Fault Diagnosis and Tolerance in Converters of Brushless DC Motor Drives for Low-Speed Applications

Condition monitoring and fault detection have become essential due to the growing need for reliabilityin motor drive applications. In electronically commutated motors, switching elements form the core components of the motor drives. These switching devices are prone to open-circuit faults (OCF) and short-circuit faults (SCF), which can impact the stability of the target application. This article introduces a simple switch fault diagnosis technique for brushless direct current (BLDC) motor drives, employing stator current sensing and sector information. The proposed method detects switch faults by monitoring the deviations in the conducting and non-conducting intervals of stator currents beyond their anticipated durations under normal conditions. Upon fault detection, the faulty legs of the converter are isolated and dynamically replaced by a two-leg redundant inverter. This reconfiguration is achieved by using low-cost electromechanical relays (EMRs). The fault-tolerant configuration ensures the motor operates at its rated power, even after experiencing up to two switch faults in the converter. In addition to fault detection and tolerance, the presented work also examines the severity of SCF, which causes abnormal stator currents due to three-winding conduction in BLDC motors. The effectiveness of the proposed approach is validated through experimental results obtained from a 36 V, 400 W BLDC motor drive.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Energy Conversion
Published
2025-03-31
DOI
https://doi.org/10.1109/tec.2025.3556012
Citations
1
Primary Topic
Multilevel Inverters and Converters
Type
article
Field-Weighted Citation Impact
0.73
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Fault Diagnosis and Tolerance in Converters of Brushless DC Motor Drives for Low-Speed Applications

Sanjay Reddy, Kalaiselvi Jayaraman, Priya Singh Bhakar, Annima Gupta
1 citations
IEEE Transactions on Energy Conversion
Multilevel Inverters and Converters
0.73
article

Fault Diagnosis and Tolerance in Converters of Brushless DC Motor Drives for Low-Speed Applications

Sanjay Reddy, Kalaiselvi Jayaraman, Priya Singh Bhakar, Annima Gupta
article en
1 citations

Abstract

Condition monitoring and fault detection have become essential due to the growing need for reliabilityin motor drive applications. In electronically commutated motors, switching elements form the core components of the motor drives. These switching devices are prone to open-circuit faults (OCF) and short-circuit faults (SCF), which can impact the stability of the target application. This article introduces a simple switch fault diagnosis technique for brushless direct current (BLDC) motor drives, employing stator current sensing and sector information. The proposed method detects switch faults by monitoring the deviations in the conducting and non-conducting intervals of stator currents beyond their anticipated durations under normal conditions. Upon fault detection, the faulty legs of the converter are isolated and dynamically replaced by a two-leg redundant inverter. This reconfiguration is achieved by using low-cost electromechanical relays (EMRs). The fault-tolerant configuration ensures the motor operates at its rated power, even after experiencing up to two switch faults in the converter. In addition to fault detection and tolerance, the presented work also examines the severity of SCF, which causes abnormal stator currents due to three-winding conduction in BLDC motors. The effectiveness of the proposed approach is validated through experimental results obtained from a 36 V, 400 W BLDC motor drive.

IEEE Transactions on Energy ConversionVol. 40(4)
Indian Institute of Technology Ropar (IN), Nanyang Technological University (SG)
Affordable and clean energy
Openalex Percentile: Top 30%
Multilevel Inverters and Converters
0.73
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.