Statistical Determination of Local Driving Cycles Based on Experimental Campaign as WLTC Real Approach

2017-24-0138

09/04/2017

Features
Event
13th International Conference on Engines & Vehicles
Authors Abstract
Content
In the context of a transport sustainability, some solutions could be proposed from the integration of many disciplines, architects, environmentalists, policy makers, and consequently it may be addressed with different approaches. These solutions would be applied at different geographical levels, i.e. national, regional or urban scale. Moreover, the assessment of cars emissions in real use plays a fundamental role for their reductions. This is also the direction of the new harmonized test procedures (WLTP). Furthermore, it is fundamental to keep in mind that the new WLTC cycle will reproduce a situation closer to the reality comparing to the EUDC/NEDC driving cycle. In this paper, we will be focused on vehicle kinematic evaluation aimed at valuation of traffic situation and emissions. For this purpose, driving data and emissions were acquired during an experimental campaign through six instrumented vehicles by PEMS for the simultaneous acquisition of emissions, kinematic variables and GPS localization data. Moreover, the analyzed vehicles have different type approval classes and different displacements. At this time, we present a different statistical approach to classify the pieces of speed parts in order to identify typical traffic situation and their emission evaluation. Finally, apply some statistical criteria, and going in the same direction of WLTC, a driving cycle composed by a succession of speed parts was built.
Meta TagsDetails
DOI
https://doi.org/10.4271/2017-24-0138
Pages
10
Citation
Meccariello, G., and Della Ragione, L., "Statistical Determination of Local Driving Cycles Based on Experimental Campaign as WLTC Real Approach," SAE Technical Paper 2017-24-0138, 2017, https://doi.org/10.4271/2017-24-0138.
Additional Details
Publisher
Published
Sep 4, 2017
Product Code
2017-24-0138
Content Type
Technical Paper
Language
English