RESEARCH PAPER
Multi-objective optimization of the deck structure of the lightweight micro-vehicle for improved reliability and desired comfort and stability while driving
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1
Institute of Mechanics and Computational Engineering, Faculty of Mechanical Engineering, Military University of Technology, Poland
2
Department of Industrial Engineering, Università degli Studi di Firenze, Italy
Submission date: 2025-04-09
Final revision date: 2025-04-30
Acceptance date: 2025-06-08
Online publication date: 2025-06-11
Publication date: 2025-06-11
Corresponding author
Kamil Sybilski
Institute of Mechanics and Computational Engineering, Faculty of Mechanical Engineering, Military University of Technology, gen. Sylwester Kaliski Street 2, 00-908, Warsaw, Poland
Eksploatacja i Niezawodność – Maintenance and Reliability 2025;27(4):206048
HIGHLIGHTS
- Novel approach to design of main deck of e-scooter.
- Actual distribution of loads on deck.
- A comparison of two optimization techniques.
- Optimal thickness of deck.
- Low-maintenance and reliable design.
KEYWORDS
TOPICS
ABSTRACT
Electric kick scooters represent a viable alternative to reduce emissions associated with the use of cars. However, several obstacles hinder the widespread adoption of e-scooters, primarily stemming from their high mass, short range, and challenges in navigating uphill routes. The LEONARDO project aims to develop an innovative, 10 kg microvehicle with high torque, similar to a monowheel, while maintaining the ease of riding. To achieve this goal, heavy and complex suspension components were eschewed. In order to maintain ride comfort and stability, it was necessary to design a scooter deck with a specific susceptibility, but one that provided a high level of vehicle reliability.
The article presents a novel approach to the design of a microvehicle deck. The methodology and the results of measuring operational loads are presented, which were used to develop a design that meets the assumed level of reliability, comfort and stability. The study employs a comparative analysis of two distinct optimization algorithms, each accounting for varying load scenarios and multiple objectives.
ACKNOWLEDGEMENTS
The article was co-financed from the state budget of Poland and awarded by the Minister of Science within the framework of the Excellent Science II Programme.
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