A Tool for Generating Individual Driving Cycles - IDCB

Authors Abstract
Content
Standardized driving cycles, such as the New European Driving Cycle (NEDC) in Europe or the Federal Test Procedure 75 (FTP-75) in the U.S. are an important tool to certify new vehicle models. They are used to estimate real world fuel consumption as well as real world emissions. The latter has recently become more important with the stronger focus on green driving, resulting in much stricter emission regulations, while fuel consumption still remains one of the most important aspects in terms of economy and long term costs for the vehicle owner. However these cycles do not reflect the actual behaviour of the driver or regional influences (i.e. topography). Therefore, manufacturers have developed their own usage and test cycles and are able to extract data from the vehicle to analyse the individual driving behaviour and vehicle usage. Apart from that, Naturalistic Driving Observation (NDO) is interested in understanding the driver. Thus, methods are required to create individual driving cycles (or derive them from large sets of recorded data) that can be used to describe the behaviour of a single driver as well as a group. However, creating driving cycles “by hand” is time consuming and less effective due to the large amount of data. The paper presents the Individual Driving Cycle Builder (IDCB), a software tool that automatically creates an individual driving cycle based on individual driving data. The cycle construction process itself is based on the same method used to create the ARTEMIS driving cycles. To verify the IDCB method, 15 created cycles are compared against the original data as well as several standardised driving cycles.
Meta TagsDetails
DOI
https://doi.org/10.4271/2016-01-9019
Pages
12
Citation
Grüner, J., and Marker, S., "A Tool for Generating Individual Driving Cycles - IDCB," Commercial Vehicles 9(2):417-428, 2016, https://doi.org/10.4271/2016-01-9019.
Additional Details
Publisher
Published
Sep 16, 2016
Product Code
2016-01-9019
Content Type
Journal Article
Language
English