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The Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model incorporated fuel economy and electricity use of alternative fuel/vehicle systems simulated by the Powertrain System Analysis Toolkit (PSAT) to conduct a well-to-wheels (WTW) analysis of energy use and greenhouse gas (GHG) emissions of plug-in hybrid electric vehicles (PHEVs). Based on PSAT simulations of the blended charge depleting (CD) operation, grid electricity accounted for a share of the vehicle’s total energy use ranging from 6% for PHEV 10 to 24% for PHEV 40 based on CD vehicle mile traveled (VMT) shares of 23% and 63%, respectively. Besides fuel economy of PHEVs and type of on-board fuel, the type of electricity generation mix impacted the WTW results of PHEVs, especially GHG emissions.

Many Small Unmanned Aerial Vehicles (SUAV) are driven by small scale, fixed blade propellers. Flow produced by the propeller can have a significant impact on the aerodynamics of a SUAV. Therefore, in Computational Fluid Dynamic (CFD) simulations, it is often necessary to simulate the SUAV and propeller coupled together. For computational efficiency, the propeller can be modeled in a steady-state view by using momentum source terms to add the thrust and swirl produced by the propeller to the flow field. Many momentum source term models are based on blade element theory. Blade element theory divides the blade into element sections in the spanwise direction and assumes each element to operate independently as a two-dimensional (2D) airfoil.

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.

EcoCAR 2: Plugging In to the Future is a three-year design competition co-sponsored by General Motors and the Department of Energy. Mississippi State University has designed a plug-in hybrid powertrain for a 2013 Chevrolet Malibu vehicle platform. This vehicle will be capable of 57 miles all-electric range and utility-factor corrected fuel economy of greater than 80 miles per gallon gasoline equivalent (mpgge). All modifications are designed without sacrificing any of the vehicle's utility or performance. Advanced modeling, simulation, and Hardware-in-the-Loop (HIL) simulation capabilities are being used for rapid control prototyping and vehicle design to ensure success in the following years of the competition.

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.

In this work, a process-structure-property relationship for additively manufactured Al-Si-Mg alloy was constructed, with the aid of an integrated multi-physics model. Specifically, first, a series of thermal simulations were performed to understand molten pool geometry under different additive manufacturing (AM) operating conditions, including laser beam power, scanning speed, and hatch spacing. The porosity formation was predicted based on thermal simulation results, which yield molten pool dimension information for predicting the lack-of-fusion porosity. Dream.3D was utilized to reconstruct synthetic microstructures with different volume fraction of porosity.

The current research conducted a cross-validation between an infrared motion capture system and an electromechanical motion capture device. No differences were found between the motion capture methods in shoulder and elbow angles. However, differences were found between the motion capture methods on distances of hand movements and actor location in space. Results of the current study indicate electromechanical motion capture devices are too inaccurate to use for validating digital human models unless the ultimate application of the model does not require millimeter accuracy or an absolute location in space. If one is primarily interested in joint angles, and distances are secondary, an electromechanical device is acceptable.

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.

The advantages of having higher stiffness to weight ratio and strength to weigh ratio that composite materials have resulted in an increased interest in them. In automotive engineering, the weight savings has positive impacts on other attributes like fuel economy and possible noise, vibration and harshness (NVH). The driveline of an automotive system can be a target for possible use of composite materials. The design of the driveshaft of an automotive system is primarily driven by its natural frequency. This paper presents an exact solution for the vibration of a composite driveshaft with intermediate joints. The joint is modeled as a frictionless internal hinge. The Euler-Bernoulli beam theory is used. Lumped masses are placed on each side of the joint to represent the joint mass. Equations of motion are developed using the appropriate boundary conditions and then solved exactly.

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.

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.

A time-resolved x-radiographic technique has been employed for measuring the fuel distribution close to a single-hole nozzle fitted in a high-pressure diesel injector. Using a monochromatic synchrotron x-ray beam, it is possible to perform quantitative x-ray absorption measurements and obtain two-dimensional projections of the mass of the fuel spray. We have completed a series of spray measurements in the optically dense, near-nozzle region (< 15 mm from the nozzle orifice) under ambient pressures of 1, 2, and 5.2 bar N2 and 1 bar SF6 at room temperature with injection pressures of 500 and 1000 bar. The focus of the measurements is on the dynamical behaviors of the fuel jets with an emphasis on their penetration in the near-nozzle region. Careful analysis of the time-resolved x-radiographic data revealed that the spray penetration in this near nozzle region was not significantly affected by the limited change of the ambient pressure.

