Speed robust design of switched reluctance motor for electric vehicle system

Abstract

The strong nonlinear and uncertain parameters of the switched reluctance motor make the traditional controllers difficult to ensure a good performances and stable operation under diverse operating conditions. This work focuses on developing of a new robust design control for switched reluctance motor drives for electrical vehicle to attenuate the effect of disturbances and parameter uncertainties. For this, we have adopted the cascade control architecture (velocity-torque) using two different H ' syntheses (standard and fixed H ' approaches). The first controller of velocity in the outer control loop products the total torque of switched reluctance motor. Hence, a linear equivalent mechanical dynamic is obtained. In the inner control loop, the phase reference current is determined using the torque-angle-current (T À u À i) characteristics stored in lookup table, and the torque is regulated indirectly through the second controller of current. For each control loop, two H ' synthesis approaches are used and compared by m analysis. The simulation and experimental results demonstrate the effectiveness of the designed robust controllers and confirm the ability of the proposed strategies.

Modified Whale Algorithm-Based Optimization for Fractional Order Concurrent Diminution of Torque Ripple in Switch Reluctance Motor for EV Applications

“…The controlling profile of the stator current, and with intelligent selection of the turn-on (θ ON )/turn-off angle (θ OFF ) [6], the dimunition of torque ripple is achieved. By the appropriate and exact computation of the switching angle and by controlling the stator current profile, the control of SRM can be achieved [20,[32][33][34][35].…”

Control of variable reluctance machine (8/6) by artificiel intelligence techniques

“…For it to have a physical meaning, it must be according to known variables. (5) Replacing in (5) and simplification: (6) This equation clearly shows that the instantaneous input power is equal to the sum of the resistive losses given by , the rate of change of the electromagnetic energy is given by and the power P i in the air gap given by the term .Setting the time according to rotor position and speed (7) The power in the gap becomes: The power in the air gap is equal to the product of the electromagnetic torque and the speed of the rotor (9) Whence comes the equation of the electromagnetic torque:…”

“…A current direction of research is essentially based on the comparison of advanced commands that use the tools of artificial intelligence: fuzzy logic, artificial neural networks [5]. We will demonstrate the utility of applying different robust comands with fuzzy logic or neural networks that will at best enable the prosecution of position trajectories with great accuracy and, on than the others, significantly reduce the ripples of torque of VRM [6].…”

Advanced powertrain dynamic modelling and control for electrified vehicles

“…Starting from the propulsion system in the powertrain system, the paper 'Speed robust design of switched reluctance motor for electric vehicle system' presents a new robust controller for switched reluctance motor (SRM) in electric vehicles, which can help the SRM better attenuate the negative effect of external load disturbances as well as system parameter uncertainties by using H-infinity synthesis approaches. 1 In the paper 'Approximate dynamic programming solution for the optimal nitrogen oxides/particulate matter trade-off control of a WAPS engine', a data-driven approximate dynamic programming controller is developed to achieve optimal trade-off between nitrogen oxides and particulate matter emission for a unique 4JB1-Tweifu accumulator pump system (WAPS) engine. 2 In the paper 'Experimental investigation of emission characteristics based on new alcohol-based gasoline fuel', emission characteristics of a new type alcohol-based fuel are investigated in a CA4G5 engine.…”