Trapezoidal Current Generator for an Electromagnetic Groundwater Flowmeter

Heffernan, Bill; Mitchell, Ben; Hayes, Michael

doi:10.1109/i2mtc43012.2020.9128643

Cited by 2 publications

(1 citation statement)

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“…Moreover, it avoids the instability and inaccuracy associated with numerical integration required by time-stepping simulation. The symbolic solution provides insight into system behavior, for example, how a component influences the poles of a power-electronics controller ( Heffernan, Mitchell & Hayes, 2020 ). Using symbolic mathematical tools allows expressions to be easily converted to standard forms, such a pole-zero-gain or partial fraction, to gain further insight into system behaviour.…”

Section: Introductionmentioning

confidence: 99%

Lcapy: symbolic linear circuit analysis with Python

Hayes¹

2022

PeerJ Computer Science

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Lcapy is an open-source Python package for solving linear circuits symbolically. It uses a superposition of DC analysis, AC (phasor) analysis, transient (Laplace) analysis, and noise analysis. Expressions are evaluated using the computer algebra system SymPy. Lcapy can model circuits comprised of combinations of one-port and two-port networks or circuits specified using a netlist with a Spice-like notation. Lcapy can present the system of equations produced from nodal analysis, modified nodal analysis, loop analysis, and state-space analysis. Expressions can be formatted into many representations, parameterized, and transformed to other domains. Dimensional analysis is performed to reduce user errors and to present results with units. Both continuous and discrete signals are supported. Lcapy produces high-quality output. Textbook quality schematics in a number of different formats can be generated from netlists and customized for different conventions. Expressions can be formatted into LaTeX format for inclusion into a document or numerically evaluated and plotted. An overview of the features and capabilities of Lcapy is presented, along with implementation details and performance considerations.

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Section: Introductionmentioning

confidence: 99%