State of the art perturb and observe MPPT algorithms based wind energy conversion systems: A technology review

Experimental implementation of Flower Pollination Algorithm for speed controller of a BLDC motor

To improve braking performance and regenerative energy of front drive electric vehicles (EVs) driven by switched reluctance motor (SRM), a regenerative braking control strategy based on multi-objective optimization of switched reluctance generator (SRG) drive system is proposed in this paper. Firstly, a partition braking force distribution strategy is developed by jointly considering braking energy and safety, and SRG drive system model is established based on low and high-speed condition. The vehicle braking system model including mechanic and regenerative braking system is built. Then, a multi-objective optimization function with three weight factors is defined, where output generated power, torque smoothness, and current smoothness are selected as optimization objectives to improve the driving range, braking comfort, and battery lifetime, respectively. Furthermore, a multi-objective optimization controller with variable switch angles is designed and combined with vehicle braking system. Finally, braking energy recovery efficiency, braking smoothness, and charging current smoothness under the multi-objective optimization controller for SRG are analyzed and compared with those under output power optimization controller. The comparison results show that the regenerative braking control strategy based on multi-objective optimization of SRG can effectively increase the vehicle braking comfort and improve battery lifetime without decreasing recovery energy.

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Regenerative Braking Control Strategy for Electric Vehicles Based on Optimization of Switched Reluctance Generator Drive System

Control of switched reluctance generator in wind power system application for variable speeds

A Mechanical Sensorless MPPT Algorithm for a Wind Energy Conversion System based on a Modular Multilayer Perceptron and a Processor-in-the-Loop Approach

Mohamed E. Metally

Papers

Artificial neural controller for torque ripple control and maximum power extraction for wind system driven by switched reluctance generator

Sensorless Control of Switched Reluctance Generator with Maximum Power Extraction Wind Driven Based on MO-PSO