RTOS-Based Task-Driven Scheduling for Vehicle Independent Brushless Direct Current Motor Control

Dongkyu Jung, Daejin Park

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

High-level, self-driving vehicles and unmanned vehicles are completely electronic instead of having traditional mechanical steering methods. Among the electronic steering systems, a motor is assigned to each wheel to simplify the structure of the vehicle, and additional efficiency and functions can be obtained through unique movements. Brushless direct current (BLDC) motors, which operate by applying a voltage pattern controlled by pulse-width modulation(PWM), are advantageous for these systems. When a steering command is entered into the system that outputs a motor signal that changes the PWM pattern, the motor signal output is interrupted during the steering task, which negatively affects the motor's operation. In this situation, if the motor's specific section output signal is ensured, the unexpected effect on the motor's operation can be reduced. This paper proposes a real-time scheduling system led by a motor signal task that ensures phase cycles according to the operating characteristics of a BLDC motor. After generating a motor operation output of a specific phase cycle, the motor signal task checks the priority table of the tasks currently to be performed and continues performing the task or blocks itself. In this case, the length of the phase cycle varies according to the current motor operation state. The scheduler manages the execution status of tasks after the motor signal task is blocked, and updates the priority table by receiving external requests in the form of interrupts. In situations where the motor is accelerating, the proposed method provides a disturbance ratio, that is 20.14% less than that of the general method. In situations where the motor is driven at constant speed, the proposed method provides a disturbance ratio, that is 8.82% less than that of the general method. In both cases, the proposed method showed the highest amount of stability increase in the low-speed section.

Original languageEnglish
Title of host publicationIECON 2023 - 49th Annual Conference of the IEEE Industrial Electronics Society
PublisherIEEE Computer Society
ISBN (Electronic)9798350331820
DOIs
StatePublished - 2023
Event49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023 - Singapore, Singapore
Duration: 16 Oct 202319 Oct 2023

Publication series

NameIECON Proceedings (Industrial Electronics Conference)
ISSN (Print)2162-4704
ISSN (Electronic)2577-1647

Conference

Conference49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023
Country/TerritorySingapore
CitySingapore
Period16/10/2319/10/23

Keywords

  • BLDC motor
  • real-time OS
  • scheduling
  • self-driving vehicles

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