PARAMETER OPTIMIZATION OF ELECTRIC POWER STEERING INTEGRATED WITH ACTIVE FRONT STEERING FUNCTION

The dynanaic model of a novel electric power steering（EPS） system integrated with active front steer- ing function and the three-freedom steering model are built. Based on these models, the concepts and the quanti- tative expressions of road feel, sensitivity, and operation stability of the steering are introduced. Then, according to constrained optimization features of multi-variable function, a genetic algorithm is designed. Making the road feel of the steering as optimization objective, and operation stability and sensitivity of the steering as constraints, the system parameters are optimized by the genetic and the coordinate rotation algorithms. Simulation results show that the optimization of the novel EPS system by the genetic algorithm can effectively improve the road feel, thus providing a theoretical basis for the design and optimization of the novel EPS system.

AFS/DYC协调控制下汽车侧风稳定性研究

针对高速汽车在侧风环境下的气动稳定性问题,基于车辆空气动力学与车辆动力学构建了动态双向耦合模型,通过采用相平面法确定主动前轮转向(AFS)和直接横摆力矩控制(DYC)的工作时机,实现汽车AFS和DYC的协调控制,以改善汽车的操纵稳定性。研究结果表明:在侧风的作用下,有、无协调控制的车辆最大侧向位移分别为0.23 m和1.24 m,最大偏航角分别为1.92°和2.89°;最大侧向位移减小了81.5%,最大偏航角减小了33.5%,汽车的侧风稳定性得到明显改善。

Yaw stability control using the fuzzy PID controller for active front steering

In order to improve the yaw stability of the vehicle with active front steering system, an adaptive PID-type fuzzy control scheme is designed to make the yaw rate tracking the desired values as close as possible. A 2-DOF vehicle model with active front steering is built firstly, and then the fuzzy PID controller is designed in detail. The simulation investigations of the yaw stability with different steering ma- neuvers are performed. The simulation results show the effectiveness of the fuzzy PID controller for improving the vehicle＇s yaw stability.

极限工况下AFS与DYC可拓协调控制

主动前轮转向系统(AFS)和直接横摆力矩控制(DYC)集成控制可提高商用货车的操纵稳定性。由于主动前轮转向在轮胎非线性区作用效果有限,与直接横摆力矩控制简单叠加的控制效果不一定能达到预期,为此这里设计了可拓协调控制系统。该系统分为上、中、下三层,上层为AFS与DYC协调切换控制层。采用试验法得到前轮临界转角,根据线性二自由度车辆模型反推临界转角下的稳态质心侧偏角,结合车辆实际质心侧偏角及其速度的相平面稳定域将相平面图分区,设计了3种不同协调控制策略;中层是基于指数趋近律设计的AFS与DYC滑模控制器,可得到前轮附加转角和附加横摆力矩;附加横摆力矩由下层控制器根据车辆实时状态进行制动力分配。采用TruckSim、Matlab/Simulink建立联合仿真平台,在极限工况下进行仿真验证可拓协调控制系统。仿真结果得到最优可拓协调策略,该协调控制弥补了AFS/DYC单一控制的缺陷,可保证车辆的操纵稳定性和行驶安全性。

ACTIVE FRONT STEERING DURING BRAKING PROCESS

An active front steering （AFS） intervention control during braking for vehicle stability is presented. Based on the investigation of AFS mechanism, a simplified model of steering system is established and integrated with vehicle model. Then the AFS control on vehicle handling dynamics during braking is designed. Due to the difficulties associated with the sideslip angle measurement of vehicle, a state observer is designed to provide real time estimation. Thereafter, the controller with the feedback of both sideslip and yaw angle is implemented. To evaluate the system control, the proposed AFS controlled vehicle has been tested in the Hardware-in-the-loop-simulation （HILS） system and compared with that of conventional vehicle. Results show that AFS can improve vehicle lateral stability effectively without reducing the braking performance.

H∞ control of novel active steering integrated with electric power steering function

Based on the traditional active steering system, a novel active steering system integrated with electric power steering function was introduced, which can achieve the functions of both active steering and electric power steering. In view of the interference from road random signal and sensor noise in the novel active steering system, the H∞ control model of the novel active steering system was built. With satisfying steering feel, good robust performance and steering stability being the control objectives, the H∞ controller for the novel active front steering (AFS) system was designed. The simulation results show that the novel AFS system with H∞ control strategy can attenuate the road interference quickly, and there is no resonance peak in the bode diagram. It can make the driver obtain more useful information in the low frequency range, and attenuate the road interference better in the high frequency range, thus the driver can get more satisfying road feeling. Therefore, the designed H∞ controller can synthesize the advantages of both robust performance and robust stability, and has certain contribution to the design of novel AFS system.

