Drivability Evaluation Model of Engine Start Based on Principal Component Analysis and Support Vector Regression Tongji University

Format:

Book

Conference/Event

Author/Creator:

Huang, Huang, author.

Contributor:

Liu, Jiang

Ma, Yifei

Conference Name:

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

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2019

Summary:

AbstractAiming at the problem that the evaluation model had proposed by researchers to evaluate the drivability of a vehicle in the process of engine start to exist poor stability and poor accuracy. In this paper, a drivability evaluation model combined with principal component analysis and support vector regression is proposed. In this evaluation model, the principal component analysis is adapted to determine the input index of evaluation model, and the drivability evaluation model is built on the basis of support vector regression. The experimental results demonstrate that the drivability evaluation model is proposed by this paper has higher accuracy and stability than the model using the BP neural network. This method can be as well extended to other evaluation models, with higher theoretical guidance and application value in practical issues

Notes:

Vendor supplied data

Publisher Number:

2019-01-0932

Access Restriction:

Restricted for use by site license