The substitution of lightweight materials, such as aluminum or magnesium alloys, to produce lightweight car bodies, has been the subject of intensive research in resent years. It has been established that an aluminum body is lighter than a steel body for constant stiffness. The causes of this weight reduction have not been established. In particular, since the specific modulus (modulus of elasticity/density) of steel, aluminum and magnesium are nearly identical, there is no easy answer for their ability to reduce weight. In this paper, it is shown that there are stress concentrations in thin walled structures, which are dependent on the thickness of the material. These stress concentrations appear in joints and other parts with complex geometry and loading conditions. For example, the flanges on a curved beam in flexure have an effective (load bearing) width, which increases as the material is thickened.

The concept of a structural index, λ, is developed using the simple example of a hollow beam with a cantilever load case. It is assumed that when performing material substitution, only the thickness, t, is changed. It is shown that the stiffness, K, of the beam can be defined as a function of tλ, that 1 ≤ λ ≤ 3, and that λ can be used to predict the weight savings from material substitution where stiffness is held constant. It is then demonstrated that λ can be used to predict the weight savings from material substitution in the more complex cases of the joints of a light truck cab.

In 1994, Ford produced a small demonstration fleet of Mercury Sables with aluminum bodies. Argonne National Laboratory obtained one of these vehicles on a lease so that Laboratory staff could observe the wear characteristics of the body under normal operating conditions. The vehicle was placed in the transportation pool, parked outdoors, and used by staff members for both local and longer trips. The vehicle performed normally, except for having particularly good acceleration because of its light weight and high-power SHO engine. No significant problems were encountered that related to the Al body or engine. No special driving protocols were observed, but a log was kept of trip lengths and fuel purchases. Fuel economy was observed to be improved, compared with that of a similar conventional steel-bodied vehicle that was available for one year of the lease period. The vehicle was tested on a chassis dynamometer to obtain emissions and fuel economy over the federal test cycle.

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.

Although the cost-saving and good environmental impacts are the benefits that make Electric Vehicles (EVs) popular, these advantages are significantly influenced by the cost of battery replacement over the vehicle lifetime. After several charging and discharging cycles, the battery is subjected to energy and power degradation which affects the performance and efficiency of the vehicle. In addition to battery replacement cost, the electricity cost being paid by drivers is another key factor in selecting the EVs. An Energy Management System (EMS) with Model Predictive Control-based (MPC) algorithm is presented for a specific case of heavy-duty EV. Such EV draws its energy from the grid via catenary in addition to the on-board battery. Dynamic model of the vehicle will be defined by State Space Equations (SSE).

A cost effective, portable particulate management system was developed, prototyped, and evaluated for further application and commercialization, which could remove and dispose particulate matter suspended in air efficiently and safely. A prototype of the present system was built for experimental assessment and validation. The experimental data showed that the developed particulate management system can effectively clean the air by capturing the particles inside it. Effects of viscosity of filter medium on the performance of the developed system were also discussed. The present system is very flexible, whose size and shape can be scaled and changed to be fit for different applications. Its manufacturing cost is less than $10. Based on the experimental validation results, it was found that the present system can be further developed, commercialized, and applied for a variety of industries.

A dynamic modeling framework was established to predict status (position, displacement, velocity, acceleration, and shape) of a towed vehicle system with different driver inputs. This framework consists of three components: (1) a state space model to decide position and velocity for the vehicle system based on Newton’s second law; (2) an angular acceleration transferring model, which leads to a hypothesis that the each towed unit follows the same path as the towing vehicle; and (3) a polygon model to draw instantaneous polygons to envelop the entire system at any time point. Input parameters of this model include initial conditions of the system, real-time locations of a reference point (e.g. front center of the towing vehicle) that can be determined from a beacon and radar system, and instantaneous accelerations of this system, which come from driver maneuvers (accelerating, braking, steering, etc.) can be read from a data acquisition system installed on the towing vehicle.