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Navitas Showcases Pure-Play WBG Solutions for EV at ECCE - Vimarsana News

Navitas Showcases Pure-Play WBG Solutions for EV at ECCE

Industry-leading, high-speed GaNFast™ and GeneSiC™ technologies deliver energy savings, faster charging, extended range, and lower system costs...

Anticipating Complex Network Issues Through the Use of Advanced Simulation Models - Vimarsana News

Anticipating Complex Network Issues Through the Use of Advanced Simulation Models

Introduction Wind energy penetration in the transmission networks has been steadily increasing during the last decades. This situation causes integration

QM Power and University of Kentucky demonstrate 50 kW/liter electric motor; DOE 2025 power density goal - Vimarsana News

QM Power and University of Kentucky demonstrate 50 kW/liter electric motor; DOE 2025 power density goal

QM Power and the SPARK Lab at University of Kentucky shared the combined results of a large-scale, multi-objective design optimization study, and lab testing of a prototype motor designed to meet the 2025 power density goals set by the US Department of Energy (DOE). The research demonstrated the high torque...

QM Power and University of Kentucky Achieve Ambitious Electric Motor Goal - Vimarsana News

QM Power and University of Kentucky Achieve Ambitious Electric Motor Goal

/PRNewswire/ -- QM Power and the SPARK Lab at University of Kentucky shared the combined results of a large-scale, multi-objective design optimization study,...

Using machine learning to solve engineering challenges | WSU Insider - Vimarsana News

Using machine learning to solve engineering challenges | WSU Insider

January 27, 2021 Designing safe and workable autonomous, electric-powered flight is a complex engineering problem. To use electric power instead of fossil fuels to fly requires systems that are light, use a minimum amount of energy, make proper flying decisions, and are safe. Even a relatively simple UAV can have hundreds of thousands of design possibilities for its power system, only a few of which are the best for maximizing safety and efficiency. A WSU research team recently developed and used a machine learning algorithm to find the five optimal designs out of about 250,000 possible desig...

Source: wsu.edu