4 research outputs found
Torque Ripple Suppression in the 6/4 Variable Flux Reluctance Machine with Open Winding Configuration by Using Harmonic Injection
No full textHigh torque ripple can be observed with a 6/4 variable flux reluctance machine (VFRM). In order to minimize the torque ripple in VFRMs, this paper presents a harmonic injection method for 6/4 VFRMs with an open-winding configuration. By analyzing the impact of harmonics on VFRMs, the method involves detecting the third harmonic using a first-order low-pass filter (FLPF). Subsequently, the extracted harmonics are controlled and shifted to counteract the voltage harmonics in both inverters without inducing phase imbalance or overvoltage. With the proposed method, the torque ripple can be significantly reduced by about 50% under load conditions. The effectiveness of the harmonic injection method is validated through a prototype VFRM
Dynamic Decoupled Current Control for Smooth Torque of the Open-Winding Variable Flux Reluctance Motor Using Integrated Torque Harmonic Extended State Observer
Get PDFVariable Flux Reluctance Machines (VFRMs) face multiple interconnected challenges that limit their performance, particularly in high-performance applications such as electric vehicles (EVs), where smooth torque output and robust operation are critical. Chief among these challenges are complex inter-axis couplings, including cross-coupling in the dq-axis, differential term coupling in the d0-axis, and disturbances propagating from the 0-axis to the q-axis. Additionally, harmonic disturbances associated with torque ripple exacerbate performance issues, resulting in degraded dynamic behavior. These challenges hinder current loop controllers, preventing effective management of winding impedance voltage drops and inter-axis coupling terms without advanced decoupling strategies. To address these challenges, this paper proposes a novel integrated torque harmonic extended state observer (ITHESO) within a decoupled current control designed to ensure fast and accurate current tracking, system stability, and torque ripple reduction. The ITHESO identifies and compensates for total current disturbances, including harmonic components, through feed-forward compensation within the current loop. Furthermore, the influence of control parameters and the effects of parameter mismatches on stability, torque ripple reduction, and disturbance rejection are thoroughly analyzed. Experimental validations demonstrate that the proposed strategy significantly enhances torque dynamics and reduces torque ripple, outperforming the conventional Active Disturbance Rejection Control (ADRC), which does not explicitly address disturbances associated with torque ripple. These advancements position the VFRM with the ITHESO as a competitive option for high-performance EV propulsion systems, offering smooth operation, noise reduction, and reliable performance under varying speeds and loads.© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed
Band level similarity reduction and deep dual signal fusion for reliable diagnosis of power insulator defects
No full textAbstract Effective monitoring of electrical insulators is critical for maintaining power system reliability, because insulator defects can trigger partial discharges and service interruptions. However, state-of-the-art diagnostic methods are computationally inefficient, require extensive hyperparameter tuning and perform poorly on complex scenarios—particularly perforated insulators without contamination (Signal d). This study addresses these limitations by proposing a novel, hyperparameter-free framework that applies a Similarity Reduction (SR) technique to remove redundant frequency bands through bandpass filtering and feature extraction, then fuses classifier outputs from acoustic (0–20 kHz) and ultrasonic (21–250 kHz) signal components using MFCC features (which outperform FFT, wavelet and time-domain alternatives). By reducing inter-signal redundancy via SR, the framework enables FFT features to be effectively used and allows a transition from a complex CNN–RNN architecture to a lightweight CNN while maintaining high performance. The resulting SRMF + CNN model achieved perfect classification (100% true positive and true negative rates) and dramatically shorter training times, with about a 20 times speedup on perforated cases and a 10 times speedup on contaminated cases compared with the SRMF + CNN–RNN baseline; it also resolved previous failures in Signal d classification, achieving 96.8% accuracy for perforation and 96.9% for contamination. Comparative benchmarks confirm that the SRMF approach outperforms XGBoost, Random Forest and MLP classifiers in both accuracy and efficiency, without increasing sensitivity to class imbalance. These results highlight the SRMF framework as a scalable, generalisable solution for real-time, embedded insulator diagnostics in modern power systems
Abstracts of the First International Conference on Advances in Electrical and Computer Engineering 2023
Get PDFThis book presents extended abstracts of the selected contributions to the First International Conference on Advances in Electrical and Computer Engineering (ICAECE'2023), held on 15-16 May 2023 by the Faculty of Science and Technology, Department of Electrical Engineering, University of Echahid Cheikh Larbi Tebessi, Tebessa-Algeria. ICAECE'2023 was delivered in-person and virtually and was open for researchers, engineers, academics, and industrial professionals from around the world interested in new trends and advances in current topics of Electrical and Computer Engineering.
Conference Title: First International Conference on Advances in Electrical and Computer Engineering 2023Conference Acronym: ICAECE'2023Conference Date: 15-16 May 2023Conference Venue: University of Echahid Cheikh Larbi Tebessi, Tebessa-AlgeriaConference Organizer: Faculty of Science and Technology, Department of Electrical Engineering, University of Echahid Cheikh Larbi Tebessi, Tebessa-Algeri
