公开(公告)号：US20230168304A1

公开(公告)日：2023-06-01

申请号：US17916041

申请日：2021-09-01

Applicant: BEIJING INSTITUTE OF TECHNOLOGY

Inventor： Rui XIONG ,  Jinpeng TIAN ,  Yanzhou DUAN

IPC: G01R31/367 ,  G01R31/378 ,  G01R31/392

CPC classification number: G01R31/367 ,  G01R31/378 ,  G01R31/392

Abstract: An artificial intelligence (AI)-based charging curve reconstruction and state estimation method for a lithium-ion battery is provided to estimate various states of a battery. In the method, a complete charging curve is reconstructed through deep learning with charging data segments as input. Then, a plurality of states of the battery can be extracted from the complete charging curve, including a maximum capacity, maximum energy, a state of charge (SOC), a state of energy (SOE), a state of power (SOP), and a capacity increment curve. The battery charging curve reconstruction and state estimation method is adaptively updated with a change in a working state of the battery.

公开(公告)号：US20230204668A1

公开(公告)日：2023-06-29

申请号：US17916048

申请日：2021-09-01

Applicant: BEIJING INSTITUTE OF TECHNOLOGY

Inventor： Rui XIONG ,  Jinpeng TIAN ,  Yanzhou DUAN

IPC: G01R31/367 ,  G01R31/378

CPC classification number: G01R31/367 ,  G01R31/378

Abstract: A method for estimating the state of charge (SOC) of a lithium-ion battery system based on artificial intelligence (AI) is provided. In the method, the relationship between the charging data segments and the SOC of the battery system is established through deep learning, and the SOC at any stage of the charging process can be corrected. SOC in a discharging process is estimated through ampere-hour integration. The estimation method is adaptively updated with a change in the working state of the battery system.