Control of Vehicle Active Front Steering Based on Active Disturbance Rejection Feedback Controller

A control method of active front steering(AFS)based on active disturbance rejection technique was proposed for solving the model nonlinearity and parameter decoupling control in the traditional control methods.The AFS controller consists of the proportional and derivative(PD)feed-forward controller and the active disturbance rejection feedback controller.To improve the steering response characteristics of a vehicle,a PD controller is designed to realize variable steering gear ratio,and to enhance the safety of vehicle when steering.An active disturbance rejection controller(ADRC)is designed to follow the expected yaw rate of the vehicle.According to the input and output of system,extended state observer(ESO)of ADRC can dynamically estimate internal and external disturbance of the system,thus easily realizing the model nonlinear and parameter decoupling control.The AFS controller is simulated and validated in Matlab and CarSim.The simulating results of double lane change(DLC)test and pylon course slalom(PCS)test show that the ADRC can well control the vehicle model to complete the road simulation test of DLC and PCS with small path tracking error.The simulating results of angle step test of steering wheel show that the vehicle under the control of ADRC demonstrates good lateral response characteristic.The controller regulates a wide range of parameters.The model has less precision requirements with good robustness.

A Novel Integrated Stability Control Based on Differential Braking and Active Steering for Four-axle Trucks

Di erential braking and active steering have already been integrated to overcome their shortcomings. However, existing research mainly focuses on two-axle vehicles and controllers are mostly designed to use one control method to improve the other. Moreover, many experiments are needed to improve the robustness; therefore, these control methods are underutilized. This paper proposes an integrated control system specially designed for multi-axle vehicles, in which the desired lateral force and yaw moment of vehicles are determined by the sliding mode control algorithm. The output of the sliding mode control is distributed to the suitable wheels based on the abilities and potentials of the two control methods. Moreover, in this method, fewer experiments are needed, and the robustness and simultaneity are both guaranteed. To simplify the optimization system and to improve the computation speed, seven simple optimization subsystems are designed for the determination of control outputs on each wheel. The simulation results show that the proposed controller obviously enhances the stability of multi-axle trucks. The system improves 68% of the safe velocity, and its performance is much better than both di erential braking and active steering. This research proposes an integrated control system that can simultaneously invoke di erential braking and active steering of multi-axle vehicles to fully utilize the abilities and potentials of the two control methods.

Multi-objective optimization of active steering system with force and displacement coupled control

A novel active steering system with force and displacement coupled control(the novel AFS system) was introduced,which has functions of both the active steering and electric power steering.Based on the model of the novel AFS system and the vehicle three-degree of freedom system,the concept and quantitative formulas of the novel AFS system steering performance were proposed.The steering road feel and steering portability were set as the optimizing targets with the steering stability and steering portability as the constraint conditions.According to the features of constrained optimization of multi-variable function,a multi-variable genetic algorithm for the system parameter optimization was designed.The simulation results show that based on parametric optimization of the multi-objective genetic algorithm,the novel AFS system can improve the steering road feel,steering portability and steering stability,thus the optimization method can provide a theoretical basis for the design and optimization of the novel AFS system.

Vehicle Active Steering Control Research Based on Two-DOF Robust Internal Model Control

Because of vehicle＇s external disturbances and model uncertainties,robust control algorithms have obtained popularity in vehicle stability control.The robust control usually gives up performance in order to guarantee the robustness of the control algorithm,therefore an improved robust internal model control（IMC） algorithm blending model tracking and internal model control is put forward for active steering system in order to reach high performance of yaw rate tracking with certain robustness.The proposed algorithm inherits the good model tracking ability of the IMC control and guarantees robustness to model uncertainties.In order to separate the design process of model tracking from the robustness design process,the improved 2 degree of freedom（DOF） robust internal model controller structure is given from the standard Youla parameterization.Simulations of double lane change maneuver and those of crosswind disturbances are conducted for evaluating the robust control algorithm,on the basis of a nonlinear vehicle simulation model with a magic tyre model.Results show that the established 2-DOF robust IMC method has better model tracking ability and a guaranteed level of robustness and robust performance,which can enhance the vehicle stability and handling,regardless of variations of the vehicle model parameters and the external crosswind interferences.Contradiction between performance and robustness of active steering control algorithm is solved and higher control performance with certain robustness to model uncertainties is obtained.

