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A Location-Aware Adaptive Vehicle Dynamics System (LAAVDS) is developed to assist the driver in maintaining vehicle handling capabilities through various driving maneuvers. An integral part of this System is an Intervention Strategy that uses a novel measure of handling capability, the Performance Margin, to assess the need to intervene. Through this strategy, the driver's commands are modulated to affect desired changes to the Performance Margin in a manner that is minimally intrusive to the driver's control authority. Real-time implementation requires the development of computationally efficient predictive vehicle models. This work develops one means to alter the future vehicle states: modulating the driver's brake commands. This control strategy must be considered in relationship to changes in the throttle commands. Three key elements of this strategy are developed in this work.

A Location-Aware Adaptive Vehicle Dynamics System (LAAVDS) is developed to assist the driver in maintaining vehicle handling capabilities through various driving maneuvers. An Intervention Strategy uses a novel measure of handling capability, the Performance Margin, to assess the need to intervene. The driver's commands are modulated to affect desired changes to the Performance Margin in a manner that is minimally intrusive to the driver's control authority. Real-time implementation requires the development of computationally efficient predictive vehicle models which is the focus of this work. This work develops one means to alter the future vehicle states: modulating the driver's throttle commands. First, changes to the longitudinal force are translated to changes in engine torque based on the current operating state (torque and speed) of the engine.

Studying the kinetic and kinematics of the rim-tire combination is very important in full vehicle simulations, as well as for the tire design process. Tire maneuvers are either quasi-static, such as steady-state rolling, or dynamic, such as traction and braking. The rolling of the tire over obstacles and potholes and, more generally, over uneven roads are other examples of tire dynamic maneuvers. In the latter case, tire dynamic models are used for durability assessment of the vehicle chassis, and should be studied using high fidelity simulation models. In this study, a three-dimensional finite element model (FEM) has been developed using the commercial software package ABAQUS. The purpose of this study is to investigate the tire dynamic behavior in multiple case studies in which the transient characteristics are highly involved.

Modeling the tire forces and moments (F&M) generation, during combined slip maneuvers, which involves cornering and braking/driving at the same time, is essential for the predictive vehicle performance analysis. In this study, a new semi-empirical method is introduced to estimate the tire combined slip F&M characteristics based on flat belt testing machine measurement data. This model is intended to be used in the virtual tire design optimization process. Therefore, it should include high accuracy, ease of parameterization, and fast computational time. Regression is used to convert measured F&M into pure slip multi-dimensional interpolant functions modified by weighting functions. Accurate combined slip F&M predictions are created by modifying pure slip F&M with empirically determined shape functions. Transient effects are reproduced using standard relaxation length equations. The model calculates F&M at the center of the contact patch.

Research interests in autonomous driving have increased significantly in recent years. Several methods are being suggested for performance optimization of autonomous vehicles. However, weather conditions such as rain, snow, and fog may hinder the performance of autonomous algorithms. It is therefore of great importance to study how the performance/efficiency of the underlying scene understanding algorithms vary with such adverse scenarios. Semantic segmentation is one of the most widely used scene-understanding techniques applied to autonomous driving. In this work, we study the performance degradation of several semantic segmentation algorithms caused by rain for off-road driving scenes. Given the limited availability of datasets for real-world off-road driving scenarios that include rain, we utilize two types of synthetic datasets.

This paper describes a real time application of mechatronics with constructional details along with simulation results. Applications like part tracking and automatic speed control are of interest to the industry and the academic alike. Based on certain specific information about the system a control program is prepared and embedded in a microcontroller, so that it responds repetitively to various input parameters. To widen the range of control, it is necessary that a huge database of input-output information has to be provided to the microcontroller. In this paper, different sensing and actuating elements and details of microcontrol programming are presented with reference to typical applications such as component recognition strategy using a vision system, a remote controlled mobile robot, tracking system of moving components, and automatic speed control of laboratory diesel engine model. Some simulation results of the control are also presented.

Models for off-road vehicles, such as farm equipment and military vehicles, require an off-road tire model in order to properly understand their dynamic behavior on off-road driving surfaces. Extensive literature can be found for on-road tire modeling, but not much can be found for off-road tire modeling. This paper presents an off-road tire model that was developed for use in vehicle handling studies. An on-road, dry asphalt tire model was first developed by performing rolling road force and moment testing. Off-road testing was then performed on dirt and gravel driving surfaces to develop scaling factors that explain how the lateral force behavior of the tire will scale from an on-road to an off-road situation. The tire models were used in vehicle simulation software to simulate vehicle behavior on various driving surfaces. The simulated vehicle response was compared to actual maximum speed before sliding vs. turning radius data for the studied vehicle to assess the tire model.

