Investigating Steady-State Road Load Determination Methods for Electrified Vehicles and Coordinated Driving (Platooning)

2018-01-0649

04/03/2018

Features
Event
WCX World Congress Experience
Authors Abstract
Content
Reductions in vehicle drive losses are as important to improving fuel economy as increases in powertrain efficiencies. In order to measure vehicle fuel economy, chassis dynamometer testing relies on accurate road load determinations. Road load is currently determined (with some exceptions) using established test track coastdown testing procedures. Because new vehicle technologies and usage cases challenge the accuracy and applicability of these procedures, on-road experiments were conducted using axle torque sensors to address the suitability of the test procedures in determining vehicle road loads in specific cases. Whereas coastdown testing can use vehicle deceleration to determine load, steady-state testing can offer advantages in validating road load coefficients for vehicles with no mechanical neutral gear (such as plug-in hybrid and electric vehicles). Steady-state testing may also be the only way to directly evaluate vehicle loads during coordinated driving (platooning or automated cruise control). Several electrified test vehicles with axle torque sensors were tested on a flat, level stretch of pavement to (1) validate/compare to conventional coastdown testing loads, and (2) investigate road load reductions from two-car platooning for the front and rear vehicles at varied following distances. Results show that steady-state testing provides a suitable alternative to coastdown procedures, while test data suggest that a two car on-road platooning scenario offers a potential 15% reduction in road load following at close distances.
Meta TagsDetails
DOI
https://doi.org/10.4271/2018-01-0649
Pages
7
Citation
Duoba, M., and Jehlik, F., "Investigating Steady-State Road Load Determination Methods for Electrified Vehicles and Coordinated Driving (Platooning)," SAE Technical Paper 2018-01-0649, 2018, https://doi.org/10.4271/2018-01-0649.
Additional Details
Publisher
Published
Apr 3, 2018
Product Code
2018-01-0649
Content Type
Technical Paper
Language
English