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Hybrid Loader Automatic Shift Strategy Based on Neural Network
  • ISSN号:1000-8152
  • 期刊名称:《控制理论与应用》
  • 时间:0
  • 分类:U462.3[机械工程—车辆工程;交通运输工程—载运工具运用工程;交通运输工程—道路与铁道工程]
  • 作者机构:[1]School of Energy and Power Engineering, Shandong University, Jinan 250061, China, [2]Jianghuai Automobile Co., Ltd., Hefei 230000, China
  • 相关基金:The Youth Foundaticn Projects of the National Natural Science Foundation of China ( No. 61403236)
中文摘要:

Hybrid loader ’s comprehensive performance mainly depends on the performance of hydraulic torque converter during its driving and working. Hybrid loader and hydraulic torque converter are taken for the research objects. The primary characteristic curve of hydraulic torque converter and the traction curve of hybrid loader are acquired by analyzing the characteristic parameters of hydraulic torque converter, the characteristic parameters of engine, the characteristic parameters of battery pack and geometric parameters of hybrid loader. The gear shift curves based on the best energy saving performance and the best power performance are acquired respectively with the opening of throttle,the speed of pump wheel and the speed of turbine as parameters. Then the two curves are combined to get the comprehensive gear shift curve. Radical basis function( RBF) neural network is applied to building the gear shift strategy to keep hybrid loader with the best power performance and energy saving performance. The experimental bench is set up for experimental verification. It proves that both of the power performance and energy saving performance of hybrid loader are improved effectively by using the automatic shift strategy.

英文摘要:

Hybrid loader 's comprehensive performance mainly depends on the performance of hydraulic torque converter during its driving and working. Hybrid loader and hydraulic torque converter are taken for the research objects. The primary characteristic curve of hydraulic torque converter and the traction curve of hybrid loader are acquired by analyzing the characteristic parameters of hydraulic torque converter, the characteristic parameters of engine, the characteristic parameters of battery pack and geometric parameters of hybrid loader. The gear shift curves based on the best energy saving performance and the best power performance are acquired respectively with the opening of throttle,the speed of pump wheel and the speed of turbine as parameters. Then the two curves are combined to get the comprehensive gear shift curve. Radical basis function( RBF) neural network is applied to building the gear shift strategy to keep hybrid loader with the best power performance and energy saving performance. The experimental bench is set up for experimental verification. It proves that both of the power performance and energy saving performance of hybrid loader are improved effectively by using the automatic shift strategy.

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期刊信息
  • 《控制理论与应用》
  • 北大核心期刊(2011版)
  • 主管单位:国家教育部
  • 主办单位:华南理工大学 中国科学院数学与系统科学研究院
  • 主编:胡跃明
  • 地址:广州五山路华南理工大学3号楼516室
  • 邮编:510640
  • 邮箱:aukzllyy@scut.edu.cn
  • 电话:020-87111464
  • 国际标准刊号:ISSN:1000-8152
  • 国内统一刊号:ISSN:44-1240/TP
  • 邮发代号:46-11
  • 获奖情况:
  • 国内外数据库收录:
  • 美国化学文摘(网络版),美国数学评论(网络版),德国数学文摘,荷兰文摘与引文数据库,美国工程索引,美国剑桥科学文摘,英国科学文摘数据库,日本日本科学技术振兴机构数据库,中国中国科技核心期刊,中国北大核心期刊(2004版),中国北大核心期刊(2008版),中国北大核心期刊(2011版),中国北大核心期刊(2014版),中国北大核心期刊(2000版)
  • 被引量:21084