Document Type

Article

Publication Date

2025

DOI

10.3390/electronics14183598

Publication Title

Electronics

Volume

14

Issue

18

Pages

3598

Abstract

As robotic systems advance in autonomy and sophistication while being used in uncertain environments, the challenge of building reliable and robust electric motors that are embedded into robotic systems has never been a more important engineering problem. Thermal distress caused by extended operation or excessive loading can negatively affect a motor’s performance and efficiency and lead to catastrophic hardware failure. This paper proposes a novel intelligent control framework that includes real-time thermal feedback for hybrid electric motors that are embedded into robotic systems. The framework relies on adaptive control techniques and lightweight machine learning techniques to estimate internal motor temperatures and dynamically change operational parameters. Unlike traditional reactive methods, this framework provides a spacious active/predictive method of heat management, while preserving efficiency and allowing for responsive control. Simulations, experimental validations, and preliminary trials that deployed real robotic systems demonstrated that our framework allows for reductions in peak temperatures by up to 18% and extends motor lifetime by 22%, while retaining control stability and a range of variations in PWM adjustments of ±12% across disparate workloads. These results demonstrate the efficacy of intelligent and thermally aware motor control architectures and processes to improve the reliability of autonomous robotic systems and open the door for next-generation embedded controllers that will allow robotic platforms to self-manage thermal effects in resilient, adaptable robots.

Rights

© 2025 The Authors

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) License.

Data Availability

Article states: "Data is contained within the article."

Original Publication Citation

Shili, M., Hammedi, S., Chaoui, H., & Nouri, K. (2025). A novel intelligent thermal feedback framework for electric motor protection in embedded robotic systems. Electronics, 14(18), Article 3598. https://doi.org/10.3390/electronics14183598

ORCID

0000-0001-8728-3653 (Chaoui)

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