Publicação

Battery management system for mobile robots based on an extended Kalman filter approch

Ver documento

Detalhes bibliográficos
Resumo:Robots are rapidly developing, due to the technology advances and the increased need for their mobility. Mobile Robots can move freely in unconstrained environments, without any external help. They are supplied by batteries as the only source of energy that they could access. Thus, the management of the energy offered by these batteries is so crucial and has to be done properly. Most advanced Battery Management System (BMS) algorithms reported in literature are developed and veri ed with laboratory-based experiments. The acquired data is then processed either online or of ine, using PC-based software. This work consists of developing an on-Chip Extended Kalman Filter based BMS, which can be directly linked in a robot without having to be connected with an external device to process the data. The proposed system is implemented in a low-cost 8 bit microcontroller and results allow to validate the proposed approach.
Autores principais:Chellal, Arezki Abderrahim
Outros Autores:Lima, José; Gonçalves, José; Megnafi, Hicham
Assunto:Electric batteries Extended Kalman filters Mobile robots Personal computers
Ano:2021
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso aberto
Instituição associada:Instituto Politécnico de Bragança
Idioma:inglês
Origem:Biblioteca Digital do IPB
Descrição
Resumo:Robots are rapidly developing, due to the technology advances and the increased need for their mobility. Mobile Robots can move freely in unconstrained environments, without any external help. They are supplied by batteries as the only source of energy that they could access. Thus, the management of the energy offered by these batteries is so crucial and has to be done properly. Most advanced Battery Management System (BMS) algorithms reported in literature are developed and veri ed with laboratory-based experiments. The acquired data is then processed either online or of ine, using PC-based software. This work consists of developing an on-Chip Extended Kalman Filter based BMS, which can be directly linked in a robot without having to be connected with an external device to process the data. The proposed system is implemented in a low-cost 8 bit microcontroller and results allow to validate the proposed approach.