An Efficient Approach to Precise Parameter Identification on Lithium Batteries Using EIS with Goertzel Algorithm and Adaptive Sampling

Arroyo Pecchi J.G.; Tafur-Sotelo J.C.; Sal y Rosas Celi D.E. · Lecture Notes in Networks and Systems (2026) · DOI: 10.1007/978-3-032-18982-0_10

Resumen

This work presents an efficient approach for identifying electrical parameters in lithium-ion battery cells using Electrochemical Impedance Spectroscopy (EIS) with adaptive sampling and the Goertzel algorithm. A first-order Thevenin model is identified from frequency-domain data; parameters R0, R1, and C are estimated by nonlinear least squares. The proposed pipeline preserves accuracy while drastically reducing computing time and memory, making it suitable for embedded and low-power systems. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

Instituciones: Pontificia Universidad Católica del Perú