Development of Intelligent Gear-Shifting Map Based on Radial Basis Function Neural Networks
- Authors
- 하상형; 전홍태
- 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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Collections - College of ICT Engineering > School of Electrical and Electronics Engineering > 1. Journal Articles
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