Over the past couple of years, Argonne National Laboratory has tested, analyzed, and validated automobile models for the light duty vehicle class, including several types of powertrains including conventional, hybrid electric, plug-in hybrid electric and battery electric vehicles. Argonne’s previous works focused on the light duty vehicle models, but no work has been done on medium and heavy-duty vehicles. This study focuses on the validation of shifting control in advanced automatic transmission technologies for medium duty vehicles by using Argonne’s model-based high-fidelity, forward-looking, vehicle simulation tool, Autonomie.
Different medium duty vehicles, from Argonne’s own fleet, including the Ram 2500, Ford F-250 and Ford F-350, were tested with the equipment for OBD (on-board diagnostics) signal data record. For the medium duty vehicles, a workflow process was used to import test data. In addition to importing measured test signals into the Autonomie environment, the process also calculated some of the critical missing signals, such as each component effort or flow signal. Numerous analysis functions have been developed to quickly analyze the shifting map, using the integrated test data in Autonomie to generate model parameters. In addition, a set of calibrations for the generic shifting algorithm was developed to match the test data. Finally, we demonstrated the validation of Autonomie transmission component models and shifting control strategy by using medium duty vehicle test data over different driving records.