An embedded controller application with regenerative braking for the electric vehicle


Creative Commons License

Karabacak Y., UYSAL A.

Elektronika ir Elektrotechnika, vol.26, no.1, pp.10-17, 2020 (SCI-Expanded, Scopus) identifier

  • Publication Type: Article / Article
  • Volume: 26 Issue: 1
  • Publication Date: 2020
  • Doi Number: 10.5755/j01.eie.26.1.25306
  • Journal Name: Elektronika ir Elektrotechnika
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Applied Science & Technology Source, Central & Eastern European Academic Source (CEEAS), Communication Abstracts, Computer & Applied Sciences, INSPEC, Metadex, Civil Engineering Abstracts
  • Page Numbers: pp.10-17
  • Keywords: Embedded system, Index Terms—Electric vehicles, Regenerative braking
  • Open Archive Collection: AVESIS Open Access Collection
  • Manisa Celal Bayar University Affiliated: Yes

Abstract

—Regenerative braking is very important for increasing the total range of an electric vehicle. In this study, an embedded controller, including regenerative braking, is designed and implemented for an electric vehicle. Experimental studies are carried out on an electric vehicle driven by two in-wheel electric motors. In-wheel electric motors are preferred in light electric vehicles, since they are both highly efficient and supports regenerative braking. In our embedded controller application, the in-wheel electric motor is operated in both the motor mode and the regenerative braking mode. The in-wheel electric motor control embedded software is developed in the Matlab/Simulink environment. The developed software is embedded in the DSP STM32F407 microcontroller, which has ARM Cortex-M4 core. The in-wheel electric motor is controlled by a fuzzy logic controller in the motor mode, the in-wheel electric motor - in the regenerative braking mode. Different PWM (Pulse Width Modulation) ratios are applied to the wheel electric motor in the regenerative braking mode. The experimental data are recorded in real-time by transferring to a PC on the electric vehicle. The performance of the study is proven with experimental tests.