Co-simulation modeling of high performance motor-drive systems for aerospace applications

Onambele, Charles; Mpanda, Augustin; Giacchetti, Francesco

doi:10.1109/iemdc.2017.8002167

Cited by 4 publications

(1 citation statement)

References 15 publications

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“…Various fault detection techniques leverage the benefits of co-simulation tools for motor-drive applications, including inverter switch fault diagnosis [17][18][19]. In [17], the modeling of high-performance multiphase brushless AC (BLAC) machines was investigated for aerospace applications using Simulink and Ansys Twin Builder co-simulation models. The accuracy of the proposed co-simulation model has been proven by simulations for motor-drive systems.…”

Section: Introductionmentioning

confidence: 99%

A Robust Online Diagnostic Strategy of Inverter Open-Circuit Faults for Robotic Joint BLDC Motors

Metwly,

Logan,

Clark

et al. 2024

Machines

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As robots are increasingly used in remote, safety-critical, and hazardous applications, the reliability of robots is becoming more important than ever before. Robotic arm joint motor-drive systems are vulnerable to hardware failures due to harsh operating environment in many scenarios, which may yield various joint failures and result in significant downtime costs. Targeting the most common robotic joint brushless DC (BLDC) motor-drive systems, this paper proposes a robust online diagnostic method for semiconductor faults for BLDC motor drives. The proposed fault diagnostic technique is based on the stator current signature analysis. Specifically, this paper investigates the performance of the BLDC joint motors under open-circuit faults of the inverter switches using finite element co-simulation tools. Furthermore, the proposed methodology is not only capable of detecting any open-circuit faults but also identifying faulty switches based on a knowledge table by considering various fault conditions. The robustness of the proposed technique was verified through extensive simulations under different speed and load conditions. Moreover, simulations have been carried out on a Kinova Gen-3 robot arm to verify the theoretical findings, highlighting the impacts of locked joints on the robot’s end-effector locations. Finally, experimental results are presented to corroborate the performance of the proposed fault diagnostic strategy.

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