Harness Model Development by co-simulation of the Transmission Black Box model and Vehicle model for a Medium Heavy Duty Internal Combustion based Powertrain

2019-01-2268

12/19/2019

Event
2019 JSAE/SAE Powertrains, Fuels and Lubricants
Authors Abstract
Content
With the automotive industry moving toward model based development approach, detailed model integration plays an important role in the process. In comparison to map-based models, detailed models have higher fidelity with the results being more accurate & repeatable. High fidelity models are significant as it allows for early design validation through experimentation. The primary objective of this study is to develop a co-simulation between the transmission black box in Simulink and the vehicle model in GT-Suite. The secondary objective of this study is to understand the difference in the fidelity of the map based transmission model and the detailed transmission model. For the detailed transmission model, the transmission black box provided by the supplier, is a comprehensive model setup in the Simulink platform. The co-simulation is initialized from Simulink, where in Simulink acts as the primary platform. The commands are then forwarded to GT-Suite which is embedded in the Simulink environment as an S-function. The co-simulated model has been validated against the data from the field testing. On comparison with the map based transmission model, the detailed transmission model performs much better and is able to closely emulate the real world test results. Applications of this study include fuel economy estimation, performance analysis, component sizing and optimization for current and future powertrain configurations.
Meta TagsDetails
DOI
https://doi.org/10.4271/2019-01-2268
Pages
9
Citation
Shetty, A., Pasupathi, S., Vernham, B., and Bergsieker, G., "Harness Model Development by co-simulation of the Transmission Black Box model and Vehicle model for a Medium Heavy Duty Internal Combustion based Powertrain," SAE Technical Paper 2019-01-2268, 2019, https://doi.org/10.4271/2019-01-2268.
Additional Details
Publisher
Published
Dec 19, 2019
Product Code
2019-01-2268
Content Type
Technical Paper
Language
English