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Support Vector Machine Theory Based Shift Quality Assessment for Automated Mechanical Transmission (AMT)
Technical Paper
2007-01-1588
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
In China there is a strong trend in the application of vehicles equipped with automatic transmissions in considering the complexity of traffic and the convenience of automatic transmissions. As a type of automatic transmission, automated mechanical transmission (AMT) shows great potential to be developed as a main transmission because of its simple structures, easy upgrade from manual transmission (MT) and low price.
Support Vector Machine (SVM) is a new statistic method which could make a good prediction with limited training instances. Compared with Artificial Neutral Network (ANN), SVM can provide better genetic ability. In order to verify the ability of the new method, the model trained by one set of AMT car data was applied on some other AMT vehicles, and the predicted results were compared with subjective rating results by expert drivers and analyzed to identify the potential of this new assessment system.
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Authors
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Citation
Jian, W., Konghui, G., Yulong, L., and Hua, T., "Support Vector Machine Theory Based Shift Quality Assessment for Automated Mechanical Transmission (AMT)," SAE Technical Paper 2007-01-1588, 2007, https://doi.org/10.4271/2007-01-1588.Also In
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