A neural network fuel consumption model hybrid of EVT system

doi:10.11835/j.issn.1000-582X.2019.07.001

Home > Archive>Volume 42, Issue 7, 2019 >1-9. DOI:10.11835/j.issn.1000-582X.2019.07.001

A neural network fuel consumption model hybrid of EVT system
DOI:
                        10.11835/j.issn.1000-582X.2019.07.001
                    
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                        YANG YalianYANG Yalian
School of Automotive Engineering, Chongqing University, Chongqing 400044, P. R. China;State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044, P. R. China
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DENG QiyuanDENG Qiyuan
School of Automotive Engineering, Chongqing University, Chongqing 400044, P. R. China
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LIU QiangshouLIU Qiangshou
School of Automotive Engineering, Chongqing University, Chongqing 400044, P. R. China
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PEI HuanxinPEI Huanxin
School of Automotive Engineering, Chongqing University, Chongqing 400044, P. R. China
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Clc Number:U462.3
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Abstract:

In order to quickly screen the hybrid electric vehicle powertrain (EVT, electric variable transmission) configurations based on their fuel economy, a configuration matrix of hybrid EVT system is proposed and the dynamic model of hybrid EVT system is established on the basis of graph theory hierarchical drawing model of hybrid EVT system. A fuel consumption model of hybrid EVT system that combines general regression neural network and dynamic programming algorithm is established and its effectiveness is verified by comparing the calculation results of GRNN fuel consumption model and that of the DP simulation of the test configurations.

Key words:hybrid EVT system;graph theory hierarchical drawing;configuration matrix;dynamic analysis;dynamic programming;neural network model

Reference

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杨亚联,邓淇元,刘强寿,裴换鑫.混合动力耦合系统神经网络油耗模型构建[J].重庆大学学报,2019,42(7):1~9

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Received:February 23,2019
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Online: July 27,2019
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