Performance Evaluation of an Anti-Lock Braking System for Electric Vehicles with a Fuzzy Sliding Mode Controller
Open Access
- 9 October 2014
- Vol. 7 (10), 6459-6476
- https://doi.org/10.3390/en7106459
Abstract
Traditional friction braking torque and motor braking torque can be used in braking for electric vehicles (EVs). A sliding mode controller (SMC) based on the exponential reaching law for the anti-lock braking system (ABS) is developed to maintain the optimal slip value. Parameter optimizing is applied to the reaching law by fuzzy logic control (FLC). A regenerative braking algorithm, in which the motor torque is taken full advantage of, is adopted to distribute the braking force between the motor braking and the hydraulic braking. Simulations were carried out with Matlab/Simulink. By comparing with a conventional Bang-bang ABS controller, braking stability and passenger comfort is improved with the proposed SMC controller, and the chatting phenomenon is reduced effectively with the parameter optimizing by FLC. With the increasing proportion of the motor braking torque, the tracking of the slip ratio is more rapid and accurate. Furthermore, the braking distance is shortened and the conversion energy is enhanced.This publication has 12 references indexed in Scilit:
- Energy-Regenerative Braking Control of Electric Vehicles Using Three-Phase Brushless Direct-Current MotorsEnergies, 2013
- Integrated control of electromechanical braking and regenerative braking in plug-in hybrid electric vehiclesInternational Journal of Vehicle Design, 2012
- An Intelligent Regenerative Braking Strategy for Electric VehiclesEnergies, 2011
- Bond graph model-based evaluation of a sliding mode controller for a combined regenerative and antilock braking systemProceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 2011
- Combined control of a regenerative braking and antilock braking system for hybrid electric vehiclesInternational Journal of Automotive Technology, 2008
- Dynamic Slip-Ratio Estimation and Control of Antilock Braking Systems Using an Observer-Based Direct Adaptive Fuzzy–Neural ControllerIEEE Transactions on Industrial Electronics, 2008
- Anti-Lock Braking Control of a Hybrid Brake-By-Wire SystemProceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 2006
- Iterative Learning Control of Antilock Braking of Electric and Hybrid VehiclesIEEE Transactions on Vehicular Technology, 2005
- Neural-network hybrid control for antilock braking systemsIEEE Transactions on Neural Networks, 2003
- THE MAGIC FORMULA TYRE MODELVehicle System Dynamics, 1992