Open AccessElectric vehicle with sliding mode control super-twisting control strategy
Author(s) -
Anith Khairunnisa Ghazali,
Mohd Khair Hassan,
Mohd Amran Mohd Radzi,
Azizan As’arry
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1432/1/012023
Subject(s) - regenerative brake , sliding mode control , control theory (sociology) , matlab , electric vehicle , automotive engineering , mode (computer interface) , controller (irrigation) , dynamic braking , convergence (economics) , braking system , computer science , control (management) , control system , engineering , control engineering , retarder , physics , nonlinear system , artificial intelligence , brake , power (physics) , electrical engineering , quantum mechanics , economic growth , economics , biology , operating system , agronomy
The braking system is the crucial part in vehicle system. The main purpose of braking system is to slow down or stop the moving vehicle. The regenerative braking system (RBS) designed to recapture more energy during braking. The electric vehicle dynamic model was design using Matlab/Simulink. Sliding mode controller with super-twisting (SMCST) was designed to avoid overcharging and improved the batteries’ SOC. Conventional sliding mode control (SMC) shows convergence within the desire level of accuracy, in which chattering is the main issue related to destructive phenomenon. SMCST intentionally to eliminate chattering with high accuracy. The results from the simulation show that the super-twisting control strategy offers higher regeneration efficiency.