Torque Estimation of Permanent Magnet Synchronous Motor (PMSM) Using 1D Convolutional Neural Network

Vishwakarma, S.; Kumar, Anurodh; Vishwakarma, Amit

doi:10.1109/cict56698.2022.9997927

Cited by 1 publication

(2 citation statements)

References 15 publications

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“…When IM actual speed is located in the range of ½v l , v s , k is expressed to equation (9). When IM actual speed comes into the range of ½v s , v h , k is expressed to equation (10).…”

Section: Rotor Total Flux Linkage and Im Torque Modelmentioning

confidence: 99%

“…Liu et al 9 presents a torque estimation scheme for induction motors based on gated recurrent unit and uses recurrent neural network structure to learn the relationship between the excitation and response sequences of the motor. Vishwakarma et al 10 proposes a 1D convolutional neural network for motor torque prediction model and gets this model based on motor data. Du et al 11 proposes a model integration algorithm to optimally fit the nonlinear relationship among electromagnetic torque, motor current, and angle.…”

Section: Introductionmentioning

confidence: 99%

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High-accuracy torque estimation and safety control for induction motor used in electric vehicles

Peng,

Si,

Wang

et al. 2023

Advances in Mechanical Engineering

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As a power output unit, Induction Motor (IM) is widely used in Electric Vehicles (EV) due to its unique advantages of higher power density and better torque ability. With more complicated motor controller system, there are some hardware and software failures which bring some risks including EV unexpected acceleration or deceleration, therefore it is necessary to build high-accuracy torque estimation and safety control strategy. Firstly, hazard and safety concept are analyzed to make sure function safety goals and levels for IM system. Secondly, a novel method of high-accuracy torque estimation is proposed based on a rotor dynamic and composite flux linkage observer. Then, fault diagnosis and handling mechanisms of motor torque are designed to avoid hazards when it is a significant difference between motor estimation torque and vehicle requested torque. Finally, power test and Hardware in Loop (HIL) bench are configured to verify torque estimation accuracy and fault protection mechanisms rationality by comparing test results and injecting related faults. Experiment result shows that motor torque accuracy is within ±5 Nm and fault protection mechanisms can bring motor to safety state promptly.

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“…When IM actual speed is located in the range of ½v l , v s , k is expressed to equation (9). When IM actual speed comes into the range of ½v s , v h , k is expressed to equation (10).…”

Section: Rotor Total Flux Linkage and Im Torque Modelmentioning

confidence: 99%