Real-Time Dynamic Brake Assessment for Heavy Commercial Vehicle Safety

2020-01-1646

10/05/2020

Features
Event
Brake Colloquium & Exhibition - 38th Annual
Authors Abstract
Content
This paper summarizes initial results and findings of a model developed to determine the braking performance of commercial motor vehicles in motion regardless of brake type or gross weight. Real-world data collected by Oak Ridge National Laboratory for a U.S. Department of Energy study was used to validate the model. Expanding on previous proof-of-concept research showing the linear relationship of brake application pressure and deceleration additional parameters such as elevation were added to the model. Outputs from the model consist of coefficients calculated for every constant pressure braking event from a vehicle that can be used to calculate a deceleration and thus compute a stopping distance for a given scenario. Using brake application pressure profiles derived from the dataset, stopping distances for light and heavy loads of the same vehicle were compared for various speed and road grades. For a constant brake application pressure profile (i.e. the pressure is relatively constant throughout the entire stop) it was shown that the lighter vehicle was able to stop in a shorter distance than the heavier vehicle in most scenarios other than large uphill grades. Significant changes in weight can be observed through the fuel efficiency of the vehicle to determine if the model needs to be calibrated with new or additional braking events. The model was initially developed for tracking brake performance to inform routine maintenance and the ordering of vehicles in a platoon but can be expanded to other connected and automated research areas.
Meta TagsDetails
DOI
https://doi.org/10.4271/2020-01-1646
Pages
11
Citation
Siekmann, A., Franzese, O., and Lascurain, M., "Real-Time Dynamic Brake Assessment for Heavy Commercial Vehicle Safety," SAE Technical Paper 2020-01-1646, 2020, https://doi.org/10.4271/2020-01-1646.
Additional Details
Publisher
Published
Oct 5, 2020
Product Code
2020-01-1646
Content Type
Technical Paper
Language
English