Yasami, Amirreza, Tofigh, Mohamadali, Shahbakhti, Mahdi et Koch, Charles Robert.
2025.
« Representative driving cycle construction incorporating road grade transitions using a Markov-chain method ».
In Proceedings of the CSME-CFDSC-CSR 2025 International Congress (Montreal, QC, Canada, May 25-28, 2025)
Coll. « Progress in Canadian Mechanical Engineering », vol. 8.
Prévisualisation |
PDF
338 - Representative driving cycle const.pdf - Version publiée Licence d'utilisation : Tous les droits réservés aux détenteurs du droit d'auteur. Télécharger (8MB) | Prévisualisation |
Résumé
Driving cycles are needed for vehicle design, fueleconomy analysis, and transportation emission estimation. Despitetheir significant role, conventional driving cycle construction methodsoften fail to capture the full range of real-world driving dynamics,primarily due to their limited consideration of road grade. In thiswork, a Markov Chain-Based (MCB) methodology for constructingrepresentative driving cycles is presented, which integrates extensivereal-world data, including vehicle speed, acceleration, and road grade.By leveraging a sparse transition matrix, our proposed approachenhances computational efficiency and is scalable to large statespaces. Experimental evaluations demonstrate that incorporating roadgrade significantly improves driving cycle representativeness, withthe mean Vehicle Specific Power (VSP) changing from 1.45 to1.44 kW/tonne (a 0.69% decrease), variance increasing from 4.29to 6.15 (a 43.3% increase), and the maximum VSP rising from7.53 to 11.6 kW/tonne (a 54.2% increase). Quantitative assessmentsfurther demonstrate that while average speed and acceleration errorsare maintained within 8.31% and 6.03%, respectively, idling time isunderestimated by 68.7% compared to the experimental data, which isa potential area for future refinement. Overall, the results underscorethat the representative driving cycle incorporating vehicle speed,acceleration, and road grade provides a better foundation for accurateperformance evaluations and emissions analyses. Future research willfocus on further optimizing computational efficiency and extendingthe framework to account for additional variables such as weatherconditions and cold climate effects, helping to contribute to theadvancement of next-generation, eco-friendly transportation systems.
| Type de document: | Compte rendu de conférence |
|---|---|
| Éditeurs: | Éditeurs ORCID Hof, Lucas A. NON SPÉCIFIÉ Di Labbio, Giuseppe NON SPÉCIFIÉ Tahan, Antoine NON SPÉCIFIÉ Sanjosé, Marlène NON SPÉCIFIÉ Lalonde, Sébastien NON SPÉCIFIÉ Demarquette, Nicole R. NON SPÉCIFIÉ |
| Date de dépôt: | 18 déc. 2025 15:34 |
| Dernière modification: | 18 déc. 2025 15:34 |
| URI: | https://espace2.etsmtl.ca/id/eprint/32526 |
Actions (Authentification requise)
![]() |
Dernière vérification avant le dépôt |

