A Particle Swarm Optimization-Based Method for Fast Parametrization of Transmission Plant Models Ford Motor Company

Format:

Conference/Event

Author/Creator:

Liu, Pinzhi, author.

Contributor:

Dai, Edward

Jiang, Weiran

McCullough, Todd

Wu, Guang

Xu, Yang

Conference Name:

WCX SAE World Congress Experience (2019-04-09 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2019

Summary:

AbstractTransmission system models require a high level of fidelity and details in order to capture the transient behaviors in drivability and fuel economy simulations. Due to model fidelity, manufacturing tolerances, frictional losses and other noise sources, parametrization and tuning of a large number of parameters in the plant model is very challenging and time consuming. In this paper, we used particle swarm optimization as the key algorithm to fast correlate the open-loop performance of an automatic transmission system plant model to vehicle launch and coast down test data using vehicle control inputs. During normal operations, the model correlated well with test data. For error states, due to the lack of model fidelity, the model cannot reproduce the same error state quantitatively, but provided a valuable methodology for qualitatively identifying error states at the early stages

Notes:

Vendor supplied data

Publisher Number:

2019-01-0344

Access Restriction:

Restricted for use by site license