EconPapers    
Economics at your fingertips  
 

Multi-Plane Virtual Vector-Based Anti-Disturbance Model Predictive Fault-Tolerant Control for Electric Agricultural Equipment Applications

Hengrui Cao, Konghao Xu, Li Zhang (), Zhongqiu Liu, Ziyang Wang and Haijun Fu
Additional contact information
Hengrui Cao: School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China
Konghao Xu: School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China
Li Zhang: School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China
Zhongqiu Liu: School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China
Ziyang Wang: School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China
Haijun Fu: School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China

Energies, 2025, vol. 18, issue 14, 1-19

Abstract: This paper proposes an anti-disturbance model predictive fault-tolerance control strategy for open-circuit faults of five-phase flux intensifying fault-tolerant interior permanent magnet (FIFT-IPM) motors. This strategy is applicable to electric agricultural equipment that has an open winding failure. Due to the rich third-harmonic back electromotive force (EMF) content of five-phase FIFT-IPM motors, the existing model predictive current fault-tolerant control algorithms fail to effectively track fundamental and third-harmonic currents. This results in high harmonic distortion in the phase current. Hence, this paper innovatively proposes a multi-plane virtual vector model predictive fault-tolerant control strategy that can achieve rapid and effective control of both the fundamental and harmonic planes while ensuring good dynamic stability performance. Additionally, considering that electric agricultural equipment is usually in a multi-disturbance working environment, this paper introduces an adaptive gain sliding-mode disturbance observer. This observer estimates complex disturbances and feeds them back into the control system, which possesses good resistance to complex disturbances. Finally, the feasibility and effectiveness of the proposed control strategy are verified by experimental results.

Keywords: model prediction; fault-tolerance; sliding mode disturbance observer; flux-intensifying motor (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: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/18/14/3857/pdf (application/pdf)
https://www.mdpi.com/1996-1073/18/14/3857/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:18:y:2025:i:14:p:3857-:d:1705717

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-07-21
Handle: RePEc:gam:jeners:v:18:y:2025:i:14:p:3857-:d:1705717