One seminal question that faces a vehicle's driver (either human or computer) is predicting the capability of the vehicle as it encounters upcoming terrain. A Location-Aware Adaptive Vehicle Dynamics (LAAVD) System is developed to assist the driver in maintaining vehicle handling capabilities through various driving maneuvers. In contrast to current active safety systems, this system is predictive rather than reactive. This work provides the conceptual groundwork for the proposed system. The LAAVD System employs a predictor-corrector method in which the driver's input commands (throttle, brake, steering) and upcoming driving environment (terrain, traffic, weather) are predicted. An Intervention Strategy uses a novel measure of handling capability, the Performance Margin, to assess the need to intervene. The driver's throttle and brake control are modulated to affect desired changes to the Performance Margin in a manner that is minimally intrusive to the driver's control authority.

There is significant potential for connected and autonomous vehicles to impact vehicle efficiency, fuel economy, and emissions, especially for hybrid-electric vehicles. These improvements could have large-scale impact on oil consumption and air-quality if deployed in large Mobility-as-a-Service or ride-sharing fleets. As part of the US Department of Energy's current Advanced Vehicle Technology Competition (AVCT), EcoCAR: The Mobility Challenge, Mississippi State University’s EcoCAR Team is redesigning and doing the development work necessary to convert a conventional gasoline spark-ignited 2019 Chevy Blazer into a hybrid-electric vehicle with SAE Level 2 autonomy. The target consumer segments for this effort are the Mobility-as-a-Service fleet owners, operators and riders. To accomplish this conversion, the MSU team is implementing a P4 mild hybridization strategy that is expected to result in a 30% increase in fuel economy over the stock Blazer.

Recently [1, 2, 3 and 4], the novel Advanced (injection) Low Pilot-Ignited Natural Gas (ALPING) low-temperature combustion (LTC) concept was demonstrated to yield very low NOx emissions (<0.2 g/kWh) with high fuel conversion efficiencies (>40%). In the ALPING-LTC concept, very small diesel pilot sprays (contributing ∼2-3 percent of total fuel energy) are injected early in the compression stroke (60°BTDC) to ignite lean, homogeneous natural gas-air mixtures. To simulate ALPING-LTC, a phenomenological thermodynamic model was developed. The cylinder contents were divided into an unburned zone containing fresh natural gas-air mixture, several packets containing diesel and entrained natural gas-air mixture, a flame zone, and a burned zone. The simulation explicitly accounted for pilot injection, spray entrainment, diesel ignition (with the Shell autoignition model), spray combustion of diesel and entrained natural gas, and premixed turbulent combustion of the natural gas-air mixture.

The Mississippi State Challenge X team has built a new rear cradle for its 2005 Chevy Equinox hybrid, which allows for the integration of a Ballard electric drive system. The OEM cradle would have required extensive modification for the installation of the Ballard unit. The new cradle will save space by utilizing smaller members with thicker walls, thereby permitting more flexibility in mounting the drive. The team developed a working model of the MSU cradle that serves the duties of the existing cradle and allows the Ballard drive to be installed. Analytical calculations were performed to determine the loads experienced by the cradle during on-road service. A stress analysis was then performed using these loading criteria. The MSU team determined that mechanical testing would be the fastest way to analyze the stiffness of the original part. Two mechanical tests were performed to determine the part's stiffness.

One of the major applications of cam mechanism is valve actuation of Internal Combustion (IC) engines. This work deals with the follower response determination for a given prescribed cam motion for single DOF cam mechanism. Here follower response by two methods are presented first one is using Johnson's numerical method analytically obtained the dynamic response. In the second method transient dynamic analysis is carried out using FEM. Here each method is carried out considering two types of cam motions, parabolic motion and cycloidal motion. The responses of both methods are yielding good agreement.

The Mississippi State University Formula SAE race car upright was optimized using radial basis function metamodels and an internal state variable (ISV) plasticity damage material model. The weight reduction of the upright was part of a goal to reduce the weight of the vehicle by 25 percent. Using an optimization routine provided an upright design that is lighter that helps to improve vehicle fuel economy, acceleration, and handling. Finite element (FE) models of the upright were produced using quadratic tetrahedral elements. Using tetrahedral elements provided a quick way to produce the multiple FE models of the upright required for the multi-objective optimization. A design of experiments was used to determine how many simulations were required for the optimization. The loads for the simulations included braking, acceleration, and corning loads seen by the car under track conditions.

