Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Drives”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,009 records · Page 56

Motor and drive arrangement for refrigeration system

A heat exchanger system includes a heat exchanger coil circulating a first heat transfer fluid therethrough, and a fan at least partially surrounded by the heat exchanger coil to urge a flow of air through the heat exchanger coil to dissipate thermal energy from the first heat transfer fluid. A brushless direct current fan motor is located the fan to urge rotation of the fan and an ancillary electrical component operably connected to the heat exchanger system and electrically isolated from the first heat transfer fluid.

Feng, Yinshan↗

Cooling methods for medium voltage drive systems

In one aspect, a medium voltage power converter includes a cabinet having: a power cube bay to house a plurality of power cubes, each of the plurality of power cubes adapted within a corresponding enclosure and comprising a low frequency front end stage, a DC link and a high frequency back end stage, the plurality of power cubes to couple to a high speed machine; and a plurality of first barriers adapted to isolate and direct a first flow of cooling air through one of the plurality of power cubes; and a transformer bay having at least one transformer to couple between a utility connection and the plurality of power cubes, the transformer bay including a plurality of cooling fans to cool the at least one transformer.

Ledezma, Enrique↗

Data-driven estimation of energy consumption for electric bus under real-world driving conditions

Reliable and accurate estimation of an electric bus’s instantaneous energy consumption is critical in evaluating energy impacts of planning and control of electric bus operations. In this study, we developed machine learning-based long short-term memory (LSTM) and artificial neural network (ANN) models to estimate 1 Hz energy consumption of electric buses based on continuous monitoring data of electric buses in Chattanooga, Tennessee, in 2019 and 2020. We propose a data-partitioning algorithm to separate energy charging and discharging modes before applying data-driven estimation models. Here, a K-fold cross-validation-based model selection process was conducted to identify the optimal model structure and input variables in terms of prediction accuracy. The estimation results show the predicted mean absolute percentage error rates of LSTM and ANN models were 3% and 5%, respectively. We compared the proposed models with existing models in the literature based on the same testing data to demonstrate the predictability of our models.

Artificial neural network↗

Push-pull circuit with driving assisted by asymmetric charge sharing

A push-pull circuit for an opto-electronic device includes: an output node; a pull-up circuit that, in operation, controls a falling edge rate of an input signal to the opto-electronic device while sharing charge with the output node; and a pull-down circuit that, in operation, controls a rising edge rate of the input signal to the opto-electronic device while sharing charge with the output node.

Zhu, Zhubiao↗

DC input current ripple reduction in SRM drive for high volumetric power density applications

A control system for a switched reluctance machine includes a capacitor and an inverter connected to the capacitor, wherein the inverter generates current signals and a ripple current returned to the capacitor. A switched reluctance machine (SRM) receives the current signals and generates a position signal. A controller receives the ripple current, current signal values of the current signals, and the position signal and generates desired reference current waveforms received by the inverter to adjust the current signals received by the SRM.

Sozer, Yilmaz↗

Transforming Energy Through Computational Excellence: A Virtual Test-Drive of Energy Scenarios

Researchers at the National Renewable Energy Laboratory (NREL) are conducting groundbreaking research to decarbonize transportation systems and reduce emissions. As they plan for growing populations and related demands on aging infrastructure and energy systems, local transportation departments and city planners are facing significant, complex challenges. New approaches to planning and operations, as well as capitalizing on rapidly advancing technology, can address mobility and energy-centric challenges, including cost and energy efficiency, emissions reduction, decarbonization, and congestion.

33 ADVANCED PROPULSION SYSTEMS↗