客车行驶侧翻安全性控制研究
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摘要
客车行驶侧翻安全性控制可以保证车辆在不同道路状况、车辆行驶状态下对车身姿态进行实时控制,保证汽车行驶安全性和稳定性,进行防侧翻控制的关键难点在于影响车辆侧翻的因素较多、较难开展实车实验、实车实验成本较高且受人为因素影响较大。其中车速和瞬时方向盘角度构成影响车辆侧翻的主要因素,因此选取二者作为研究变量,此外选取trucksim中客车作为试验车型,在车速、瞬时方向盘转角均不相同状况下在trucksim中运行,获取不同状况下LTR值,采用BP神经网络算法进行多次预测取平均值,拟合出稳定的三维曲面图,同时通过MATLAB cftool拟合工具箱拟合,量化出LTR与车速和瞬时方向盘转角关系,然后进行二者的预测准确性对比发现,基于BP神经网络预测LTR值具有较高的准确性,可以有效提高了客车行驶安全性。
The safety control of passenger car rollover can ensure the vehicle's real time control of vehicle body attitude in different road conditions and vehicle running state,and ensure the safety and stability of the vehicle.The key difficulty in controlling the rollover prevention is that there are many factors affecting the vehicle rollover,and it is difficult to carry out the actual vehicle experiment because of the higher cost for actual vehicle experiment and influenced by human factors.The speed and the angle of the instantaneous steering wheel were the main factors that affect the rollover of the vehicle.Therefore,the two were selected as the research variables.In addition,the bus in Trucksim was selected as the experimental model,and the speed and instantaneous steering angle of the steering wheel were run on the Trucksim,the LTR value of the different conditions was obtained,and the BP neural network was used.The average value of the algorithm was obtained,and the stable 3D surface map was fitted.At the same time,the relationship between the speed and the instantaneous steering angle was quantified by fitting with MATLAB cftool fitting toolbox,and then the prediction accuracy of the two was compared with the accuracy of the LTR value based on the BP neural network.The safety of passenger cars is improved.
The safety control of passenger car rollover can ensure the vehicle's real time control of vehicle body attitude in different road conditions and vehicle running state,and ensure the safety and stability of the vehicle.The key difficulty in controlling the rollover prevention is that there are many factors affecting the vehicle rollover,and it is difficult to carry out the actual vehicle experiment because of the higher cost for actual vehicle experiment and influenced by human factors.The speed and the angle of the instantaneous steering wheel were the main factors that affect the rollover of the vehicle.Therefore,the two were selected as the research variables.In addition,the bus in Trucksim was selected as the experimental model,and the speed and instantaneous steering angle of the steering wheel were run on the Trucksim,the LTR value of the different conditions was obtained,and the BP neural network was used.The average value of the algorithm was obtained,and the stable 3D surface map was fitted.At the same time,the relationship between the speed and the instantaneous steering angle was quantified by fitting with MATLAB cftool fitting toolbox,and then the prediction accuracy of the two was compared with the accuracy of the LTR value based on the BP neural network.The safety of passenger cars is improved.
引文
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[3]刘军,余节发,穆桂脂,秦国振.基于汽车运动状态在线预报的侧翻预警研究[J].车辆与动力技术,2012,130(2).
[4]唐歌腾,任春晓,李臣.基于Trucksim的不同弯道半径安全车速确定方法[J].公路交通科技,2016,33(6).
[5]张义花,许洪国,刘宏飞.基于Trucksim的双挂汽车列车瞬态侧翻状态[J].吉林大学学报(工学版),2016,46(4).
[6]章雪华,石柏军,李岩.基于Trucksim整车操纵稳定性仿真分析研究[J].机械设计与制造工程,2017,46(2).
[7]岑达希,胡树根,王耘,宋小文.基于L T R的汽车差动制动防侧翻动力学研究[J].机电工程,2011,28(5).
[8]薛俊,胡灿.谭正海.汽车转向侧翻稳定性分析[J].装备制造技术,2013,12(7).
[9]杨波,张文,张晗.汽车侧翻稳定性仿真与分析[J].机械设计,2015,10(10).
[10]黄金燕,葛化敏,唐明军.基于BP神经网络的PID控制方法的研究[J].微计算机信息,2006,22(26).
[11]李世武,田晶晶,沙学锋,孙文财,王琳虹.基于模糊综合评价和BP神经网络的车辆危险状态辨识[J].吉林大学学报(工学版),2012,41(6).
[12]赵会敏,雒江涛,杨军超,徐正,雷晓,罗林.集成BP神经网络预测模型的研究与应用[J].电信科学,2016,60(1).