Battery state of health estimator

US11360155B2 · kind B2 · utility

Assignees

• VOLKSWAGEN AKTIENGESELLSCHAFT · DE
• AUDI AG · DE
• Dr. Ing. h.c. F. Porsche AG · DE

Inventors

• Melanie Senn · Mountain View, US
• Joerg Wolf · Karlsruhe, DE
• Lorenz Haghenbeck Emde · Menlo Park, US

Key dates

• Filing date: Sep 3, 2020
• Grant date: Jun 14, 2022
• Expiry date: Sep 8, 2040

Classification

• Technology area (CPC G): Physics
• CPC primary: G06N3/088
• WIPO field: Measurement
• WIPO sector: Instruments

Abstract

A computing system, method, and apparatus for determining a state of health indication for a battery are provided. A first supervised deep neural network (“DNN”) is trained using received characteristics for the battery as input and received process parameters as outputs. An unsupervised AI estimator is trained using one or more clustering methods based on extracted features from the first supervised DNN, where the received characteristics are input to the unsupervised AI estimator. A second supervised DNN is trained using identified clusters from the unsupervised AI estimator. The identified clusters are validated with state of health indications. User battery data is inputted to the second supervised DNN to determine the state of health for the battery.