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An Improved Model Predictive Current Controller of Switched Reluctance Machines Using Time-Multiplexed Current

Bingchu Li1, Xiao Ling2, Yixiang Huang3

  • 1School of Mechanical Engineering, Shanghai JiaoTong University, 800 Dongchuan Road, Minhang Qu, Shanghai 200240, China. bcli@sjtu.edu.cn.

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|May 18, 2017
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Summary
This summary is machine-generated.

A novel model predictive current controller uses a single multiplexed current sensor for switched reluctance machine (SRM) drives. This cost-effective approach achieves accurate current sampling and control, comparable to systems with multiple sensors.

Keywords:
current controllerfixed switching frequencymodel predictive controlmultiplexed current sensorswitched reluctance machine

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Area of Science:

  • Electrical Engineering
  • Power Electronics
  • Control Systems

Background:

  • Switched reluctance machines (SRMs) require precise current control for efficient operation.
  • Traditional current sensing methods in SRMs often involve multiple sensors, increasing cost and complexity.
  • Model predictive control (MPC) offers advanced current tracking but typically relies on accurate, multi-channel current feedback.

Purpose of the Study:

  • To develop and validate a fixed-switching-frequency model predictive current controller for SRM drives utilizing a multiplexed current sensor.
  • To reduce the cost and hardware complexity of SRM drives by employing a single current sensor.
  • To demonstrate the effectiveness of time-division multiplexing for phase current sampling in an SRM converter.

Main Methods:

  • A modified converter design enabled distinguishing currents from simultaneously excited phases using a single sensor.
  • Time-division multiplexing (TDM) was employed for phase current sampling, with staggered sampling times during commutation.
  • Pulse width modulation (PWM) duty ratios were limited to ensure sufficient analog-to-digital (A/D) conversion time.

Main Results:

  • The proposed multiplexed current sensing achieved satisfied current sampling with minimal difference compared to independent sensors.
  • The model predictive current controller demonstrated high accuracy in tracking reference current profiles, comparable to controllers with independent sensors.
  • The system exhibited minor tracking errors relative to a hysteresis current controller, validating its performance.

Conclusions:

  • A cost-effective and efficient current control strategy for SRM drives using a multiplexed current sensor has been successfully proposed and verified.
  • The TDM approach for current sensing is feasible and does not require complex adjustments to driver circuits or control algorithms.
  • This method offers a viable alternative for reducing hardware costs and potential sensor inconsistencies in SRM applications.