Li-ion battery pack SoC estimation for electric vehicles

Kodjo Senou Rodolphe Mawonou , Akram Eddahech , Didier Dumur (1) , Emmanuel Godoy (1) , Dominique Beauvois (1) , Michel Mensler (2)

1 L2S - Laboratoire des signaux et systèmes
2 Direction de la Recherche, Etudes Avancées, Matériaux

An accurate state of charge (SoC) estimation by the battery management system (BMS) is crucial for efficient and non-destructive battery-packs operation in electric vehicles (EV s), However, simply replicating an Equivalent Electric Circuit (EEC) method for all cells in a pack leads to huge computational complexity. This paper proposes two different approaches to estimate battery-packs SoC more accurately while keeping a suitable computational burden. We argue that for an operating battery-pack, only the limiting cells SoCs and voltages are relevant. The first approach consists of detection of limiting cells based on voltage and current measurement to reduce computational burden. The second is an improvement of the existing “bar-delta” approach developed by Plett. Both of theses approaches lead to significant improvement of limiting cells detection, computational burden reduction and accuracy.

Domaines: Automatique / Robotique; Energie électrique

Kodjo Senou Rodolphe Mawonou, Akram Eddahech, Didier Dumur, Emmanuel Godoy, Dominique Beauvois, et al.. Li-ion battery pack SoC estimation for electric vehicles. IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society, Oct 2018, Washington D.C., United States. ⟨10.1109/iecon.2018.8591187⟩. ⟨hal-02111246⟩