Drivability Evaluation Model of Engine Start Based on Principal Component Analysis and Support Vector Regression 2019-01-0932
Aiming 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.
Citation: Huang, W., Liu, J., and Ma, Y., "Drivability Evaluation Model of Engine Start Based on Principal Component Analysis and Support Vector Regression," SAE Technical Paper 2019-01-0932, 2019, https://doi.org/10.4271/2019-01-0932. Download Citation
Author(s):
Wei Huang, Jiang Liu, Yifei Ma
Affiliated:
Tongji University
Pages: 6
Event:
WCX SAE World Congress Experience
ISSN:
0148-7191
e-ISSN:
2688-3627
Related Topics:
Ignition systems
Statistical analysis
Starters and starting
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