Abstract
This paper proposes a low-complexity, fast sensorless collision detection method for permanent-magnet synchronous motors (PMSMs) based on a forgetting-factor recursive least-squares (FFRLS) estimator. The method estimates the load torque from the motor motion equations and detects collisions by monitoring abrupt changes in a processed load-torque metric. The algorithm is tailored for resource-constrained embedded controllers: it avoids high-order matrix operations and the use of external sensors while achieving rapid detection. Experimental results under constant speed, acceleration, and time-varying load conditions demonstrate fast and repeatable detection performance. The approach provides a practical trade-off between computational cost and detection reliability for embedded motor drives.
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All data generated or analysed during this study are included in this published article and its supplementary information files. A simulation model for strategy verification is also included in the supplementary information files.
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Funding
This work was supported by the National Natural Science Foundation of China under Grant No. 62173279 (Project: Multi-level Federated/Migration Learning for Fault Diagnosis of Train Bogies on Sichuan-Tibet Railway).
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D.Z. supervised the study; T.R. proposed this strategy, designed the experiments and wrote the manuscript; GK.H. and MY.L. participated in part of the experimental work. All authors reviewed the manuscript.
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Zhao, D., Ren, T., Huang, G. et al. Fast sensorless collision detection for resource-constrained pmsm controllers using an FFRLS-based method. Sci Rep (2026). https://doi.org/10.1038/s41598-026-43846-5
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DOI: https://doi.org/10.1038/s41598-026-43846-5
