کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
645350 1457139 2015 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Electric vehicle air conditioning system performance prediction based on artificial neural network
ترجمه فارسی عنوان
پیش بینی عملکرد سیستم تهویه مطبوع خودرو بر اساس شبکه عصبی مصنوعی
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی جریان سیال و فرایندهای انتقال
چکیده انگلیسی
In this study, electric vehicle air conditioning system (EVACS) performances with scroll compressor and electronic expansion valve (EEV) were experimentally investigated by varying scroll compressor speed, EEV opening and environment temperature. An artificial neural network (ANN) model for EVACS performances (such as refrigerant mass flow rate, condenser heat rejection, refrigeration capacity and compressor power consumption) prediction was developed based on experimental data. The ANN model was tested with two transfer functions (logsig and tansig) and different hidden neurons (3-13) using Levernberg-Marquardt algorithm. The optimized ANN was determined as a configuration of 4-13-4 with logsig transfer function, which demonstrated the best capability with mean relative errors, root mean square errors and correlation coefficients in the range of 0.92-2.71%, 0.0044-0.0141 and 0.9975-0.9998, respectively.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Thermal Engineering - Volume 89, 5 October 2015, Pages 101-114
نویسندگان
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