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

被引:0
|
作者
Traore, Bakou [1 ]
Doumiati, Moustapha [2 ]
Morel, Cristina [2 ]
Olivier, Jean-Christophe [3 ]
Soumaoro, Ousmane [4 ]
机构
[1] Univ Nantes, IREENA Lab EA4642, 10 Bd Jean Jeanneteau, Angers, France
[2] ESEO High Sch Engn, IREENA Lab EA 4642, 10 Bd Jean Jeanneteau, Angers, France
[3] Univ Nantes, IREENA Lab EA 4642, 37 Bd Univ, St Nazaire, France
[4] Natl Sch Engn ENI ABT, 410 Av Vollenhoven, Bamako, Mali
来源
PROCEEDINGS OF THE 15TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA 2020) | 2020年
关键词
Electric vehicle; Energy management strategy; Ultracapacitor; Battery; Adaptive filtering;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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.
引用
收藏
页码:392 / 396
页数:5
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