Fuzzy-Super twisting control implementation of battery/super capacitor for electric vehicles.

The present paper deals with a real-time implementation of a novel Fuzzy logic energy management strategy (EMS), applied to a battery-super capacitor hybrid energy system and associated with a permanent magnet synchronous motor (PMSM) which emulates the traction part of an electric vehicle (EV). On the sources side, the fuzzy logic supervisor acts in a smart way to permute smoothly between the various operations modes via an efficient power frequency splitting. In addition, it permits a quite regulation of both the DC bus and the super-capacitor (SC) voltages regardless of the speed profile variations to ensure an optimal power flow to the load and to keep the SC operation in a safe voltage range while providing or absorbing power in transients. On the traction side, a second order sliding mode control called 'super-twisting' (ST), associated with a space vector modulation (SVM) strategy is applied to ensure both decoupled torque and flux control under low torque and flux ripples. The assessment of the proposed control techniques is conducted on a small-scale battery/SC/PMSM system, controlled via two dSPACE1104 cards. The obtained experimental results show a smooth operation of the whole system, where the proposed Fuzzy logic supervisor succeeds to provide fast and high performances under different speed levels and ensures the proper functioning of each source while respecting its dynamics. Furthermore, the second order sliding mode controller shows good dynamic performances, where the system arrives to track perfectly the speed profile, under tolerable torque and flux ripples.

Robust sensorless vector control of an induction machine using Multiobjective Adaptive Fuzzy Luenberger Observer.

This paper presents an inherent speed estimation scheme associated to the Indirect Field Oriented Control in case of Induction motor sensorless control. Indeed, through the design of a Multiobjective Adaptive Fuzzy Luenberger Observer, the speed sensorless control issue even at low speed, the observer poles' assignment issues and the speed estimation's sensitivity to rotor resistance uncertainties issue are treated concurrently. First of all, the structure of the proposed Takagi-Sugeno adaptive observer is described. Secondly, based on Lyapunov theory, observer gains are designed and a fuzzy speed estimation scheme is provided. The design's objectives consist of minimizing the sensitivity of the proposed observer to rotor resistance uncertainties (using the L2 techniques) and to guarantee a specified observer dynamic performances through a D-stability analysis. The design conditions are formulated into Linear Matrix Inequalities terms. Finally, experiments are conducted to demonstrate the effectiveness of the proposed results regardless of uncertainties in the rotor resistance.