کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
303686 | 512750 | 2012 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Implementation of an optimal control strategy for a hydraulic hybrid vehicle using CMAC and RBF networks
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی عمران و سازه
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چکیده انگلیسی
A control strategy on a hybrid vehicle can be implemented through different methods. In this paper, the Cerebellar Model Articulation Controller (CMAC) and Radial Basis Function (RBF) neural networks were applied to develop an optimal control strategy for a split parallel hydraulic hybrid vehicle. These networks contain a nonlinear mapping, and, also, the fast learning procedure has made them desirable for online control. The RBF network was constructed with the use of the K-mean clustering method, and the CMAC network was investigated for different association factors. Results show that the binary CMAC has better performance over the RBF network. Also, the hybridization of the vehicle results in considerable reduction in fuel consumption.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Scientia Iranica - Volume 19, Issue 2, April 2012, Pages 327–334
Journal: Scientia Iranica - Volume 19, Issue 2, April 2012, Pages 327–334
نویسندگان
A. Taghavipour, M.S. Foumani, M. Boroushaki,