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Design and Implementation of a Data-Driven Defect and Linearity Assessment Monitoring System for Electric Power Steering

  • Journal of Internet of Things and Convergence
  • Abbr : JKIOTS
  • 2023, 9(2), pp.61-69
  • Publisher : The Korea Internet of Things Society
  • Research Area : Engineering > Computer Science > Internet Information Processing
  • Received : February 3, 2023
  • Accepted : March 3, 2023
  • Published : April 30, 2023

Lawal Alabe Wale 1 키에 킴렁 1 Youngsun Han 2 TaeKyung Kim 3

1부경대
2부경대학교
3인천재능대학교

Accredited

ABSTRACT

In recent years, due to heightened environmental awareness, Electric Power Steering (EPS) has been increasingly adopted as the steering control unit in manufactured vehicles. This has had numerous benefits, such as improved steering power, elimination of hydraulic hose leaks and reduced fuel consumption. However, for EPS systems to respond to actions, sensors must be employed; this means that the consistency of the sensor's linear variation is integral to the stability of the steering response. To ensure quality control, a reliable method for detecting defects and assessing linearity is required to assess the sensitivity of the EPS sensor to changes in the internal design characters. This paper proposes a data-driven defect and linearity assessment monitoring system, which can be used to analyze EPS component defects and linearity based on vehicle speed interval division. The approach is validated experimentally using data collected from an EPS test jig and is further enhanced by the inclusion of a Graphical User Interface (GUI). Based on the design, the developed system effectively performs defect detection with an accuracy of 0.99 percent and obtains a linearity assessment score at varying vehicle speeds.

Citation status

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