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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.

Predicting fuel economy during early stages of concept development or feasibility study for a new type of powertrain configuration is an important key factor that might affect the powertrain configuration decision to meet CAFE standards. In this paper an efficient model has been built in order to evaluate the fuel economy for a new type of charge sustaining series hybrid vehicle that uses a Genset assembly (small 2 cylinders CNG fueled engine coupled with a generator). A first order mathematical model for a Li-Ion polymer battery is presented based on actual charging /discharging datasheet. Since the Genset performance data is not available, normalized engine variables method is used to create powertrain performance maps. An Equivalent Consumption Minimization Strategy (ECMS) has been implemented to determine how much power is supplied to the electric motor from the battery and the Genset.

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.

Hybrid vehicle embedded systems and payloads require progressively more accurate and versatile thermal control mechanisms and strategies capable of withstanding harsh environments and increasing power density. The division of the cargo and passenger compartments into convective thermal zones which are independently managed can lead to a manageable temperature control problem. This study investigates the performance of a Peltier-effect thermoelectric zone cooling system to regulate the temperature of target objects (e.g., electronic controllers, auxiliary computer equipment, etc) within ground vehicles. Multiple thermoelectric cooling modules (TEC) are integrated with convective cooling fans to provide chilled air for convective heat transfer from a robust, compact, and solid state device. A series of control strategies have been designed and evaluated to track a prescribed time-varying temperature profile while minimizing power consumption.

The advancements in automation, big data computing and high bandwidth networking has expedited the realization of Industrial Internet of Things (IIoT). IIoT has made inroads into many sectors including automotive, semiconductors, electronics, etc. Particularly, it has created numerous opportunities in the automotive manufacturing sector to realize the new aura of platform concepts such as smart material flow control. This paper provides a thought provoking application of IIoT in automotive composites body shop. By creating a digital twin for every physical part, we no longer need to adhere to the conventional manufacturing processes and layouts, thus opening up new opportunities in terms of equipment and space utilization. The century-old philosophy of the assembly line might not be the best layout for vehicle manufacturing, thus proposing a novel assembly grid layout inspired from a colony of ants working to accomplish a common goal.

This paper outlines a real-time hierarchical control allocation algorithm for multi-axle land vehicles with independent hub motor wheel drives. At the top level, the driver’s input such as pedal position or steering wheel position are interpreted into desired global state responses based on a reference model. Then, a locally linearized rigid body model is used to design a linear quadratic regulator that generates the desired global control efforts, i.e., the total tire forces and moments required track the desired state responses. At the lower level, an optimal control allocation algorithm coordinates the motor torques in such a manner that the forces generated at tire-road contacts produce the desired global control efforts under some physical constraints of the actuation and the tire/wheel dynamics. The performance of the proposed control system design is verified via simulation analysis of a 3-axle heavy vehicle with independent hub-motor drives.

The ever-growing concern to reduce the impact of transportation systems on environment has pushed automotive industry towards fuel-efficient and sustainable solutions. While several approaches have been used to improve fuel efficiency, the light-weighting of automobile components has proven broadly effective. A substantial effort is devoted to lightweighting body-in-white which contributes ~35% of total weight of vehicle. Closure systems, however, have been often overlooked. Closure systems are extremely important as they account for ~ 50% of structural mass and have a very diverse range of requirements, including crash safety, durability, strength, fit, finish, NVH, and weather sealing. To this end, a carbon fiber-reinforced thermoplastic composite door is being designed for an OEM’s mid-size SUV, that enables 42.5% weight reduction. In this work, several novel composite door assembly designs were developed by using an integrated design, analysis and optimization approach.

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.

Traditional Electronic Stability Control (ESC) for automobiles is usually accomplished through the use of estimated vehicle dynamics from simplified models that rely on parameters such as cornering stiffness that can change with the vehicle state and time. This paper proposes a different method for electronic stability control of oversteer by predicting the degree of instability in a vehicle. The algorithm is solely based on measurable response characteristics including lateral acceleration, yaw rate, speed, and driver steering input. These signals are appropriately conditioned and evaluated with fuzzy logic to determine the degree of instability present. When the “degree of instability” passes a certain threshold, the appropriate control action is applied to the vehicle in the form of differential yaw braking. Using only the measured response of the vehicle alleviates the problem of degraded performance when vehicle parameters change.

Over the last decade, tremendous amount of research and progress has been made towards developing smart technologies for autonomous vehicles such as adaptive cruise control, lane keeping assist, lane following algorithms, and decision-making algorithms. One of the fundamental objectives for the development of such technologies is to enable autonomous vehicles with the capability to avoid obstacles and maintain safety. Automobiles are real-world dynamical systems - possessing inertia, operating at varying speeds, with finite accelerations/decelerations during operations. Deployment of autonomy in vehicles increases in complexity multi-fold especially when high DOF vehicle models need to be considered for robust control. Model Predictive Control (MPC) is a powerful tool that is used extensively to control the behavior of complex, dynamic systems. As a model-based approach, the fidelity of the model and selection of model-parameters plays a role in ultimate performance.

Simultaneous Localization and Mapping (SLAM) algorithms are extensively utilized within the field of autonomous navigation. In particular, numerous open-source Robot Operating System (ROS) based SLAM solutions, such as Gmapping, Hector, Cartographer etc., have simplified deployments in application. However, establishing the accuracy and precision of these ‘out-of-the-box’ SLAM algorithms is necessary for improving the accuracy and precision of further applications such as planning, navigation, controls. Existing benchmarking literature largely focused on validating SLAM algorithms based upon the quality of the generated maps. In this paper, however, we focus on examining the localization accuracy of existing 2-dimensional LiDAR based indoor SLAM algorithms. The fidelity of these implementations is compared against the OptiTrack motion capture system which is capable of tracking moving objects at sub-millimeter level precision.

