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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.

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.

Supercharger gear whine noise has been a NVH concern for many years, especially around idle rpm. The engine masking noise is very low at idle and the supercharger is sensitive to transmitted gear whine noise from the timing gears. The low loads and desire to use spur gears for ease in timing the rotors have caused the need to make very accurate profiles for minimizing gear whine noise. Over the past several years there has been an effort to better understand gear whine noise source and transmission path. Based on understanding the shaft bending mode frequencies and better gear design optimization tools, the gear design was modified to increase the number of teeth in order to move out of the frequency range of the shaft bending modes at idle speed and to lower the transmission error of the gear design through optimization using the RMC (Run Many Cases) software from the OSU gear laboratory.

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 discusses the effect of torque vectoring differential on improving vehicle handling and stability performance. The torque vectoring concept has been analyzed. The vehicle discussed in this paper is an AWD vehicle with torque vectoring differential in the rear and a torque biasing center differential. First, simulation results with vehicle model in CarSim® and torque vectoring control algorithm in Matlab®/Simulink® is discussed. Then, experimental results for vehicle tested at winter and summer test facility is presented. Both simulation and experimental results demonstrate the effectiveness of torque vectoring differential on vehicle handling & stability.

The effects of downspeeding and supercharging a passenger car diesel engine were studied through laboratory investigation and vehicle simulation. Changes in the engine operating range, transmission gearing, and shift schedule resulted in improved fuel consumption relative to the baseline turbocharged vehicle while maintaining performance and drivability metrics. A shift schedule optimization technique resulted in fuel economy gains of up to 12% along with a corresponding reduction in transmission shift frequency of up to 55% relative to the baseline turbocharged configuration. First gear acceleration, top gear passing, and 0-60 mph acceleration of the baseline turbocharged vehicle were retained for the downsped supercharged configuration.

This study examines the performance and subject acceptance level of a hand-operated brake actuator. Using a fixed-base vehicle simulator, data for driver reaction time, stopping time, distance, deceleration, customer acceptance and mental workload were collected. Data for three prototype hand-operated brake actuators and traditional foot-operated brake were compared. An additional test, designed to evaluate anthropometrics, sensitivity, and comfort was performed during training. A user preference survey to determine handbrake acceptance was given to subjects after completing the driving test in the simulator. In certain trials, participants were given the choice of handbrake or footbrake for an unexpected stop condition. When placed into an unexpected braking situation, subjects showed faster brake-application times for operating the hand-operated brake, indicating potential for reduced braking distance.

EcoCAR 2: Plugging In to the Future (EcoCAR) is North America's premier collegiate automotive engineering competition, challenging students with systems-level advanced powertrain design and integration. The three-year Advanced Vehicle Technology Competition (AVTC) series is organized by Argonne National Laboratory, headline sponsored by the U. S. Department of Energy (DOE) and General Motors (GM), and sponsored by more than 28 industry and government leaders. Fifteen university teams from across North America are challenged to reduce the environmental impact of a 2013 Chevrolet Malibu by redesigning the vehicle powertrain without compromising performance, safety, or consumer acceptability. During the three-year program, EcoCAR teams follow a real-world Vehicle Development Process (VDP) modeled after GM's own VDP. The VDP serves as a roadmap for the engineering process of designing, building and refining advanced technology vehicles.

The EcoCAR Mobility Challenge (EMC) is the latest edition of the Advanced Vehicle Technology Competition (AVTC) series sponsored by the US Department of Energy. This competition challenges 11 North American universities to redesign a stock 2019 Chevrolet Blazer into an energy-efficient, SAE level 2-autonomous mild hybrid electric vehicle (mHEV) for use in the Mobility as a Service (MaaS) market. The Mississippi State University (MSU) team designed a P4 electric powertrain with an 85kW (113.99 HP) permanent magnet synchronous machine (PMSM) powered by a custom 5.4 kWh lithium-ion energy storage system. To maximize energy efficiency, Model Based Design concepts were leveraged to optimize the overall gear ratio for the P4 system. To accommodate this optimized ratio in the stock vehicle, a custom offset gearbox was designed that links the PMSM to the rear drive module.

A common interaction between a penetrator and a target has been the use of copper and nickel materials. However, a multiscale analysis has not been performed on such a system. Compared to steels, aluminum alloys, titanium alloys and other metallic materials, a description of the mechanical behavior of pure ductile metals such as Cu struck by a penetrator comprises nickel under the high strain rate at different multiscale still remains unknown. In this research, Modified Embedded Atom Method (MEAM) Potential is utilized to study this system and the molecular dynamics simulation is employed in order to provide structure property evolution information for plasticity and shearing mechanisms.