A multiple regression approach to estimating traction machine brake torque

Abstract

This study proposes a novel method for estimating braking torque in elevator traction machines using multiple regression analysis. The method employs three key parameters, including static torque, brake temperature, and air gap. Experimental validation conducted with an elevator traction machine brake (rated at 240 N・m) demonstrates that this method enables the quantitative evaluation of braking torque during periodic inspections, contributing to enhanced safety and improved maintenance efficiency. Additionally, this approach complies with the recent regulatory requirements for Unintended Car Movement Protection (UCMP) and offers a practical and efficient solution for field technicians.