Generalized Internal Model Robust Control for Active Front Steering Intervention

Because of the tire nonlinearity and vehicle＇s parameters＇uncertainties,robust control methods based on the worst cases,such as H_∞,μsynthesis,have been widely used in active front steering control,however,in order to guarantee the stability of active front steering system（AFS）controller,the robust control is at the cost of performance so that the robust controller is a little conservative and has low performance for AFS control.In this paper,a generalized internal model robust control（GIMC）that can overcome the contradiction between performance and stability is used in the AFS control.In GIMC,the Youla parameterization is used in an improved way.And GIMC controller includes two sections：a high performance controller designed for the nominal vehicle model and a robust controller compensating the vehicle parameters＇uncertainties and some external disturbances.Simulations of double lane change（DLC）maneuver and that of braking on split-μroad are conducted to compare the performance and stability of the GIMC control,the nominal performance PID controller and the H_∞controller.Simulation results show that the high nominal performance PID controller will be unstable under some extreme situations because of large vehicle＇s parameters variations,H_∞controller is conservative so that the performance is a little low,and only the GIMC controller overcomes the contradiction between performance and robustness,which can both ensure the stability of the AFS controller and guarantee the high performance of the AFS controller.Therefore,the GIMC method proposed for AFS can overcome some disadvantages of control methods used by current AFS system,that is,can solve the instability of PID or LQP control methods and the low performance of the standard H_∞controller.

AFS与DYC协调控制的智能汽车路径跟踪方法

为提高智能车辆在复杂道路条件下的路径跟踪能力与行驶稳定性,提出了一种基于AFS(主动前轮转向)与DYC(直接横摆力矩控制)协调控制的智能汽车路径跟踪控制方法。为保证车辆在复杂道路条件下的路径跟踪精度,在车辆2自由度模型及单点预瞄模型的基础上,控制预瞄时间使其自适应跟踪目标路径;在DYC设计时,考虑到横摆角速度和质心侧偏角量纲不同,采用无量纲方法设计横摆力矩滑模控制器,并采用单轮制动的方式实现附加横摆力矩的分配;同时,为了使AFS和DYC的工作效果得到充分发挥,基于车辆失稳侧滑时的前轮临界转角,采用加权分配函数的方式保证协调控制的平顺性。基于Carsim-Simulink联合进行鱼钩工况及双移线工况下的试验仿真,并与独立控制对比。试验结果表明:协调控制在满足对复杂道路条件跟踪准确性的同时可有效改善智能车辆行驶时的操纵稳定性,具有更好的鲁棒性。

AFS四轮线控驱动转向稳定性控制技术

提出基于AFS的四轮线控驱动转向稳定性控制技术,提高四轮线控驱动车辆的稳定性。信号调理层通过建立线性二自由度期望模型得出四轮线控驱动车辆转向的横摆角速度与质心侧偏角的理想值;集成控制层以二者与实际值的偏差判断四轮线控驱动车辆的稳定状态,利用滑模控制(SMC)实现主动前轮转角(AFS)的控制,维持四轮线控驱动的稳定性,同时利用模型预测控制(MPC)实现横摆力矩(DYC)控制,控制分配层通过驱动力分配器将集成控制层获取的横摆力矩分配给各车轮;执行层以此为基础结合集成控制层得出前轮附加转角值,驱动车辆稳定运行。实验表明:该方法可以降低四轮线控车辆的滑移率;将驱动力经由分配器分配给各车轮,以保证驱动车辆稳定运行;当四轮线控驱动车辆以低速或高速行驶时,均可有效控制四轮线控车辆的稳定性。

三轴重载货车AFS与DYC集成控制研究

针对三轴重载货车的工作环境恶劣、工况复杂以及车辆结构的原因,容易发生横向失稳等问题。提出基于自适应MPC模型预测控制理论建立了前轮主动转向(AFS)与直接横摆力矩控制(DYC)集成控制策略。该策略采用分层控制结构,在二自由度线性变参数时变(LPV)车辆模型基础上设计了LPV/MPC上层控制器,基于垂直载荷的轮胎力分配设计了下层横摆力矩分配的控制器,利用Simulink-Trucksim进行联合仿真验证。研究表明:在匀速的双移线工况下,基于自适应MPC的集成控制方法比MPC模型预测控制方法的横摆角速度,质心侧偏角以及侧向加速度等均方面降低了3%~5%左右,保证了三轴重载汽车的行驶稳定性;在变速的工况下,MPC模型预测控制方法不能适应车辆速度的变化,控制效果微弱。而提出的自适应MPC模型预测控制方法不仅在车速方面具有很好的鲁棒性,并且提高了车辆的操纵稳定性。

