Invention Grant
- Patent Title: Modular machine learning structure for electric vehicle battery state of health estimation
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Application No.: US17553585Application Date: 2021-12-16
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Publication No.: US11921163B2Publication Date: 2024-03-05
- Inventor: Gianina Alina Negoita , Wesley Teskey , Jean-Baptiste Renn , William Arthur Paxton
- Applicant: VOLKSWAGEN AKTIENGESELLSCHAFT
- Applicant Address: DE Wolfsburg
- Assignee: VOLKSWAGEN AKTIENGESELLSCHAFT
- Current Assignee: VOLKSWAGEN AKTIENGESELLSCHAFT
- Current Assignee Address: DE Wolfsburg
- Agency: Shield Intellectual Property PC
- Agent Zhichong Gu
- Main IPC: G01R31/367
- IPC: G01R31/367 ; B60L58/12 ; G01R31/382 ; G01R31/392 ; G01R31/396 ; G06N3/02 ; G06N3/04 ; G06N3/045

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.
Public/Granted literature
- US20230194614A1 MODULAR MACHINE LEARNING STRUCTURE FOR ELECTRIC VEHICLE BATTERY STATE OF HEALTH ESTIMATION Public/Granted day:2023-06-22
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