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.

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.

In-cylinder surface temperature is of heightened importance for Homogeneous Charge Compression Ignition (HCCI) combustion since the combustion mechanism is thermo-kinetically driven. Thermal Barrier Coatings (TBCs) selectively manipulate the in-cylinder surface temperature, providing an avenue for improving thermal and combustion efficiency. A surface temperature swing during combustion/expansion reduces heat transfer losses, leading to more complete combustion and reduced emissions. At the same time, achieving a highly dynamic response sidesteps preheating of charge during intake and eliminates the volumetric efficiency penalty. The magnitude and temporal profile of the dynamic surface temperature swing is affected by the TBC material properties, thickness, morphology, engine speed, and heat flux from the combustion process. This study follows prior work of authors with Yttria Stabilized Zirconia, which systematically engineered coatings for HCCI combustion.

Spark-assisted compression ignition (SACI) leverages flame propagation to trigger autoignition in a controlled manner. The autoignition event is highly sensitive to several parameters, and thus, achieving SACI in production demands a high tolerance to variations in conditions. Limited research is available to quantify the combustion response of SACI to these variations. A simulation study is performed to establish trends, limits, and control implications for SACI combustion over a wide range of conditions. The operating space was evaluated with a detailed chemical kinetics model. Key findings were synthesized from these results and applied to a 1-D engine model. This model identified performance characteristics and potential actuator positions for a production-viable SACI engine. This study shows charge preparation is critical and can extend the low-load limit by strengthening flame propagation and the high-load limit by reducing ringing intensity.

Computational Fluid Dynamics (CFD) modeling was used to investigate the effects of the direct injection of wet ethanol at various injection timings during the intake stroke in a diesel engine with a shallow bowl piston. Thermally Stratified Compression Ignition (TSCI) has been proposed to expand the operating range of Low Temperature Combustion (LTC) by broadening the temperature distribution in the cylinder prior to ignition. TSCI is accomplished by injecting either water or a water-fuel mixture with a high latent heat of vaporization like wet ethanol. This current study focuses on isolating the effects that injecting such a high heat of vaporization mixture during the intake stroke has on the distribution of temperature and equivalence ratio in the cylinder before the onset of combustion. A CONVERGE 3-D CFD model of a single cylinder diesel research engine using Reynolds Averaged Naiver Stokes (RANS) turbulence modeling was developed and validated against experimental data.

This paper presents a hierarchical control architecture to coordinate a group of connected vehicles on signalized intersection roads, where vehicles are allowed to change lane to follow a prescribed path. The proposed hierarchical control strategy consists of two control levels: a high level controller at the intersection and a decentralized low level controller in each car. In the hierarchical control architecture, the centralized intersection controller estimates the target velocity for each approaching connected vehicle to avoid red light stop based on the signal phase and timing (SPAT) information. Each connected vehicle as a decentralized controller utilizes model predictive control (MPC) to track the target velocity in a fuel efficient manner. The main objective in this paper is to consider mandatory lane changes. As in the realistic scenarios, vehicles are not required to drive in single lane. More specifically, they more likely change their lanes prior to signals.

The emphasis on vehicle fuel economy and tailpipe emissions, coupled with a trend toward greater system functionally, has prompted automotive engineers to develop on-board control systems with increased requirements and complexity. Mainstream engine controllers regulate fuel, spark, and other subsystems using custom solutions that incorporate off-the-shelf hardware components. Although the digital processor core and the peripheral electronics may be similar, these controllers are targeted to fixed engine architectures which limit their flexibility across vehicle platforms. Moreover, additional software needs are emerging as electronics continue to permeate the ground transportation sector. Thus, automotive controllers will be required to assume increased responsibility while effectively communicating with distributed hardware modules.

The purpose of this research is to characterize the wear resistance of wheel treads made of polymeric woven and non-woven fabrics. Experimental research is used to characterize two wear mechanisms: (1) external wear due to large sliding between the tread and rocks, and (2) external wear due to small sliding between the tread and abrasive sand. Experimental setups include an abrasion tester and a small-scale merry-go-round where the tread is attached to a deformable rolling wheel. The wear resistance is characterized using various measures including, quantitatively, by the number of cycles to failure, and qualitatively, by micro-visual inspection of the fibers’ surface. This paper describes the issues related to each experiment and discusses the results obtained with different polymeric materials, fabric densities and sizes. The predominant wear mechanism is identified and should then be used as one of the criteria for further design of the tread.

This paper discusses a compliant link suspension concept developed for use on a high performance automobile. This suspension uses compliant or flexible members to integrate energy storage and kinematic guidance functions. The goal of the design was to achieve similar elasto-kinematic performance compared to a benchmark OEM suspension, while employing fewer components and having reduced mass and complexity, and potentially providing packaging advantages. The proposed suspension system replaces a control arm in the existing suspension with a ternary supported compliant link that stores energy in bending during suspension vertical motion. The design was refined iteratively by using a computational model to simulate the elasto-kinematic performance as the dimensions and attachment point locations of the compliant link were varied, until the predicted performance closely matched the performance of the benchmark suspension.