Search Results

The CFD tools in aerodynamic design process have been commonly used in aerospace industry in last three decades. Although there are many CFD software algorithms developed for aerodynamic applications, the nature of a complex, three-dimensional geometry in incompressible highly separated, viscous flow made computational simulation of ground vehicle aerodynamics more difficult than aerospace applications. However, recent developments in computational hardware and software industry enabled many new engineering applications on computational environment. Traditional production process has largely influenced by computational design, analysis, manufacturing and visualization. Different aspects of linking advanced computational tools and aerodynamic vehicle design challenges are discussed in the present work. Key technologies like parallel computation, turbulence modeling and CFD/wind tunnel compatibility issues are presented.

The reasons for conducting research in a university are presented and discussed. It is concluded that fuel-engine studies are compatible with these reasons and therefore are well suited for university research. Past studies in this field are summarized and unanswered questions and future topics suitable for university investigation are suggested. Included in the topics discussed are: instrumentation, thermodynamic description of working fluids, fuel vaporization and atomization, combustion, and instantaneous heat transfer and mass flow rates. The steps that need to be taken to ensure continuing university interest in fuel-engine studies are presented.

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.

Increasingly sophisticated vehicle automation can perform steering and speed control, allowing the driver to disengage from driving. However, vehicle automation may not be capable of handling all roadway situations and driver intervention may be required in such situations. The typical approach is to indicate vehicle capability through displays and warnings, but control algorithms can also signal capability. Psychophysical methods can be used to link perceptual experiences to physical stimuli. In this situation, trust is an important perceptual experience related to automation capability that is revealed by the physical stimuli produced by different control algorithms. For instance, precisely centering the vehicle in the lane may indicate a highly capable system, whereas simply keeping the vehicle within lane boundaries may signal diminished capability.