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ABSTRACT
In this manuscript, an American Zebra Optimization Algorithm (AZOA) is proposed for minimising torque-ripple in an 8/6 switched reluctance motor (SRM) drive. The major objective of the proposed technique is to improve efficiency, steady state performance, and minimise the torque ripple. The objective is achieved by applying the AZOA to determine the optimal converter topology. The switched reluctance motor is fed by three converters with three legs. It consists of freewheeling diodes, IGBTs, capacitors, and resistors. By then, the proposed technique is executed in the MATLAB software and its performance is evaluated with various existing approaches. The simulation results of the SRM drive with different converter typologies are presented to analyse its performance with torque and speed characteristics. The proposed method demonstrates superior performance across all approaches, including the heap-based optimiser (HBO), salp swarm algorithm (SSA), and cuckoo search algorithm (CSA), yielding better results. From the result, it is concluded that the proposed technique displays a high efficiency of 95% and a low cost of 1.5$ compared with other existing methods.
Acronyms
| AZOA | = | American Zebra Optimization Algorithm |
| SRM | = | Switched Reluctance Motor |
| FOPID | = | Fractional Order Proportional-Integral-Derivative |
| SSD | = | SFO -social ski-diver based sunflower optimisation |
| IGBTS | = | Insulated Gate Bipolar Transistors |
| HBO | = | Heap-Based Optimizer |
| CSA | = | Cuckoo Search Algorithm |
| DTC | = | Direct Torque Control |
| AC | = | Alternating Current |
| ISE | = | Integral Squared Error |
| RPM | = | Revolution Per Minute |
| mWOA | = | Modified Whale Optimisation Algorithm |
| GA-HFFC | = | genetic algorithm hybrid fuzzy-fuzzy controller |
| IM | = | induction motor |
| PMSM | = | Permanent Magnet Synchronous Motor |
| FOC | = | field-oriented control |
| EMF | = | Electromotive Force |
| TSF | = | Torque Sharing Functions |
| SSA | = | Salp Swarm Algorithm |
| GA | = | Genetic Algorithm |
| CMFG-RNN | = | Continuous Max-Flow Graph-based Recurrent Neural Network |
| DTI | = | Discrete Time Integrator |
| SVPWM | = | space vector pulse width modulation |
| FPA | = | Flower Pollination Algorithm |
Disclosure statement
No potential conflict of interest was reported by the author(s).