Grey Wolf Optimizer-Based Predictive Torque Control for Electric Buses Applications

Ali Djerioui, Azeddine Houari, Mohamed Machmoum and Malek Ghanes
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Ali Djerioui: IREENA Laboratory, University of Nantes, 44600 Nantes, France
Azeddine Houari: IREENA Laboratory, University of Nantes, 44600 Nantes, France
Mohamed Machmoum: IREENA Laboratory, University of Nantes, 44600 Nantes, France
Malek Ghanes: LS2N, Ecole Centrale de Nantes, UMR CNRS 6004, 44321 Nantes, France

Energies, 2020, vol. 13, issue 19, 1-18

Abstract: This paper proposes an improved Predictive Torque Control (PTC) of a PMSM based on the Grey Wolf Optimizer (GWO) for smooth torque operation in Electric Bus applications (EBs). The embedded GWO is used to resolve the torque tracking tasks with minimal oscillations in running at the low speed of PMSM drives. The new PTC algorithm can successfully ensure the smooth time evolution of the torque and the speed. The design methodology is detailed and the provided experimental results show that the proposed PTC-GWO can be implemented in real-time on embedded hardware, offering high effectiveness in both steady and transient states of the PMSM drives, even at low-speed range.

Keywords: predictive torque control (PTC); grey wolf optimization (GWO); electric buses (EBs); low speed operation; permanent magnet synchronous motor (PMSM) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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