels at sea level.