Development of a Fault-Tolerant Permanent Magnet Synchronous Motor Using a Machine-Learning Algorithm for a Predictive Maintenance Elevator DOI Creative Commons
Vasileios I. Vlachou, Theoklitos S. Karakatsanis

Machines, Journal Year: 2025, Volume and Issue: 13(5), P. 427 - 427

Published: May 19, 2025

Elevators serve as essential vertical transportation systems for both passengers and heavy loads in modern buildings. Electromechanical lifts have become the dominant choice due to their performance advantages over hydraulic systems. A critical component of drive mechanism is Permanent Magnet Synchronous Motor (PMSM), which subject mechanical electrical stress during continuous operation. This necessitates advanced monitoring techniques ensure safety, system reliability, reduced maintenance costs. In this study, a fault-tolerant PMSM designed evaluated through 2D Finite Element Analysis (FEA), optimizing key electromagnetic parameters. The design validated experimental testing on real elevator setup, capturing operational data under various loading conditions. These signals are preprocessed analyzed using machine-learning techniques, specifically Random Forest classifier, distinguish between Normal, Marginal, Critical states motor health. model achieved classification accuracy 94%, demonstrating high precision predictive capabilities. results confirm that integrating with real-time analytics offers reliable solution early fault detection, minimizing downtime enhancing safety.

Language: Английский

Adaptive Super-Twisting Controller-Based Modified Extended State Observer for Permanent Magnet Synchronous Motors DOI Creative Commons
Lili Pan, Chunyun Fu, Bin Chen

et al.

Actuators, Journal Year: 2025, Volume and Issue: 14(4), P. 161 - 161

Published: March 23, 2025

A novel sliding mode control (SMC) strategy incorporating an adaptive super-twisting algorithm is developed for permanent magnet synchronous motors (PMSMs), effectively mitigating high-frequency chattering while enhancing external disturbance rejection capabilities. Initially, a surface crafted based on the dynamic characteristics of PMSM and real-time feedback. The subsequently applied adaptively to dynamically adjust effort required maintain state, thereby ensuring precise prompt intervention uphold system stability enhance response speed. Additionally, in light operational challenges such as road-induced load disturbances, Lyapunov-based observer proposed torque estimation systems. efficacy observation methods substantiated through hardware-in-the-loop experiment test, demonstrating that controller, leveraging algorithm, exhibits superior tracking capabilities, reduces steady-state current error, bolsters parameter robustness, modified extended state (MESO) commendable performance.

Language: Английский

Citations

0

PMSM Speed Control Based on Improved Adaptive Fractional-Order Sliding Mode Control DOI Open Access
Fengshuo Bian, Ying‐Ren Chien

Symmetry, Journal Year: 2025, Volume and Issue: 17(5), P. 736 - 736

Published: May 10, 2025

Addressing the problem of poor robustness and anti-interference ability in permanent magnet synchronous motor (PMSM) speed control system, an adaptive fractional-order sliding mode controller based on a disturbance observer is proposed. Firstly, mathematical model PMSM established, which combines with fractional order to effectively reduce drawbacks traditional integer improve accuracy system. At same time, new approach law used replace exponential law, reduces system buffeting improves performance. We use observe external disturbances perform feedforward compensation observed values system’s ability. By combining techniques, mitigates limitations integer-order approaches. It enhances symmetry preservation response under asymmetric conditions. The simulation results show that using improved can enhance stability ability, has better dynamic steady-state

Language: Английский

Citations

0

Development of a Fault-Tolerant Permanent Magnet Synchronous Motor Using a Machine-Learning Algorithm for a Predictive Maintenance Elevator DOI Creative Commons
Vasileios I. Vlachou, Theoklitos S. Karakatsanis

Machines, Journal Year: 2025, Volume and Issue: 13(5), P. 427 - 427

Published: May 19, 2025

Elevators serve as essential vertical transportation systems for both passengers and heavy loads in modern buildings. Electromechanical lifts have become the dominant choice due to their performance advantages over hydraulic systems. A critical component of drive mechanism is Permanent Magnet Synchronous Motor (PMSM), which subject mechanical electrical stress during continuous operation. This necessitates advanced monitoring techniques ensure safety, system reliability, reduced maintenance costs. In this study, a fault-tolerant PMSM designed evaluated through 2D Finite Element Analysis (FEA), optimizing key electromagnetic parameters. The design validated experimental testing on real elevator setup, capturing operational data under various loading conditions. These signals are preprocessed analyzed using machine-learning techniques, specifically Random Forest classifier, distinguish between Normal, Marginal, Critical states motor health. model achieved classification accuracy 94%, demonstrating high precision predictive capabilities. results confirm that integrating with real-time analytics offers reliable solution early fault detection, minimizing downtime enhancing safety.

Language: Английский

Citations

0