Modular machine learning structure for electric vehicle battery state of health estimation
US11921163B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 16, 2021 |
| Grant date | Mar 5, 2024 |
| Priority date | — |
| Expiry date | Dec 16, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2218/08
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Approaches, techniques, and mechanisms are disclosed for assessing battery states of batteries. According to one embodiment, raw sensor data are collected from a battery module. The battery module includes multiple battery cells. Input battery features are extracted from the raw sensor data collected from the battery module. The input battery features are used to update node states of a GNN. The GNN include multiple GNN nodes each of which representing a respective battery cell in the multiple battery cells. Estimation of one or more battery state of health (SoH) indicators is generated based at least in part on individual output states of individual GNN nodes in the multiple GNN nodes. The individual output states of individual GNN nodes in the multiple GNN nodes are determined based at least in part on the updated node states of the GNN.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.