EPS路感H∞控制下的频域整形方案研究

电动助力转向(Electric Power Steering,EPS)系统作为一种机械传动机构,受路面扰动和传感器噪声的影响比较大,直接影响到EPS系统的转向路感。将EPS系统模型与线性二自由度整车模型相结合,建立EPS系统控制模型,并给出助力控制的目标函数。根据EPS系统的频率分布,选取两个加权函数。通过转向盘把持力矩的幅频、相频特性及单位阶跃输入响应仿真计算,研究不同加权策略时助力控制对转向路感的影响。仿真结果可知,两个加权函数共同作用可以进一步改善EPS系统转向路感。     

基于干扰抑制的汽车转向与悬架系统的集成控制

建立侧向风作用下的汽车整车横向和垂向非线性动力学模型。考虑到随机路面输入和侧向风干扰,利用L2增益干扰抑制的方法设计出电动助力转向(EPS)与主动悬架系统(ASS)的非线性输出反馈H控制器。在Matlab环境下对驾驶员—汽车—道路闭环系统进行仿真计算。结果表明,所设计的控制器能有效抑制路面随机输入和较大的侧向风干扰,改善车辆的操纵稳定性、转向轻便性和行驶平顺性。     

汽车EPS和AFS衰减路面冲击集成控制

为衰减车辆行驶时受到的路面冲击,建立了人-车-路闭环系统数学模型,设计了电动助力转向(EPS)和主动前轮转向(AFS)集成控制算法,运用阻尼补偿控制和最优控制分别设计了电动助力转向和主动前轮转向子系统。在MATLAB/Simulink中的仿真结果表明,单独主动前轮转向控制不能衰减驾驶员把持力矩振动,单独电动助力转向阻尼控制对转向盘角速度振动和车辆横摆角速度振动衰减效果不佳,而集成系统可以很好地同时抑制驾驶员把持力矩振动、转向盘角速度振动和车辆横摆角速度振动,提高了驾驶舒适性、操纵稳定性和行驶安全性。     

基于模型预测控制的人车路闭环系统建模

为研究驾驶员和车辆在极限工况下的表现,建立了人-车-路闭环系统仿真模型。首先,研究了基于模型预测控制(model predictive control,MPC)的驾驶员模型,利用非线性二自由度车辆预测模型,以使轨迹跟踪误差最小的最优方向盘转角作为驾驶员模型对控制车辆的输入;利用Car Sim车辆动力学仿真软件,对目标车辆进行了参数化建模与实车试验验证。最后,采用双移线工况对建立的人-车-路闭环系统仿真结果进行了验证分析。     

电动助力转向系统双闭环模糊PID控制系统分析

电动助力转向系统(EPS)是机电结合的控制系统,电流PID控制是以目标电流和反馈电流为差值的闭环控制系统,模糊控制是以机械转向轴取差值的机电闭环控制系统,本文以力矩反馈环为外环,电流反馈环为内环,设计了一个双闭环控制系统.将模糊PD控制的输出作为助力目标值,然后进行电流PID控制,快速跟踪目标力矩. 经仿真模拟,双闭环模糊PID控制使电动助力转向系统具有更好的跟踪性和稳定性.     

基于LabVIEW的EPS性能试验台测试系统的研发

采用LabVIEW编程语言,配合研华数据采集卡以及多种传感器,建立电动助力转向性能试验台测试系统。实时采集输入转矩、输出转矩、转向盘转角和助力电流信号;信号通过滤波后存储并显示;实时输出电压信号以控制磁粉制动器模拟多种转向阻力加载形式。利用某型号EPS系统进行试验,结果验证了该测试系统的有效性。     

载货汽车EPS系统粒子群优化模糊控制仿真分析

提出了一种基于粒子群优化模糊控制的载货汽车EPS系统控制策略,在完成载货汽车EPS系统总体设计的基础上,结合驾驶人转向操纵主观感受及对路感的要求设计了助力特性曲线,建立了转向系模型,7自由度整车动力学模型,直流电动机模型,以直流电机电流作为控制目标,采用粒子群优化模糊控制策略,以MATLAB/Simulink作为仿真平台,以自卸货车为研究车型建立了装备EPS系统的载货汽车仿真模型。仿真实验结果表明:与传统模糊控制相比较,粒子群优化模糊控制能够有效地提升载货汽车EPS系统的整体动态响应,并且取得了良好的转向轻便性和操纵稳定性。     

