A novel decoupling control method based on neural network for EV's Driving PMSM

Permanent Magnet Synchronous Motor (PMSM) is often used in Electrified Vehicle (EV), while its Id (direct-axis current) and Iq (quadrature-axis current) are coupled. Traditional FOC (Field Oriented Control) method can't get an accurate decoupling control of them when the motor speed changed wit...

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Bibliographic Details
Published inIOP conference series. Materials Science and Engineering Vol. 383; no. 1; pp. 12038 - 12043
Main Authors Zhao, Wanbang, Song, Qiang, Huang, Yishan
Format Journal Article
LanguageEnglish
Published Bristol IOP Publishing 01.07.2018
Subjects
Control methods
Controllers
Decoupling
Driving conditions
Electric potential
Feedback control
High speed
Negative feedback
Network control
Neural networks
Permanent magnets
Proportional integral derivative
Quadratures
Synchronous motors
Voltage
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Summary:Permanent Magnet Synchronous Motor (PMSM) is often used in Electrified Vehicle (EV), while its Id (direct-axis current) and Iq (quadrature-axis current) are coupled. Traditional FOC (Field Oriented Control) method can't get an accurate decoupling control of them when the motor speed changed with the vehicle's driving condition, especially at high speed. This coupling issue leads an unstable torque output. And further, it deteriorates the NVH (noise vibration and harshness) performance of EV. This paper focuses on the decoupling solution and puts forward a new control strategy which combines the neural network control idea with FOC method. The novel method gives a neural network controller based on four single neuron PID controllers, which its function is to realize the d-q axis interacted adjustment and decoupling. Four single neurons PID controllers achieve the negative feedback control of Id to Ud (direct-axis voltage), Iq to Ud, Iq to Uq (quadrature-axis voltage), and Id to Uq respectively. Creatively, it takes PMSM speed as one of the neuron inputs to adjust the feedback weight of Id and Iq dynamically. A comparing simulation which is set up in the Simulink platform is given in this paper. Simulation results show that this method gives a good self-adaptiveness and decouples the influence of Id and Iq, as well as improve the motor control quality at high speed.
ISSN:1757-8981
1757-899X
DOI:10.1088/1757-899X/383/1/012038