Journal of Jilin University(Engineering and Technology Edition) ›› 2022, Vol. 52 ›› Issue (10): 2213-2224.doi: 10.13229/j.cnki.jdxbgxb20210227

   

Deadbeat predictive voltage compensation control for permanent magnet synchronous hub motors of electric vehicles

Xiao-dong SUN(),Yao ZHANG,Long CHEN   

  1. Automotive Engineering Research Institute，Jiangsu University，Zhenjiang 212013，China
  • Received:2021-03-22 Online:2022-10-01 Published:2022-11-11

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Abstract:

The traditional deadbeat predictive current control is dependent on mathematical model. The parameter mismatch caused by temperature change will increase the current response error and current pulsation. To solve these problems， a deadbeat predictive voltage compensation control （DPVCC） strategy based on composite sliding mode disturbance observer （CSMDO） was proposed. The observer can estimate the future current value and the lumped perturbation of the system simultaneously and compensate them into the voltage vector to improve the robustness. The MATLAB/Simulink simulation and experimental results based on a 30 kW permanent magnet synchronous hub motor show that DPVCC can reduce the current error more than 60%， which can restrain current pulsation， improve the accuracy and robustness of the control system.

Key words: vehicle engineering, permanent magnet synchronous hub motor, deadbeat predictive control, sliding mode disturbance observer, voltage compensation, robust control

CLC Number: 

  • TM341

Fig.1

Block diagram of conventional DPCC"

Table 1

Main parameters of permanent magnet synchronous hub motor"

参 数符 号数 值
极对数pn22
定子电阻/ΩRs0.8
d?轴电感/mHLs4.5
q?轴电感/mHLs4.5
永磁体磁链/Wbψf0.215
转动惯量/（kg·m2）J0.03
额定转速/（r·min-1）N360
额定功率/kWPN30

Fig.2

Current error under inductance and resistance parameter mismatches（parameter mismatch range 50%）"

Fig.3

Current error under inductance and permanent magnet flux linkage mismatches（parameter mismatch range 50%）"

Fig.4

Block diagram of deadbeat predictive voltage compensation control based on composite sliding modedisturbance observer"

Fig.5

Experimental platform of PMSHM system"

Fig.6

Simulation results of the two control strategies under different parameter mismatches"

Fig.7

Experimental results of two control strategies under different parameter mismatches"

Fig.8

Experimental results under parametermismatches （0.1Ls +0.1ψf ）"

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