A fuzzy adaptive sliding mode slip ratio controller of a HEV

Antilock braking system (ABS) is a safety measure for a vehicle essential during braking for regulating wheel slip ratio at its optimum value. Slip ratio control of a vehicle is an important concern for development of ABS to avoid skidding during road surface transitions. Sliding mode control (SMC) being a robust control paradigm is exploited for an ABS in a hybrid electric vehicle (HEV). But it yields significant amount of chattering. The dynamics of a braking system are time varying, nonlinear and uncertain. Fuzzy logic control (FLC) is popular in providing good performance for nonlinear uncertain systems. This paper exploits benefits of both fuzzy logic and SMC in designing a Fuzzy Adaptive Sliding Mode Control (FASMC) for slip ratio control of a HEV. This FASMC generates control voltage to actuators of HEV by combining two control signals namely an equivalent control, a discontinuous fuzzy control. Further to adapt the uncertainties in road conditions an adaption technique is developed in the equivalent control law. Fuzzy reaching control algorithm is introduced in the discontinuous control of SMC to mimic the reaching control. An adaptive tuning algorithm is developed to tune the fuzzy parameters. The slip ratio control performance of the proposed FASMC has been compared with that of a sliding mode controller through extensive simulations using MATLAB. From the obtained results it is observed that the proposed FASMC eliminates chattering completely and provides excellent slip control performance.

[1]  Chih-Min Lin,et al.  Neural-network hybrid control for antilock braking systems , 2003, IEEE Trans. Neural Networks.

[2]  Rolf Isermann,et al.  Wheel Slip Control for Antilock Braking Systems Using Brake-by-Wire Actuators , 2003 .

[3]  D. Morrey,et al.  Recent advances in antilock braking systems and traction control systems , 2000 .

[4]  Okyay Kaynak,et al.  The fusion of computationally intelligent methodologies and sliding-mode control-a survey , 2001, IEEE Trans. Ind. Electron..

[5]  Christopher M. Bingham,et al.  Application of fuzzy control algorithms for electric vehicle antilock braking/traction control systems , 2003, IEEE Trans. Veh. Technol..

[6]  B. Subudhi,et al.  Comparison of two controllers for directional control of a hybrid electric vehicle , 2012 .

[7]  Barry Dwolatzky,et al.  State Feedback Based Linear Slip Control Formulation for Vehicular Antilock Braking System , 2011 .

[8]  Hui Lin,et al.  Iterative learning control of antilock braking of electric and hybrid vehicles , 2005, IEEE Transactions on Vehicular Technology.

[9]  Bidyadhar Subudhi,et al.  Effects of sliding surface on the performances of sliding mode slip ratio controller for a HEV , 2012, 2012 Annual IEEE India Conference (INDICON).

[10]  R. Bozorgmehry Boozarjomehry,et al.  A fuzzy sliding mode control approach for nonlinear chemical processes , 2009 .

[11]  Shuzhi Sam Ge,et al.  Sliding-Mode-Observer-Based Adaptive Slip Ratio Control for Electric and Hybrid Vehicles , 2012, IEEE Transactions on Intelligent Transportation Systems.