Lithium-ion battery state-of-health prediction using Inception-V4 network optimized by Modified Hiking Optimization Algorithm

Electrochemical impedance spectroscopy (EIS) represents a non-invasive method of measuring state-of-health (SoH) of lithium-ion batteries, but it is difficult to obtain strong degradation measurements because of complicated responses with frequency. The paper presents a new approach of combining Inception-V4 deep learning architecture with a Modified Hiking Optimization Algorithm (MHOA) to obtain precise SoH estimation using only raw impedance spectra. Unlike traditional approaches that rely on