| 基于径向基神经网络优化汽车除霜性能研究 |
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| 引用本文： | 刘天宏,范平清.基于径向基神经网络优化汽车除霜性能研究[J].农业装备与车辆工程,2020,58(5):106-110. |
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| 作者姓名： | 刘天宏 范平清 |
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| 作者单位： | 201620 上海市 上海工程技术大学机械与汽车工程学院;201620 上海市 上海工程技术大学机械与汽车工程学院 |
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| 摘 要： | 为了提高汽车的除霜性能,在出风口处增加横格栅,然后选择出风口的长度尺寸和出风角度作为设计变量,使用径向基函数神经网络找到设计变量的最优组合方案。经过优化后,前挡风玻璃上的风速分配更合理,并消灭了除霜死角,在20 min时,前挡风玻璃玻璃的霜层基本完全除净,汽车空调的除霜性能得到明显的提高。
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| 关 键 词： | CFD 除霜分析 数值模拟 优化 径向基神经网络 |
Optimization of Automotive Defrosting Performance Based on Radial Basis Function Neural Network |
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| Liu Tianhong,Fan Pingqing.Optimization of Automotive Defrosting Performance Based on Radial Basis Function Neural Network[J].Agricultural Equipment & Vehicle Engineering,2020,58(5):106-110. |
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| Authors: | Liu Tianhong Fan Pingqing |
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| Institution: | (School of Mechanical and Automotive Engineering,Shanghai University of Engineering Science,Shanghai 201620,China) |
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| Abstract: | In order to improve the defrosting performance of the automobile,the horizontal grilles are added at the outlets.Then the airflow jet angle and the length of the air conditioning outlets are selected as design variables,and the RBFNN(radial basis function neural network) is used to find the optimal combination scheme of design variables.After optimization,the wind speed distribution on the front windshield is more reasonable,and the defrost dead comers are eliminated.The frost layer is completely removed at 20 min,the defrosting performance of the automobile air conditioner is obviously improved. |
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| Keywords: | CFD defrosting performance numerical simulation optimization RBFNN |
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