This paper covers the development of a closed loop transaxle synchronization algorithm which was a key deliverable in the control system design for the L3 Enigma, a Battery Dominant Hybrid Electric Vehicle. Background information is provided to help the reader understand the history that lead to this unique solution of the input and output shaft synchronizing that typically takes place in a manual vehicle transmission or transaxle when shifting into a gear from another or into a gear from neutral when at speed. The algorithm stability is discussed as it applies to system stability and how stability impacts the speed at which a shift can take place. Results are simulated in The MathWorks Simulink programming environment and show how traction motor technology can be used to efficiently solve what is often a machine design issue. The vehicle test bed to which this research is applied is a parallel biodiesel hybrid electric vehicle called the Enigma.

Serpentine belt system has been widely used to drive automotive accessories like power steering pump, alternator, and A/C compressor from a crankshaft pulley. Overload under severe conditions can lead to excessive slippage in the belt pulley interface in poorly designed accessory systems. This can lead to undesirable noise that increases warranty cost substantially. The mechanisms and data of these tribology performance, noise features and system response are of utmost interest to the accessory drive designers. As accessories belt systems are usually used in ambient condition, the presence of water on belt is unavoidable under the raining weather conditions. The presence of water in interface induces larger slippage as the water film in interface changes the friction mechanisms in rubber belt-pulley interface from coulomb friction to friction with mixed lubrication that has negative slope of coefficient of friction (cof) - velocity.

This study outlines a protocol for image data collection acquired from human volunteers. The data set will serve as the foundation of a consolidated effort to develop the next generation full-body Finite Element Analysis (FEA) models for injury prediction and prevention. The geometry of these models will be based off the anatomy of four individuals meeting extensive prescreening requirements and representing the 5th and 50th percentile female, and the 50th and 95th percentile male. Target values for anthropometry are determined by literature sources. Because of the relative strengths of various modalities commonly in use today in the clinical and engineering worlds, a multi-modality approach is outlined. This approach involves the use of Computed Tomography (CT), upright and closed-bore Magnetic Resonance Imaging (MRI), and external anthropometric measurements.

This study pertains to motion control algorithms using statistical calculations based on relative displacement measurements, in particular where the rattle space is strictly limited by fixed end-stops and a load leveling system that allows for roll to go undetected by the sensors. One such application is the cab suspension of semi trucks that use widely-spaced springs and dampers and a load leveling system that is placed between the suspensions, near the center line of the cab. In such systems it is possible for the suspension on the two sides of the vehicle to settle at different ride heights due to uneven loading or the crown of the road. This paper will compare the use of two moving average signals (one positive and one negative) to the use of one root mean square (RMS) signal, all calculated based on the relative displacement measurement.

In this paper a yaw stability control algorithm along with an emergency roll control strategy have been developed. The yaw stability controller and emergency roll controller were both developed using linear two degree-of-freedom vehicle models. The yaw stability controller is based on Lyapunov stability criteria and uses vehicle lateral acceleration and yaw rate measurements to calculate the corrective yaw moment required to stabilize the vehicle yaw motion. The corrective yaw moment is then applied by means of a differential braking strategy in which one wheel is selected to be braked with appropriate brake torque applied. The emergency roll control strategy is based on a rollover coefficient related to vehicle static stability factor. The emergency roll control strategy utilizes vehicle lateral acceleration measurements to calculate the roll coefficient. If the roll coefficient exceeds some predetermined threshold value the emergency roll control strategy will deploy.

The finite element method (FEM) is used daily in the automotive industry for such purposes as reducing the time of product development and improving the design based on analysis results, followed by later validation by tests in the laboratory and on the proving ground. This paper will present some of the methodology used to develop automotive components by finite element analysis, including procedures to specialize FEM models to obtain quantitative and qualitative results for systems such as body, chassis, and suspension components, as well as validation of the models by experimental data.

Finite element models of vehicles have been increasingly used in component design and crashworthiness evaluation. As vehicle finite element models are becoming more sophisticated in terms of their accuracy, robustness, fidelity, and size, the need to compare different FEA codes has become more apparent. In this study, we compare finite element simulations of a 1996 Dodge Neon using LS-DYNA and PAM-CRASH codes with an effort to keep sameness of the material models, meshes and boundary conditions. The original Neon mesh and material properties were developed at the FHWA/NHTSA National Crash Analysis Center (NCAC) for LS-DYNA and subsequently modified for this study. The comparisons between test data and simulation results of the full-scale vehicle in terms of overall impact deformation, component failure modes, and velocity and acceleration at various locations in the vehicle show good correlations with only minor discrepancy.