Model Predictive Control of Quasi-Z-Source Inverter

Sultana, Razia; Lodhi, Anuj; Gade, Chandrasekhar Reddy; Chitra, A.; Vanishree, J.; Manimozhi, M.

doi:10.1007/978-981-15-8221-9_285

Cited by 1 publication

(1 citation statement)

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“…It is inherent in model-predictive control to handle the dynamic relationship between feedforwards and decoupling, but the existing controllers are not capable enough to do so. An inverter applies the specified ideal output voltages to the motor based on the cost function parameters [9,21,22]. The prime advantage of the MPC is to provide greater flexibility and intuition, since it achieves control objectives through the application of a mathematical cost function.…”

Section: Icet Et Hetmentioning

confidence: 99%

Control of Permanent Magnet Synchronous Motor Using MPC–MTPA Control for Deployment in Electric Tractor

Gade

2022

Sustainability

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This study aims to evaluate the interior permanent magnet synchronous motor (IPMSM) drive performance for various load conditions under steady state and dynamic conditions. Therefore, this paper proposes finite set model-predictive control (FS-MPC) for IPMSM with maximum torque per ampere (MTPA) for electric tractor application. The MTPA control technique is used to obtain maximum torque while maintaining a minimum current constraint. In addition to MTPA control, the MPC scheme is used as the suitable alternative control strategy in the electric tractor application, which eliminates the occurrence of torque ripples during the dynamic speed tracking under variable load conditions. The MPC is used to improve the dynamic response of the motor drive and reduce torque ripples under variable load conditions. MPC–MTPA is developed in the MATLAB/SIMULINK and validated in the real-time environment using the hardware-in-the-loop (HIL) simulator (OPAL-RT OP5700). The results prove that MPC improves the dynamic performance and MTPA reduces the stator copper loss and increases the drive efficiency.

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Section: Icet Et Hetmentioning

confidence: 99%