公开(公告)号：US20250079861A1

公开(公告)日：2025-03-06

申请号：US18517923

申请日：2023-11-22

Applicant: NATIONAL TAIWAN UNIVERSITY OF SCIENCE AND TECHNOLOGY

Inventor： Chang-Hua LIN ,  Jhih-Han DAI ,  Yi-Xin LIN

IPC: H02J7/00

Abstract: A method is to estimate the state of batteries by using a multi-level neural network formed with at least three neural networks. The method comprises steps of: extracting features from the charging and discharging data of a battery through a first-level neural network to form a first-stage output data, and inputting the first-stage output data into a second-level neural network; enhancing local features in the first-stage output data through the second-level neural network to form a second-stage output data; combining the first-stage output data with the second-stage output data to form a combination result to be input into a third-level neural network for data modeling, to generate a state estimation result of the battery. The present invention improves the accuracy of estimation for a flat zone in the charge/discharge curve of the battery, and quickly adjusts the multi-level neural network to achieve accurate estimation of different types of batteries.