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This manuscript presents a systematic approach for the design and development of a 403 V, 7 kWh battery pack for a Formula SAE student racing electric car. The pack is made up of 6 individual segments which are connected in series. Each segment has a maximum energy of 1.17 kWh and is made up of 16 arrays connected in series. Each array holds 8 Lithium-ion batteries which are connected in parallel. The overall design of the battery pack is in full compliance with the Formula SAE rules. The manuscript presents the calculation procedure and battery sizing for the power demand of a typical Formula SAE student racing electric car using vehicle dynamics equations. The entire electric traction system is modelled in Matlab/Simulink. The paper also explains the development process of the 7 kWh battery pack and highlights important design considerations, such as busbar sizing.

The thermal comfort inside automotive cabin has been extensively studied for decades. Traditional CFD models provide accurate simulation results of the air temperature distributions inside cabins but at a relatively high computation cost. In order to reduce the computational cost while still providing reasonable accuracy in simulating the air temperature profile inside a mid-sized sedan cabin, this paper introduces a new simulation tool that utilizes a proper orthogonal decomposition (POD) method. The POD method, an interpolation technique, requires only one set of multiple CFD simulations to produce a set of “snapshots”. Later, any simulations that require CFD runs to solve algorithm equation sets can be simplified by using interpolation between the snapshots provided that the geometry of the cabin keeps the same. As a result, the computation time can be reduced to only a few minutes.

The University of Maryland FutureTruck Team has redesigned a 2002 Ford Explorer to function as a charge-sustaining parallel hybrid electric vehicle for the 2002-2003 FutureTruck competition. Dubbed the Excite, it is powered by a dedicated E85 3.0L V6 engine coupled to a 21.6 kW peak (10kW continuous), electric motor using a 144V NiMH battery pack. The philosophy behind the UMD plan is to use a smaller, lightweight, dedicated E85 engine in parallel with an electric motor to provide starting and mild assist capabilities. The engine provides similar power to the stock 4.0 L Explorer engine and the electric motor functions as a starter, an alternator, and assists the engine during high power demands. The combination of the two systems provides the Excite with engine-off-at-idle capability, increased efficiency and fuel economy, and decreased emissions while maintaining the utility of a stock SUV.

The University of Maryland team converted a model year 2000 Chevrolet Suburban to an ethanol-fueled hybrid-electric vehicle (HEV) and tied for first place overall in the 2000 FutureTruck competition. Competition goals include a two-thirds reduction of greenhouse gas (GHG) emissions, a reduction of exhaust emissions to meet California ultra-low emissions vehicle (ULEV) Tier II standards, and an increase in fuel economy. These goals must be met without compromising the performance, amenities, safety, or ease of manufacture of the stock Suburban. The University of Maryland FutureTruck, Proteus, addresses the competition goals with a powertrain consisting of a General Motors 3.8-L V6 engine, a 75-kW (100 hp) SatCon electric motor, and a 336-V battery pack. Additionally, Proteus incorporates several emissions-reducing and energy-saving modifications; an advanced control strategy that is implemented through use of an on-board computer and an innovative hybrid-electric drive train.

The potential for thermoelectric power generation via waste heat recovery onboard automobiles to displace alternators and/or provide additional charging to a hybrid vehicle battery pack has increased with recent advances in thermoelectric materials processing. A preliminary design/modeling study was performed to optimize waste heat recovery for power generation using a modified radiator incorporating thermoelectric modules. The optimization incorporates not only thermoelectric performance but also critical systems issues such as accessory power consumption, vehicle drag, and added system weight. Results indicate the effectiveness of the thermoelectric module is extremely sensitive to ambient heat rejection and to the operating temperature range of the thermoelectric device.

In low earth orbit satellite applications, spacecraft power is provided by photovoltaic cells and batteries. Unfortunately, use of batteries present difficulties due to their poor energy density, limited cycle lifetimes, reliability problems, and the difficulty in measuring the state of charge. Flywheel energy storage offers a viable alternative to overcome some of the limitations presented by batteries. FARE, Inc. has built a 50 Wh flywheel energy storage system. This system, called the Open Core Flywheel, is intended to be a prototype energy storage device for low earth orbit satellite applications. To date, the Open Core Flywheel has achieved a rotational speed of 26 krpm under digital control.

A mathematical model of combustion process in a diesel engine has been developed according to the theory of the chain reactions for the higher hydrocarbon compounds. The instantaneous rates of fuel vaporization and combustion are defined by the current values of temperature, pressure, concentration of fuel vapors, overall diffusion rate, fuel injection rate, and mean fuel droplet size in terms of the SMD. Numerical experiments have been carried out for investigating the interdependencies between various combustion-related parameters. Specifically, the effect of fuel droplet size (in terms of SMD) on the subsequent combustion parameters, such as, pressure, temperature, thermodynamic properties of air/gas mixture, heat transfer, fuel vaporization, combustion rate, current A/F ratio, gas mixture composition have been investigating. In addition, the integral indicator parameters of the engine, such as the mean indicated pressure, peak pressure, compression pressure have been analyzed.

The control and analysis of magnetic bearings has been primarily based upon classical linear control theory. This approach does not allow for some important system complexities and nonlinearities to be taken into account. The resulting simplifications degrade the overall system performance. This paper investigates the use of a neural network to control a magnetic bearing flywheel energy storage system. A plant simulation is developed as well as a neural network emulator and controller.

AMBER (Active Magnetic Bearing Evaluation Routine) is a computer algorithm developed for the University of Maryland pancake magnetic bearing, which supports and controls a flywheel in a kinetic energy storage system. Because of the gap growth due to centrifugal forces at high speed, the bearing axial load capability degrades and the axial characteristics become critical in the bearing design. AMBER applies magnetic circuit theory, magnetic material saturation curves, coenergy theory, and finite permeance-based elements to solve the air gap flux density and coenergy over a series of incremental axial displacements. Differentiation of the coenergy of the magnetic field yields axial force and stiffness characteristics. An axial test machine is constructed to conduct experiments to verify the flux distribution and axial forces predicted by the model. User interaction with AMBER allows modification of the bearing geometry and composition to optimize future prototypes.