【作者】 熊辉；

【导师】 邹斌；

【作者基本信息】 武汉理工大学 ， 动力机械及工程， 2018， 硕士

【摘要】 在汽车全面向智能化方向发展的趋势下,智能汽车在行驶过程中保证车身姿态稳定从而为车内乘客提供良好的乘坐舒适性必不可少。因此,本文结合磁流变智能悬架及智能汽车,将智能悬架应用于智能汽车路径跟踪过程中的姿态控制。根据智能汽车行驶工况的不同,提出分模式姿态优化控制方法,优化智能汽车在路径跟踪过程中的姿态变化。具体研究内容如下:首先,建立磁流变减振器模型。分析了磁流变液的基础理论,包括其组成成分、磁流变效应、流变机理以及力学特性。在此基础上,对磁流变减振器的工作模式进行了详细的分析,并对磁流变减振器各动力学模型进行了概述。基于改进Bouc-Wen模型,在Simulink中建立了磁流变减振器仿真模型,仿真结果表明该模型能够较准确地描述磁流变减振器的非线性滞回特性。其次,对磁流变悬架系统及其控制策略进行了研究。在Simulink中建立1/4车辆被动悬架及磁流变悬架的仿真模型。利用滤波白噪声生产法建立了单轮随机路面模型。将包括开关型天棚阻尼控制、LQR最优控制及模糊控制在内的多种控制策略运用于磁流变悬架的控制当中,并搭建了1/4磁流变悬架系统的控制仿真平台。仿真结果表明LQR最优控制与模糊控制的控制效果更佳。最后,针对智能汽车路径跟踪过程中行驶工况的不同,提出了分模式姿态优化控制方法,并建立联合仿真平台对该方法进行仿真验证。将姿态优化控制分为匀速直线行驶状态下的稳定姿态优化控制模式与加减速或转向行驶状态下的突变姿态优化控制模式。结合预瞄-跟随理论与改进型纯追踪控制策略,设计了智能汽车可靠的路径跟踪控制器。针对稳定姿态优化控制模式,基于LQR最优控制及改进IAHP法设计特定有效的控制策略。针对突变姿态优化控制模式,基于智能汽车状态信息及路径跟踪控制器提供的转向信息,分别设计俯仰与侧倾姿态优化模糊控制策略。搭建了基于CarSim/Simulink的联合仿真平台,仿真试验表明分模式姿态优化控制方法对不同工况下智能汽车路径跟踪过程中的车身姿态均有一定的优化效果,为基于半主动悬架的智能汽车车身姿态优化控制提供了一定的参考。更多还原

【Abstract】 Under the trend of the development of automobiles in the direction of full intelligence,it is essential for intelligent vehicle to ensure the stability of the body attitude while driving and thus provide good ride comfort for passengers in the car.Therefore,in this thesis,the intelligent suspension is applied to the attitude control in the path tracking process of the intelligent vehicle in combination with the magnetorheological intelligent suspension and the intelligent vehicle.According to the different driving conditions of the intelligent vehicle,a sub-mode optimal attitude control method is proposed to optimize the attitude change of the intelligent vehicle during the path tracking process.The specific research contents are as follows:Firstly,the magnetorheological damper model was established.The basic theories of magnetorheological fluid were analyzed,including its composition,magnetorheological effect,rheological mechanism and mechanical property.Based on this,the working mode of magnetorheological damper was analyzed in detail,and the dynamic models of magnetorheological damper were summarized.Based on the modified Bouc-Wen model,the magnetorheological damper simulation model was established in Simulink,and the simulation results showed that the model can describe the nonlinear hysteresis characteristics of the magnetorheological damper more accurately.Secondly,the magnetorheological suspension system and its control strategy were studied.The quarter vehicle simulation models of passive suspension and magnetorheological suspension were established in Simulink.A single wheel random road model was established using the filtered white noise production method.A variety of control strategies including on-off skyhook damping control,LQR optimal control and fuzzy control were applied to control the magnetorheological suspension,and a control simulation platform for the 1/4 magnetorheological suspension system was established.The simulation results showed that LQR optimal control and fuzzy control had better control effects.Finally,according to the difference of driving conditions in the path tracking process of intelligent vehicle,a sub-mode optimal attitude control method was proposed,and a co-simulation platform was established to verify the method.The optimal attitude control was divided into a stable-attitude optimal control mode under a uniform straight-line driving state and a mutated-attitude optimal control mode under an acceleration/deceleration or steering driving state.Combined the preview follower theory with the improved pure-pursuit control strategy,a reliable path tracking controller of the intelligent vehicle was designed.For the stable-attitude optimal control mode,a specific effective control strategy was designed based on the LQR optimal control and the improved IAHP method.For the mutated-attitude optimal control mode,based on the status information of the intelligent vehicle and the steering information provided by the path tracking controller,the fuzzy control strategies of pitch and roll attitude optimization were respectively designed.A co-simulation platform was established based on CarSim/Simulink,and the co-simulation simulation experiments showed that under different operating conditions,the sub-mode optimal attitude control method had certain optimization effects on the body attitude of intelligent vehicle during the path tracking process,and it provided a certain reference for the body attitude optimization control of intelligent vehicle based on semi-active suspension.更多还原