Toggle Main Menu Toggle Search

Open Access padlockePrints

Life Cycle Assessment of Electrical Machines – A Case Study

Lookup NU author(s): Dr Rafal Wrobel, Dr Mohammad RajaeifarORCiD, Professor Barrie Mecrow

Downloads


Licence

This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

This paper quantifies the environmental impacts of a range of electrical machines to demonstrate some of the challenges associated with such an evaluation. Emissions across the supply and value chain of machines are considered, which include the raw material supplies, manufacturing and processing, in-application use and maintenance, and reuse, recycling and final disposal. In this study, a set of cordless power tools (combi drills) was selected as a platform for the comparison. The drills were outsourced from a single manufacturer across a broad price range, i.e. budget, mid-range and premium drills including both brushed and brushless motor technology. The study highlights the complexity of the problem, where a fine balance amongst a multitude of factors needs to be found to achieve specific environmental targets over the lifetime of an electrical machine. The limited availability of life cycle inventory (LCI) data specific to the electrical machines, together with relatively low resolution (granularity) of the LCI data related to materials extraction, product manufacturing and recycling processes are some of the key obstacles in providing a more insightful LCA. Clearly, some of the findings are specific to the analysed machines, however some issues related to an accurate (representative) LCA are more generic and are applicable to a variety of electrical machines and their applications.


Publication metadata

Author(s): Wrobel R, Rajaeifar MA, Mecrow B

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: 2024 IEEE Energy Conversion Congress and Exposition (ECCE)

Year of Conference: 2024

Pages: 5611-5618

Online publication date: 10/02/2025

Acceptance date: 19/05/2024

Date deposited: 04/08/2025

ISSN: 2329-3748

Publisher: IEEE

URL: https://doi.org/10.1109/ECCE55643.2024.10861841

DOI: 10.1109/ECCE55643.2024.10861841

ePrints DOI: 10.57711/jvza-s187

Library holdings: Search Newcastle University Library for this item

ISBN: 9798350376067


Share