A Practical Methodology for Real-Time Adjustment of Kalman Filter Process Noise for Lithium Battery State-of-Charge Estimation

• Type: Article in International Scientific Journal
• Date: 2024

Authors

da Silva, CT (Author) Other; Dias, BMD (Author) Other; Rui Esteves Araújo (Author) FEUP; Pellini, EL (Author) Other; Laganá, AAM (Author) Other

Journal

The Journal is awaiting validation by the Administrative Services.

Title: BATTERIES-BASEL

Vol. 10

Final page: 233

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 0 Citations

Other information

Authenticus ID: P-011-3F6

DOI: 10.3390/batteries10070233

Abstract (EN): The methodology presented in this work allows for the creation of a real-time adjustment of Kalman Filter process noise for lithium battery state-of-charge estimation. This work innovates by creating a methodology for adjusting the process (Q) and measurement (R) Kalman Filter noise matrices in real-time. The filter algorithm with this adaptative mechanism achieved an average accuracy of 99.56% in real tests by comparing the estimated battery voltage and measured battery voltage. A cell-balancing strategy was also implemented, capable of guaranteeing the safety and efficiency of the battery pack in all conducted tests. This work presents all the methods, equations, and simulations necessary for the development of a battery management system and applies the system in a practical, real environment. The battery management system hardware and firmware were developed, evaluated, and validated on a battery pack with eight LiFePO4 cells, achieving excellent performance on all conducted tests.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 20