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Supporting the Transition Towards Electromobility in the Construction and Mining Sector: Optimization Framework and Demonstration on an Electrical Hauler

Published online by Cambridge University Press:  26 May 2022

R. J. Machchhar  and
A. Bertoni
R. J. Machchhar*
Affiliation:
Blekinge Institute of Technology, Sweden
A. Bertoni
Affiliation:
Blekinge Institute of Technology, Sweden
*
[email protected]

Abstract

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The paper presents a framework for the integration of the system's design variables, state variables, control strategies, and contextual variables into a design optimization problem to assist early-stage design decisions. The framework is based on a global optimizer incorporating Dynamic Programming, and its applicability is demonstrated by the conceptual design of an electrical hauler. Pareto front of optimal design solutions, in terms of time and cost, together with optimal velocity profiles and battery state-of-charge is visualized for the given mining scenario.

Keywords

systems engineering (SE)decision makingdesign optimisationdynamic programmingearly design phase
Type
Article
Information
Proceedings of the Design Society , Volume 2: DESIGN2022 , May 2022 , pp. 1649 - 1658
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2022.

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