Modeling of Digital-Displacement Pump-Motors and Their Application as Hydraulic Drives for Nonuniform Loads

1997 ◽  
Vol 122 (1) ◽  
pp. 210-215 ◽  
Author(s):  
Md. Ehsan ◽  
W. H. S. Rampen ◽  
S. H. Salter
Keyword(s):  
Energy Efficiency ◽  
Time Domain ◽  
Motor System ◽  
Response Speed ◽  
Domain Modeling ◽  
Variable Speed ◽  
Variable Flow ◽  
Hybrid Device ◽  
Displacement Pump ◽  
Time Domain Modeling

The digital-displacement pump-motor is a hybrid device, which combines reciprocating hydraulics with micro-processor control, creating a highly integrated machine capable of producing variable flow and power. It is based on the conventional hydraulic piston pump but with actively controlled poppet valves for each cylinder. This allows enabling or disabling on a stroke-by-stroke basis in any desired sequence. Time-domain modeling of the pump-motor system predicts the performance under variable-demand, variable-speed at different control-modes. The advantages of this approach over conventional techniques lie with both the response speed and the inherent energy efficiency. [S0022-0434(00)00801-7]

scholarly journals Feasibility of Black-Box Time Domain Modeling of Single-Phase Photovoltaic Inverters Using Artificial Neural Networks

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2118
Author(s):  
Elias Kaufhold ◽  
Simon Grandl ◽  
Jan Meyer ◽  
Peter Schegner
Keyword(s):  
Time Domain ◽  
Single Phase ◽  
Low Voltage ◽  
Black Box ◽  
Steady States ◽  
Domain Modeling ◽  
Dynamic Simulations ◽  
Time Domain Modeling ◽  
Artificial Neural ◽  
Grid Side

This paper introduces a new black-box approach for time domain modeling of commercially available single-phase photovoltaic (PV) inverters in low voltage networks. An artificial neural network is used as a nonlinear autoregressive exogenous model to represent the steady state behavior as well as dynamic changes of the PV inverter in the frequency range up to 2 kHz. The data for the training and the validation are generated by laboratory measurements of a commercially available inverter for low power applications, i.e., 4.6 kW. The state of the art modeling approaches are explained and the constraints are addressed. The appropriate set of data for training is proposed and the results show the suitability of the trained network as a black-box model in time domain. Such models are required, i.e., for dynamic simulations since they are able to represent the transition between two steady states, which is not possible with classical frequency-domain models (i.e., Norton models). The demonstrated results show that the trained model is able to represent the transition between two steady states and furthermore reflect the frequency coupling characteristic of the grid-side current.

Time-domain Modeling of Constant-Q Seismic Waves Using Fractional Derivatives

2002 ◽  
pp. 1719-1736 ◽  
Author(s):  
José M. Carcione ◽  
Fabio Cavallini ◽  
Francesco Mainardi ◽  
Andrzej Hanyga
Keyword(s):  
Time Domain ◽  
Fractional Derivatives ◽  
Seismic Waves ◽  
Domain Modeling ◽  
Time Domain Modeling
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