Improving rail vehicle dynamic performance with active suspension

Today,it is difficult to further improve the dynamic performance of rail vehicles with conventional passive suspension.Also,simplified vehicle respectively running gear layouts that significantly could reduce vehicle weights are difficult to realize with modern requirements on passenger vibration comfort and wheel and rail wear.Active suspension is a powerful technology that can improve the vehicle dynamic performance and make simplified vehicle concepts possible.The KTH Railway group has,together with external partners,investigated active suspensions both numerically and experimentally for 15 years.The paper provides a summary of the activities and the most important findings.One major project carried out in close collaboration with the vehicle manufacturer Bombardier and the Swedish Transport Administration was the Green Train project,where a 2-car EMU test bench was used to demonstrate different active technologies.In ongoing projects,a concept of single axle-single suspension running gear is developed with active suspension both for comfort improvement and reduced wheel wear in curves.The results from on-track tests in the Green Train project were so good that the technology is now implemented in commercial trains and the simulation results for the single-axle running gear are very promising.

基于主动横向稳定杆和AFS的车辆稳定性协调控制

根据车辆的基本动力学特性,分析了轮胎非线性对于车辆横摆稳定性的影响,建立了包括主动横向稳定杆与AFS的整车动力学模型。根据主动横向稳定杆和AFS两个系统的运动耦合关系,分别设计了主动横向稳定杆与AFS的各个子控制器,并设计了前后主动防侧倾力矩分配模糊PID控制器,实现两个子系统的协调控制,提高了车辆转向时的侧倾与横摆稳定性。在MATLAB/Simulink环境中,对车辆在转向工况下进行了仿真研究,利用Carsim软件对仿真结果进行了验证,结果证明了两者协调控制策略的有效性。

基于UKF车辆状态及路面附着系数估计的AFS控制

本文侧重于主动前轮转向(Active Front Steering,AFS)控制系统的应用性与可行性研究,针对紧急转向工况下轮胎呈现强非线性问题,以及AFS控制算法中部分状态量难以获取、路面附着系数对车辆稳定性有重要影响但难以直接测量等问题,设计非线性滑模控制器以综合考虑载荷转移、轮胎非线性及路面条件等对操稳性影响,同时,通过ESP系统现有的IMU传感器测量信息,运用无迹卡尔曼滤波(Unscented Kalman Filter,UKF)算法为滑模控制器动态估计车辆状态信息和路面附着系数.在得到期望轮胎侧偏力后,通过非线性轮胎模型精确反求所需叠加转角,以在“轮胎-路面”附着能力范围内检验控制系统的有效性.最后,高附着系数情况下的鱼钩测试仿真及低附着系数时的角阶跃转向仿真共同表明,通过IMU与UKF结合的状态估计确保了AFS控制系统的可行性,有效提高了车辆操纵稳定性.

基于车辆状态识别的AFS与ESP协调控制研究

给出了基于滑模变结构的AFS控制策略和直接横摆力矩加变滑移率联合控制的ESP控制策略。在分析两者控制性能的基础上提出了协调控制的一般原则。阐述了车辆状态识别算法并给出了具体的协调控制策略,最后通过3个典型工况的仿真计算验证了该协调控制策略的有效性。

基于路面附着系数估计的AFS控制策略研究

考虑路面附着条件对车辆横摆响应的影响,设计了路面附着系数修正的主动转向控制策略.为了迅速准确地获取当前路面附着信息,采用了无迹卡尔曼滤波观测器观测路面附着系数,并用Carsim-Simulink联合仿真验证了此方法的有效性.在传统主动转向控制的基础上将路面附着系数作为输入,设计了滑模控制器.通过Simulink仿真,验证了所设计的滑模控制器在低附着路面、对接路面均能提高车辆的操纵稳定性和理想轨迹跟踪能力.

AFS前照灯弯道旋转的计算模型

提出当车辆在弯道转向时,可以通过车速和前轮转向角度作为输入信号,根据前照灯弯道照明距离应大于安全行驶距离的控制策略,以四轮动态转向模型和ABS制动模型为基础,计算前照灯的旋转角度。经由基于MATLAB/Simulink的数值计算程序和专门设计的采用向心加速度传感器的LabVIEW实车测控系统,对比验证了AFS前照灯弯道旋转计算模型的有效性。