Synthesis of Representative Driving Cycle for Heavy Duty Vehicle Based on Markov Chain and Big Data Considering Weight Variation

2023-32-0177

09/29/2023

Features
Event
2023 JSAE/SAE Powertrains, Energy and Lubricants International Meeting
Authors Abstract
Content
Synthesized driving cycles which can reflect the real world driving scenarios are essential for electrification and hybridization of powertrains of heavy duty logistics vehicles (HDLV). Current synthetic methods always neglected weight variation which is crucial for logistic vehicle driving scenarios. This paper proposed a method based on multi-dimensional Markov chains and big data to generate typical driving cycles with consideration of vehicle weight and slope. The validation of the synthesized driving cycle was based on a statistical analysis and the adequacy of the representative to real world driving data was demonstrated.
Meta TagsDetails
DOI
https://doi.org/10.4271/2023-32-0177
Pages
7
Citation
Liu, Z., Li, Y., Tan, G., Xu, L. et al., "Synthesis of Representative Driving Cycle for Heavy Duty Vehicle Based on Markov Chain and Big Data Considering Weight Variation," SAE Technical Paper 2023-32-0177, 2023, https://doi.org/10.4271/2023-32-0177.
Additional Details
Publisher
Published
Sep 29, 2023
Product Code
2023-32-0177
Content Type
Technical Paper
Language
English