基于功能分配的EPS与ESP集成协调控制

考虑汽车电动助力转向系统(Electric power steering,EPS)与电子稳定程序(Electronic stability program,ESP)系统之间耦合动力学关系,在整车7自由度模型基础上建立高阶非线性动力学模型。分别对两系统设计局部最优控制器,对EPS设计为自回正力矩补偿的模糊自适应比例积分微分(Proportion integration differentiation,PID)控制器,同时引入助力转矩变化率负反馈实现阻尼控制,对ESP设计为变加权值的滑模控制器。为进一步提高整车全局控制性能,基于功能分配原理对两子系统控制输出量进行功能协调分配,采用模糊控制策略对EPS与ESP的功能分配系数进行优化选择。基于Matlab/Simulink软件,对此功能分配协调控制系统进行仿真,并采用硬件在环系统构建功能分配的两系统试验平台,进行道路模拟试验。结果表明,提出的控制策略较子系统单独控制、不加控制时均能够取得更好的效果,明显改善汽车行驶时的操纵安全性和侧向稳定性。     

电动助力转向系统性能优化及参数研究

为研究电动助力转向(EPS)系统的转向特性,首先对转向柱式EPS系统进行了详细的建模。结合一个考虑悬架影响的整车动力学模型,提出了汽车转向性能的指标如转向灵敏度、稳定性和转向路感,并推导出其具体表达式。通过构造和分析转向路感优化模型,研究分析了EPS系统及整车参数对转向性能的影响。最后通过绝对灵敏度的方法,从系统稳定性角度对参数影响进行了分析。     

融合主动转向功能的电动助力转向系统H_∞控制

针对传统电动助力转向(EPS)系统不能在车辆极限工况行驶时实施主动转向,也不能对驾驶员的转向误操作进行主动补偿的问题,建立了融合主动转向功能的EPS整车操纵动力学模型,并以转向轻便性、灵敏性、回正特性及整车操纵稳定性为系统评价输出,运用H∞鲁棒控制策略对基于整车操纵稳定性控制的汽车EPS系统控制特性进行了仿真分析。仿真结果表明,集成主动转向功能的EPS控制系统,既能够实现EPS系统的传统控制特性,又能够根据汽车极限运行工况时整车操纵稳定性的要求实施主动转向,从而有效降低车身横摆角速度和质心侧偏角,并最大程度地发挥EPS的功能调节范围。     

Lane departure avoidance by man-machine cooperative control based on EPS and ESP systems

The ability to avoid lane departure has become an important feature for development of driving assistance technology, and the design of lane departure avoidance system (LDAS) which can achieve cooperative control with human driver is still a challenge. This paper presented a new lane departure decision algorithm along with main parameters of the electric power steering (EPS) and electronic stability program (ESP) system’s sensor. During normal situations, steering control based on EPS system was involved to avoid lane departure. However, when the vehicle reached the handling limits, both steering and braking control collaborated together to avoid lane departure based on EPS and ESP systems. Due to the time varying vehicle speed and the uncertainty of tire cornering stiffness, a gain scheduling brake controller was designed based on the energy-to-peak performance indicator, and an upper monitor was designed for activation the braking controller to ensure comfortable ride. Because the relationship between the lane departure degree with a lateral offset in the single- point preview and the driver torque could not be accurately described, a man-machine cooperative control fuzzy observer for the LDAS was designed. In order to accomplish smooth switching for driving mode to ensure ride comfort, a switching criterion was proposed. The proposed method was evaluated via numerical simulation by CarSim/Simulink. A hardware-in-the-loop test platform was set up, and the effectiveness of the proposed control strategy was compared via the driver-in-the-loop experiment. The obtained results show that the proposed man-machine cooperative control strategy not only can return the vehicle to the normal lane effectively, but also realize smooth switching from man-machine cooperative control to driver control.

