Energy Management Strategy Based on a New Adaptive Filtering Algorithm for Battery-Ultracapacitor Electric Vehicles

Bakou Traoré (1) , Moustapha Doumiati (1, 2) , Cristina Morel (3) , Jean-Christophe Olivier (2) , Ousmane Soumaoro (4)

1 AGE - ESEO-AGE
2 IREENA - Institut de Recherche en Energie Electrique de Nantes Atlantique EA4642
3 ESTACA'Lab - ESTACA'Lab
4 ENI-ABT - National School of Engineering

This paper presents an energy management algorithm based on a new adaptive filtering method for a multi-sources battery-ultracapacitor electric vehicle. Compared to literature where most of the filtering techniques are developed based on empirical knowledge of the system, the proposed adaptation method is performed online to optimize a cost function that considers the state of charge of the ultracapacitor. The developed approach allows a better power sharing between both electric sources while respecting their constraints and physical limitations. Simulations on Matlab/Simulink validate the performances of the proposed method.

Mots clés: Electric vehicle; Energy management strategy; Ultracapacitor; Battery; Adaptive filtering

Domaines: Sciences de l'ingénieur [physics]; Energie électrique

Bakou Traoré, Moustapha Doumiati, Cristina Morel, Jean-Christophe Olivier, Ousmane Soumaoro. Energy Management Strategy Based on a New Adaptive Filtering Algorithm for Battery-Ultracapacitor Electric Vehicles. 15th IEEE Conference on Industrial Electronics and Applications, Nov 2020, Kristiansand, Norway. pp.392-396, ⟨10.1109/ICIEA48937.2020.9248112⟩. ⟨hal-02473858⟩