This article presents a power management strategy (PMS) to control the power flow in a dc microgrid operating in the grid-connected mode. The microgrid model is composed of the ac utility grid interfaced with a voltage source inverter operating as a grid-forming converter (VSC), an energy storage system (ESS) formed by a battery bank and a bidirectional dc-dc converter operating as a grid-supporting unit, a distributed generation acting as a grid-feeding unit, and the customer loads with strict voltage regulation. The power management technique applies a virtual inertia concept together with a state of charge-based management function to regulate the charging and discharging process of the battery bank according to the dc microgrid power flow. Thus, high-rate peaks of power are avoided, which improves the ESS life cycle. With the proposed PMS, an autonomous power flow is achieved inside the dc microgrid, while the ac utility grid focuses exclusively upon forming the dc bus and processing the surplus or shortage of power. In addition, the proposed strategy simplifies the communication link between the grid inverter and the ESS, since the VSC power is the sole information exchanged. The experimental results show that the proposed PMS is reliable, leading to high ESS performance and power flow control within the dc microgrid, without degrading the dc bus voltage.

Switched reluctance motors are frequently quoted for electric and hybrid electric vehicle traction. However, high torque ripple is a common restraining disadvantage. This article proposes a design method for model following sliding mode as cruise controller, considering a direct instantaneous torque controller as part of the controlled plant. In addition, a back-electromotive force cancelation is incorporated by modifying the torque reference using the developed model. A minimum torque ripple point tracking (MTRPT) that actuates over the turn- off angle is proposed through an adaptation from the steepest descent maximum power point tracking algorithm. The turn- on angle is also controlled, aiming for enhanced torque regulation. The cruise controller is Lyapunov stable, robust to parameter variations, and is capable of rejecting load disturbances. Experimental results show that the MTRPT convergence time is around $\text{2.5 s}$ for a load step and around $\text{1.625 s}$ for a speed step. Besides, the speed tracking capability of the proposed system returns an MAE of 0.9223% and 1.0884% for the ECE-R15 and for the EUDC driving schedules, respectively. The MTRPT is capable of reducing the torque ripple by 14.6% in low speeds (ECE-R15) and by 10.1% at high speeds (EUDC). The results show that the proposed system is well founded for electric and hybrid electric vehicles applications.

This article presents as a new contribution a proposal to optimize the performance of switched reluctance generator (SRG) in a variable wind energy conversion system (WECS). An approach based on design of computational experiment (DCE) is applied to determinate the optimal firing angles and the optimal DC link voltage that guarantee the best system behavior for each rotor speed. Third order response surface model (RSM) based on space-filling designs is applied to build a multiobjective function considering efficiency improvement and torque ripple reduction. Interior point method (IPM) is applied to find the minimum of the surface, optimizing the process. Direct power control (DPC) is used to obtain the maximum power as function of the rotor speed, employing the optimal parameters. Hysteresis and single pulse current control are applied for low and high speed operation, respectively. Simulation and experimental results have shown that the proposed approach returned a good compromise between SRG high efficiency and low torque ripple. Moreover, the presented technique reduces the computational effort and provides a clear massive data simulation framework.

Switched reluctance machines have gained interest in electric vehicle applications because of its prominent advantages. However, drawbacks as torque ripple and highly nonlinear model restrain the usage of such machines on larger scale. In this paper, a minimum torque ripple point tracking (MTRPT) algorithm is proposed for online variation of turn-off angle. Also, a method for designing Dahlin cruise controllers with back-emf cancellation is presented. The system model accounts the current profiling technique for the design. The developed model is verified through simulation and experiments. The system presents minimum torque ripple tracking capability in broad operation speed testified by ECE-R15 and EUDC driving schedules. The MTRPT convergence time achieved during a load step in simulation and experiment is around 1s. In simulation, the speed tracking capability of the controller returns a RMSE of 0.047rad/s and 0.0182rad/s for the ECE-R15 and EUDC driving cycles, respectively. When the EUDC driving schedule is tested experimentally, the MTRPT diminished the torque ripple on average by 20% compared to when the turn-off angle is fixed. The speed tracking error is 0.99% with the MTRPT, and 1.3414% with the turn-off angle fixed. The results show that the system is valid for electric and hybrid electric vehicle implementation.

The ability of the four-quadrant operation is essential for transportation electrification applications. Switched reluctance machines (SRMs) have been increasingly considered an option for electric vehicles’ traction. However, achieving higher efficiency and low torque ripple may be a challenge for this type of machine, especially at low speeds. This article proposes a cruise control for SRM with the four-quadrant operation for extended autonomy. The cruise control is realized with a model following sliding mode speed controller and direct instantaneous torque control (DITC) for direct torque control. The proposed generating mode DITC aims for higher efficiency. An asymptotic stable model is developed for mode transition. The developed control system is Lyapunov stable in motoring, generating, and transition modes. Furthermore, an online multiobjective optimum point tracker (OPTPT) based on the steepest descent method is proposed aiming for efficiency maximization and torque ripple minimization. The experimental results show that the OPTPT convergence time is 1.25 s for a speed step and 1.2 s for a load step. The proposed control was submitted to an EUDC driving schedule, showing good speed regulation. The speed MAE of the cruise controller was 1.1344%. The transition between operation modes (motor–generator) occurs smoothly, which substantiates the proposed system for four-quadrant transportation electrification applications.