Directed Graph-Based Data Processing and Discharge Model Parameter Identification of Ternary Lithium Battery

• Published in: 2023 35th Chinese Control and Decision Conference (CCDC) pp. 4348 - 4351
• Main Authors: Shan, Duo, Yang, Jun, Wang, Jian, Zhang, Wenwen, Gu, Youchao
• Format: Conference Proceeding
• Language: English
• Published: IEEE 20.05.2023
• Subjects: Data models; discharge test; Discharges (electric); Lithium batteries; Mathematical models; Parameter estimation; parameter identification; Production; Resistance; Ternary lithium battery
• ISSN: 1948-9447
• DOI: 10.1109/CCDC58219.2023.10327358

Based on the discharge test data of a single ternary lithium battery, a battery discharge model was constructed. Firstly, the constant current discharge test of 0.5C and 1C discharge rate of the single ternary lithium battery was carried out through the programmable constant temperature and humidity test chamber and battery test bench. Obtain test data, battery resistance, capacity and rated voltage and other standard production known parameters. Based on the graph theory method, the test defect data is identified and its validity is proved. Then, based on the test data and physical mechanism of the two working conditions. The two key parameters of the battery discharge model are polarization resistance and exponential region constant, which are identified by MATLAB. At last, comparing the identified model and test data, the results show that the polarization resistance and exponential region constant identified within the allowable error range are effective and make the battery discharge model have better accuracy and feasibility. This model better simulates the discharge characteristics of the battery.