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

• Tipo: Artigo em Revista Científica Internacional
• Data: 2024

Autores

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

Revista

A Revista está pendente de validação pelos Serviços Administrativos.

Título: BATTERIES-BASEL

Vol. 10

Página Final: 233

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 0 Citações

Outras Informações

ID Authenticus: 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 20