Circuit Synthesis of Electrochemical Supercapacitor Models

TL;DR

This paper presents a systematic method for synthesizing electrical circuits from physics-based supercapacitor models, enabling more accurate and physically interpretable circuit representations compared to traditional fitting methods.

Contribution

It introduces a novel synthesis procedure combining discretisation, linearisation, model reduction, and passive network synthesis for supercapacitor models.

Findings

Synthesized circuits reflect physical supercapacitor dynamics.

The method produces circuits with various topologies from different models.

Enhanced physical interpretability of supercapacitor circuits.

Abstract

This paper is concerned with the synthesis of RC electrical circuits from physics-based supercapacitor models describing conservation and diffusion relationships. The proposed synthesis procedure uses model discretisation, linearisation, balanced model order reduction and passive network synthesis to form the circuits. Circuits with different topologies are synthesized from several physical models. This work will give greater understanding to the physical interpretation of electrical circuits and will enable the development of more generalised circuits, since the synthesized impedance functions are generated by considering the physics, not from experimental fitting which may ignore certain dynamics.