     

Integrated control of lateral and vertical vehicle dynamics based on multi-agent system

The existing research of the integrated chassis control mainly focuses on the different evaluation indexes and control strategy. Among the different evaluation indexes, the comprehensive properties are usually not considered based on the non-linear superposition principle. But, the control strategy has some shortages on tyre model with side-slip angle, road adhesion coefficient, vertical load and velocity. In this paper, based on belief, desire and intention（BDI）-agent model framework, the TYRE agent, electric power steering（EPS） agent and active suspension system（ASS） agent are proposed. In the system（SYS） agent, the coordination mechanism is employed to manage interdependences and conflicts among other agents, so as to improve the flexibility, adaptability, and robustness of the global control system. Due to the existence of the simulation demand of dynamic performance, the vehicle multi-body dynamics model is established by SIMPACK. And then the co-simulation analysis is conducted to evaluate the proposed multi-agent system（MAS） controller. The simulation results demonstrate that the MAS has good effect on the performance of EPS and ASS. Meantime, the better road feeling for the driver is provided considering the multiple and complex driving traffic. Finally, the MAS rapid control prototyping is built to conduct the real vehicle test. The test results are consistent to the simulation results, which verifies the correctness of simulation. The proposed research ensures the driving safety, enhances the handling stability, and improves the ride comfort.     

Variable structure controller design for steer-by-wire system of a passenger car

The electric power steering (EPS) system was developed and the steer-by-wire (SBW) system achieves the purposes of EPS. The advantages of SBW are packaging flexibility, advanced vehicle control system, and superior performance. No mechanical linkage exists between the steering gear and steering column in the SBW system. The steering wheel and front-wheel steering can be controlled independently. The SBW system consists of two motors controlled by an electronic control unit (ECU). One motor is in the steering wheel and develops the steering feel of the driver and the other motor is in the steering linkage and improves vehicle maneuverability and stability. Moreover, the active front steering (AFS) system can be added to the SBW system. AFS reduces the difference between actual and estimated vehicle yaw rate. Up-to-date information from the steering wheel enables drivers to identify road conditions through the tire force, which should be fed back to the steering wheel. Furthermore, several control algorithms related to the vehicle and motor can be used together through the self-aligning torque, which is fed back to the steering wheel. This study proposes a method to control the vehicle yaw rate through an SBW system. This control method is based on a PID control method for the steering-wheel-motor controller, as well as on a sliding mode control (SMC) method for the front-wheel-motor controller and yaw stability controller. The SBW system is modeled using a bond graph method. Results imply that the controllers are robust enough when in contact with nonlinear properties of tire and road conditions. This study is expected to guide further research on the SBW system.     

Characterisation of optimal human driver model and stability of a tractor-semitrailer vehicle system with time delay

In this paper, a vehicle/driver close-loop system is studied in order to characterise the inherent model parameters of an optimal human controller for a regulation task (e.g. stabilisation after a wind gust) in articulated vehicle motions. The tractor-semitrailer vehicle model consists of two articulated rigid bodies moving on a horizontal plane with a constant forward speed. The driver establishes his steering control through a time-delayed feedback from current vehicle states with respect to the desired motion. Identification of driver model parameters is achieved through an optimal control approach. The stability of the delayed dynamical system is also studied using a numerical method by computing the eigenvalues near the imaginary axis.     

基于生理特征映射的驾驶员情绪在线识别模型构建方法

高精度驾驶员情绪识别模型是智能车辆安全辅助驾驶系统构建的关键问题之一。针对该问题,提出一种基于生理特征映射的驾驶员情绪在线识别模型构建方法。对不同情绪下驾驶员心电、脉搏生理信号进行时域特征提取,建立生理信号-情绪关联样本库,给出改进式自编码(Improved stacked autoencoder, I-SAE)神经网络架构,构建基于I-SAE神经网络的人员情绪生理表征和离线辨识模型;同步采集行驶过程中不同情绪下驾驶员生理信号和车辆状态数据,利用主成分分析法选取车辆状态特征参数向量,通过I-SAE模型识别处理生理信号数据,将驾驶员情绪的生理表征映射为车辆状态表征,构建车辆状态-驾驶员情绪关联样本库;在此基础上,建立基于学习矢量量化(Learning vector quantization, LVQ)的驾驶员情绪在线识别模型。试验数据表明,该方法构建的驾驶员情绪在线识别模型正确识别率达84%以上,可满足安全距离预警等车辆智能系统需要。     

