Abstract-This paper presents a passivity-based control (PBC) scheme for the Switched Reluctance Generator (SRG) in smallscale wind energy conversion systems (WECSs) for DC microgrid application. The main objective is to stabilize the output voltage in case the system supplies constant power loads (CPLs) and operates with maximum power point tracking (MPPT). Stability improvement and dc-link ripple reduction in the presence of CPLs is achieved using system level modeling of SRG-based DC microgrid through the Euler-Lagrange system (ELS) from the view point of the machine physical structure. Compared with other control methods, the proposed MPPT method based on passivity-based speed controller employs the back-EMF in the generation process as a position-dependent voltage source to overcome the major challenge of SRG complicated uncertain dynamic model. To deal with the time-varying inductance and back-emf of SRG, an adaptation mechanism is incorporated in proposed adaptive PBC and the control design is constructed by using the Lyapunov theorem where the closed-loop stability is ensured. The effectiveness of the proposed method in avoiding instability effects of SRG and CPL with voltage ripple reduction and precise wind turbine speed tracking is investigated with simulation results and validated with experimental by using a four-phase, 8/6 SRG drive system. Switched Reluctance Generator (SRG); Wind turbine; Passivity-based control; Constant-power load.
Selection of electrical machine is a key issue in electrical and hybrid electrical vehicles (HEVs and EVs). As far as HEVs and EVs are concerned, mechanical ruggedness of electrical machine is of utmost importance. For these reasons, the application of switched reluctance (SR) machine in EVs and HEVs is a viable option. In this study, an SR generator (SRG) has been utilised to work as a battery charger in EVs. The current ripple of the SRG is the greatest issue when it works as a battery charger. Therefore, a power converter and a smart search control (SSC) approach are proposed in this study to decrease the current ripple when the output power has a maximum quantity. During the system operation, the SSC method determines the value of excitation angle, turn-on and turn-off angles for each phase of SRG. The simulation and experimental results demonstrate the eligibility of the SSC system and power converter to obtain the acceptable charging current in maximum generated power during battery charging.
This paper investigates the problem of high torque ripple in switched reluctance motor (SRM) drives. A method is proposed for below the base speed operation of SRM that determines both the turn-off and the turn-on angles for reducing motor torque ripple. Determination of the turn-off angle is an offline process performed through solving a multiobjective optimization function consisting of two criteria: torque ripple and copper loss. Turn-on angle adjustment, however, is an online process based on the intersection approach of consecutive phase currents, particularly proposed in this paper. Simulation and experimental results are presented to validate the reduction in torque ripple gained from the proposed angles control scheme.
Permanent magnet synchronous motors (PMSMs) are suitable options for high-performance applications due to their potential of high power density and torque smoothness. Nevertheless, there are some factors affecting this feature by producing unwanted pulsating torque. One of the causes of torque ripple is the presence of harmonic components in motor back EMF. This paper has presented a multiple reference frame (MRF) method improving torque characteristic in PMSM regarding nonsinusoidal back EMF. An adaptive notch filter (ANF) was used as a current estimator which can separate needed current components. Optimal current components, obtained from Lagrange multiplier method, were regulated through PI controllers which guaranteed the desired convergence. Cogging torque and rms current minimization were intended, too. Results were investigated through simulations in Matlab/Simulink environment.
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