Optimized dispatchable battery swapping strategy for electric non-road mobile machinery systems
Wallander, Edvin LU and Márquez-Fernández, Francisco J. LU
(2025)
In Energy
339.
- Abstract
The imperative to reduce greenhouse gas emissions is intensifying in various sectors. This trend is evident in the non-road mobile machinery sectors, including agricultural and construction equipment, where the electrification of machinery is emerging as a key development. However, battery-electric non-road mobile machinery systems face challenges, primarily due to the limited energy storage capacity of batteries. One proposed solution to address these constraints is the dispatchable battery swapping strategy. This paper presents a novel multi-objective bilevel optimization algorithm for planning battery dispatch operations in non-road mobile machinery systems. The methodology optimizes battery logistics and energy cost utilizing a... (More)
The imperative to reduce greenhouse gas emissions is intensifying in various sectors. This trend is evident in the non-road mobile machinery sectors, including agricultural and construction equipment, where the electrification of machinery is emerging as a key development. However, battery-electric non-road mobile machinery systems face challenges, primarily due to the limited energy storage capacity of batteries. One proposed solution to address these constraints is the dispatchable battery swapping strategy. This paper presents a novel multi-objective bilevel optimization algorithm for planning battery dispatch operations in non-road mobile machinery systems. The methodology optimizes battery logistics and energy cost utilizing a genetic algorithm and a linear program model. A case study is conducted utilizing an agricultural model to generate battery swapping events with a variety of system parameters. The system incorporates local energy generation, varying electricity prices and two work-load scenarios: a high work-load and a light work-load scenario. The results demonstrate that the system's flexibility significantly influences energy costs. Systems with a greater number of smaller batteries have an energy cost difference of 39% compared to systems with fewer large batteries. A trade-off between transportation distance and energy cost is identified, specifically, an energy cost reduction of up to 4.7%, is achievable with an increase in transportation distance of up to 75%. Notably, in the light work-load scenario, the net energy cost is negative, indicating that operators can achieve a net financial gain on days when less energy-intensive operations are performed.
(Less)
- author
- Wallander, Edvin
LU
and Márquez-Fernández, Francisco J.
LU
- organization
- publishing date
- 2025-12-01
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Battery swapping, Electric non-road mobile machinery, Energy management, Genetic algorithm, Linear programming
- in
- Energy
- volume
- 339
- article number
- 138981
- pages
- 13 pages
- publisher
- Elsevier
- external identifiers
-
- scopus:105020261997
- ISSN
- 0360-5442
- DOI
- 10.1016/j.energy.2025.138981
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2025 The Authors
- id
- 5d3b017e-ec96-4121-9ab4-183e74c12a8c
- date added to LUP
- 2025-11-07 10:51:19
- date last changed
- 2025-11-10 12:57:35
@article{5d3b017e-ec96-4121-9ab4-183e74c12a8c,
abstract = {{<p>The imperative to reduce greenhouse gas emissions is intensifying in various sectors. This trend is evident in the non-road mobile machinery sectors, including agricultural and construction equipment, where the electrification of machinery is emerging as a key development. However, battery-electric non-road mobile machinery systems face challenges, primarily due to the limited energy storage capacity of batteries. One proposed solution to address these constraints is the dispatchable battery swapping strategy. This paper presents a novel multi-objective bilevel optimization algorithm for planning battery dispatch operations in non-road mobile machinery systems. The methodology optimizes battery logistics and energy cost utilizing a genetic algorithm and a linear program model. A case study is conducted utilizing an agricultural model to generate battery swapping events with a variety of system parameters. The system incorporates local energy generation, varying electricity prices and two work-load scenarios: a high work-load and a light work-load scenario. The results demonstrate that the system's flexibility significantly influences energy costs. Systems with a greater number of smaller batteries have an energy cost difference of 39% compared to systems with fewer large batteries. A trade-off between transportation distance and energy cost is identified, specifically, an energy cost reduction of up to 4.7%, is achievable with an increase in transportation distance of up to 75%. Notably, in the light work-load scenario, the net energy cost is negative, indicating that operators can achieve a net financial gain on days when less energy-intensive operations are performed.</p>}},
author = {{Wallander, Edvin and Márquez-Fernández, Francisco J.}},
issn = {{0360-5442}},
keywords = {{Battery swapping; Electric non-road mobile machinery; Energy management; Genetic algorithm; Linear programming}},
language = {{eng}},
month = {{12}},
publisher = {{Elsevier}},
series = {{Energy}},
title = {{Optimized dispatchable battery swapping strategy for electric non-road mobile machinery systems}},
url = {{http://dx.doi.org/10.1016/j.energy.2025.138981}},
doi = {{10.1016/j.energy.2025.138981}},
volume = {{339}},
year = {{2025}},
}