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矿用宽体车主动油气悬架的复合控制方法研究
引用本文:石运序,刘同昊,岳宗曙,曹成市,窦彬,赵浩涵,杨家辉. 矿用宽体车主动油气悬架的复合控制方法研究[J]. 机床与液压, 2023, 51(3): 173-179
作者姓名:石运序  刘同昊  岳宗曙  曹成市  窦彬  赵浩涵  杨家辉
作者单位:烟台大学机电汽车工程学院
基金项目:烟台市科技计划项目(2021XDHZ073);山东省研究生教育联合培养基地立项建设项目(SDYJD18039);烟台市科技计划项目(2019ZDCX009)
摘    要:由于矿用宽体车被动油气悬架不能根据路面情况以及车载变化达到实时调整车姿来满足车辆平顺性要求,为进一步改善矿车行驶平顺性,提出一种神经网络和模糊PID控制相结合的主动悬架复合控制方法。建立单气室油气弹簧数学模型,并经实验验证了模型的正确性;在此基础上以C级路面作为输入,建立1/2车辆动力学模型,以悬架输出力为控制对象,对控制器的设计进行了详细研究,并对矿车前半车身垂向及侧倾方向的振动特性进行了对比分析。结果表明:与被动悬架相比,所设计的主动控制策略使车身垂直加速度降低了38.45%,侧倾角加速度降低了27.16%,轮胎动载荷降低了32.68%,悬架动扰度降低了34.8%,极大地改善了车辆行驶平顺性。

关 键 词:油气悬架  神经网络  模糊PID控制  AMESim&MATLAB联合仿真  平顺性

Study on Compound Control Method of Active Hydro-pneumatic Suspension of Mining Wide-body Vehicle
SHI Yunxu,LIU Tonghao,YUE Zongshu,CAO Chengshi,DOU Bin,ZHAO Haohan,YANG Jiahui. Study on Compound Control Method of Active Hydro-pneumatic Suspension of Mining Wide-body Vehicle[J]. Machine Tool & Hydraulics, 2023, 51(3): 173-179
Authors:SHI Yunxu  LIU Tonghao  YUE Zongshu  CAO Chengshi  DOU Bin  ZHAO Haohan  YANG Jiahui
Abstract:Due to mining wide-body car passive hydro-pneumatic suspension can not change according to the road conditions and vehicle load variety real-time to meet the requirements of vehicle ride comfort,in order to further improve the ride comfort,a compound control method based on neural network and fuzzy PID control was proposed for active hydro-pneumatic suspension.The single chamber hydro-pneumatic spring mathematical model was established.The correctness of the model was verified by experiments.On this basis,the 1/2 vehicle dynamics model was established with the C-class road surface as the input,and the design of the controller was studied in detail with the output force of the suspension as the control object,and the vertical and lateral vibration characteristics of the front half body of the mine car were compared and analyzed.The results show that:compared with the passive suspension,the vehicle vertical acceleration,roll angle acceleration,tire dynamic load and suspension dynamic disturbance are reduced by 38.45%,27.16%,32.68% and 34.8% respectively,which greatly improve the vehicle ride comfort.
Keywords:Hydro-pneumatic suspension  Neural network  Fuzzy-PID control  AMESim & MATLAB co-simulation  Comfort
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