eprintid: 16211
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/62/11
datestamp: 2023-12-19 03:22:45
lastmod: 2023-12-19 03:22:45
status_changed: 2023-12-19 03:05:50
type: article
metadata_visibility: show
creators_name: Rosli, N.S.
creators_name: Ibrahim, R.
creators_name: Ismail, I.
creators_name: Omar, M.
title: Modeling of high voltage induction motor cooling system using linear regression mathematical models
ispublished: pub
keywords: accuracy; Article; cold air; industry; linear regression analysis; Malaysia; mathematical model; root mean squared error; simulation; temperature; temperature measurement; time series analysis; cold; electricity; phase transition; statistical model, Cold Temperature; Electricity; Linear Models; Phase Transition; Temperature
note: cited By 2
abstract: Achieving reliable power efficiency from a high voltage induction motor (HVIM) is a great challenge, as the rigorous control strategy is susceptible to unexpected failure. External cooling is commonly used in an HVIM cooling system, and it is a vital part of the motor that is responsible for keeping the motor at the proper operating temperature. A malfunctioning cooling system component can cause motor overheating, which can destroy the motor and cause the entire plant to shut down. As a result, creating a dynamic model of the motor cooling system for quality performance, failure diagnosis, and prediction is critical. However, the external motor cooling system design in HVIM is limited and separately done in the past. With this issue in mind, this paper proposes a combined modeling approach to the HVIM cooling system which consists of integrating the electrical, thermal, and cooler model using the mathematical model for thermal performance improvement. Firstly, the development of an electrical model using an established mathematical model. Subsequently, the development of a thermal model using combined mathematical and linear regression models to produce motor temperature. Then, a modified cooler model is developed to provide cold air temperature for cooling monitoring. All validated models are integrated into a single model called the HVIM cooling system as the actual setup of the HVIM. Ultimately, the core of this modeling approach is integrating all models to accurately represent the actual signals of the motor cooler temperature. Then, the actual signals are used to validate the whole structure of the model using Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE) analysis. The results demonstrate the high accuracy of the HVIM cooling system representation with less than 1 error tolerance based on the industrial plant experts. Thus, it will be helpful for future utilization in quality maintenance, fault identification and prediction study. Copyright: © 2022 Rosli et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
date: 2022
publisher: Public Library of Science
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143088565&doi=10.1371%2fjournal.pone.0276142&partnerID=40&md5=788c9068e9f3275398b54cf1f070b017
id_number: 10.1371/journal.pone.0276142
full_text_status: none
publication: PLoS ONE
volume: 17
number: 11 Nov
refereed: TRUE
issn: 19326203
citation:   Rosli, N.S. and Ibrahim, R. and Ismail, I. and Omar, M.  (2022) Modeling of high voltage induction motor cooling system using linear regression mathematical models.  PLoS ONE, 17 (11 Nov).   ISSN 19326203