The Real-Time Observation of Electric Vehicle Operating Points Using an Extended Kalman Filter
Küçük Resim Yok
Tarih
2024
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
MDPI
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Electric Vehicles (EVs) are set to play a crucial role in the energy transition. Although EVs offer significant environmental benefits, their technology still faces major challenges related to performance optimization, energy efficiency improvement, and cost reduction. A key point to address these challenges is the accurate identification of the speed/torque operating points of the drive systems. However, this identification is generally achieved using mechanical sensors, which are fragile, bulky, and expensive. This paper aims to develop, implement, and validate a speed/torque observer in real time based on the Extended Kalman Filter (EKF) approach for an EV equipped with an Open-End Winding Induction Motor with Dual Inverter (OEWIM-DI). The implementation of the EKF is based on the state modeling of the OEWIM-DI, enabling the observation of the torque and speed using voltage and current measurements. The validation of this approach is conducted experimentally on the FPGA and DS1104 boards. The results show that this approach offers excellent performance in terms of accuracy, stability, and real-time response speed. These results suggest that the proposed method could significantly contribute to the advancement of EV technology by providing a more robust and cost-effective alternative to traditional mechanical sensors while improving the overall efficiency and performance of EV drive systems.
Açıklama
Anahtar Kelimeler
DS1104, dual inverter, electric vehicle, extended Kalman filter, FPGA, open-end winding induction motor, speed/torque observer
Kaynak
Automation
WoS Q Değeri
Q3
Scopus Q Değeri
Q3
Cilt
5
Sayı
4
Künye
Djellouli, Y., Ardjoun, Sid Ahmed El Mehdi, Zerdali, E., Denai, M., & Chafouk, H. (2024). The real-time observation of electric vehicle operating points using an extended kalman filter. Automation (Basel), 5(4), 613-629.
