ENGLISH
La vitrine de diffusion des publications et contributions des chercheurs de l'ÉTS
RECHERCHER

Representative driving cycle construction incorporating road grade transitions using a Markov-chain method

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.

[thumbnail of 338 - Representative driving cycle const.pdf]
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 Dernière vérification avant le dépôt