基于遗传算法的混合动力汽车前向仿真驾驶员模型参数优化

建立了采用PI控制的混合动力汽车前向仿真驾驶员模型,针对传统方法难以整定PI控制器控制参数的问题,提出了基于遗传算法优化PI控制器控制参数的方法,给出了遗传算法的目标函数及其实现过程。仿真结果表明,基于遗传算法优化控制参数的驾驶员模型,能够使得实际车速很好地跟踪循环工况目标车速。     

基于H∞控制的车辆座椅主动悬架系统

建立了四自由度的“车-椅-人”悬架系统的力学和数学模型,运用H∞鲁棒控制理论设计了车辆座椅主动悬架系统的鲁棒控制器。并且用MATLAB软件包及Robust-Control-Toolbox对座椅悬架系统进行了仿真分析。仿真结果表明：鲁棒控制策略能很好地抑制座椅主动悬架系统的垂直振动加速度,其减振幅度在共振频率附近能达到50～60％,大大提高了乘坐舒适性。并且,该系统能够承受一定的模型参数不确定性,具有良好的鲁棒稳定性。     

电传动履带车辆"驾驶员-综合控制器"在环的双侧驱动控制实时仿真

为了在系统设计阶段及早验证控制方案可行性,把"驾驶员-综合控制器"纳入电传动履带车辆双侧驱动控制仿真闭环,建立双侧驱动电传动履带车辆及驱动系统模型.采用真实的驾驶员操纵设备和产品型综合控制器,不同控制策略使用不同CAN通讯协议匹配,被控对象及其外界环境通过数学模型在dSPACE中实时运算来模拟实现,构建包括CAN通讯在内的电传动履带车辆"驾驶员-综合控制器"在环双侧驱动控制实时仿真平台.基于该平台展开以驾驶员操作为输入的硬件在环仿真.仿真结果表明:该平台能进一步验证产品型综合控制器动力学控制算法代码,分析评估不同控制策略下车辆的机动性能.     

车辆驾驶员辅助系统中基于运动模型的前车最优跟随控制

为解决驾驶员辅助系统在前车跟随控制中车距与车速误差不易同步收敛的问题,建立考虑主车对期望加速度动态响应的主车与前车运动模型,以对前车跟随控制提供模型参考。基于主车实际运动与理想前车跟随行驶间的偏差建立前车跟随误差模型,并用线性二次型调节器求解最优期望加速度控制序列,以作为前车跟随控制中主车运动参数控制的输出。为考虑在实车控制中车辆及环境参数发生变化的可能,在前车跟随误差模型中引入车距与车速误差累积项以使线性二次型调节器具有积分控制功能,以在实际车辆与理想模型发生偏差时仍可进行有效控制。仿真对比及实车试验证明,基于运动模型的前车跟随控制可使主车车距与车速误差同步收敛并有效减少主车达到稳态前车跟随行驶的时间,同时易于在实车控制中展开应用。     

用于驾驶机器人的车速跟踪多机械手协调控制方法

提出一种用于驾驶机器人的车速跟踪多机械手协调控制方法。建立了驾驶机器人车速跟踪多机械手/腿控制模型,在此基础上设计了驾驶机器人车速跟踪协调控制器,通过油门/离合器协调控制器实现了车辆的平稳起步和平顺换挡,通过发动机/制动器切换控制器实现了驾驶机器人对给定车速的准确跟踪。实车试验结果表明,提出的方法能合理地协调控制驾驶机器人的油门、制动、离合机械腿和换挡机械手,实现对目标车速的跟踪控制,驾驶机器人完全能够代替试验人员进行各种汽车试验。