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Electric vehicles (EVs) are experiencing explosive growth in public adoption, causing a major shift in research and development priorities by OEMs toward electrified powertrains. To verify EV drivetrain platforms and software models in the design phase, testbeds with specific capabilities are essential. Full-scale vehicle testbeds are expensive, bulky, dissipative, and not easily reconfigurable or movable, making scaled testbeds more attractive, especially for education and research institutes. To support this cause, this paper reports on the development of a small-scale, modular, hardware-in-the-loop (HIL) testbed platform for the drivetrain of EVs that is cost-effective, efficient, and easily movable and reconfigurable and allows integration of a battery pack. The testbed is comprised of two directly coupled electric machines. The first machine emulates the traction motor and is used to control vehicle speed according to a specified drive cycle. The second machine is used to impose a torque profile on the first machine's shaft—based on the vehicle's parameters and driving environment—and emulates a gearbox (if necessary). A systematic two-way scaling approach is adopted to downscale the parameters and driving environment of full-size EVs to a level that can be handled by the testbed and to upscale the test results obtained from the testbed to the full-size vehicle level. The power consumption of the testbed is limited to system losses. A case study involving a full-size EV was performed and the HIL simulation results were compared to the computer simulation results to verify the performance of the testbed. [ABSTRACT FROM AUTHOR]

Wind farms featuring a series-connected dc collection system have been shown to offer advantages in terms of total conversion efficiency and amount of offshore-deployed equipment. To ensure proper exploitation of these benefits, it is necessary to determine the ratings of wind turbine converters. These ratings must be sufficient to cover the expected operating conditions over the life of the wind farm, without unnecessarily oversizing the equipment. As shown in this article, the variable string current results in an interdependence of operating points among wind turbines that has to be considered for sizing these converters. This article proposes a generic sizing framework for such single-string, series-connected dc wind farms. This framework is applied to three wind farm configurations featuring differential power processing, voltage-source converters, and diode-bridge rectifiers and buck converters. Finally, a case study for a 450 MW offshore wind farm demonstrates the implementation of this sizing methodology and quantifies the design tradeoffs between converter ratings and energy production enabled from those converters. In two of the studied wind farm configurations, significant rating reductions are achievable while still avoiding energy curtailment for >99.7% of the energy production of an equivalent ac wind farm. [ABSTRACT FROM AUTHOR]

Batteries are the most commonly used electrical energy storage devices. The cost and performance of an electric vehicle (EV) are strongly affected by the proper selection of technology, number, and arrangement of the battery cells used. This paper formulates the problem of optimal sizing of the battery unit (BU) for a plug-in EV (PEV), given the specifications of the vehicle, battery cell data, and drive cycle. This paper employs a metaheuristic optimization algorithm to find the optimal size of the BU with the objective of minimizing the overall cost. Feasibility of the optimization results in terms of respecting the constraints is verified via simulation. The developed optimization platform is highly flexible and allows use of different vehicle designs, component data, and drive cycles. [ABSTRACT FROM PUBLISHER]