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Development of Intelligent Gear-Shifting Map Based on Radial Basis Function Neural Networks

Authors
하상형전홍태
Issue Date
2013
Publisher
한국지능시스템학회
Keywords
Automatic transmission; Driver’s willingness; Gear-shifting; Normalized rad basis function neural network
Citation
International Journal of Fuzzy Logic and Intelligent systems, v.13, no.2, pp 116 - 123
Pages
8
Journal Title
International Journal of Fuzzy Logic and Intelligent systems
Volume
13
Number
2
Start Page
116
End Page
123
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/19797
ISSN
1598-2645
Abstract
Currently, most automobiles have automatic transmission systems. The gear-shifting strategy used to generate shift patterns in transmission systems plays an important role in improving the performance of vehicles. However, conventional transmission systems have a fixed type of shift map, so it may not be enough to provide an efficient gear-shifting pattern to satisfy the demands of driver. In this study, we developed an intelligent strategy to handle these problems. This approach is based on a normalized radial basis function neural network, which can generate a flexible gear-shift pattern to satisfy the demands of drivers, including comfortable travel and fuel consumption. The method was verified through simulations.
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