四轮独立驱动电动汽车单轮失效稳定性控制

为了解决四轮独立驱动电动汽车驱动系统失效时的转矩分配问题,提出了一种基于规则的驱动力控制分配策略以保证车辆在出现单轮失效情况下的稳定性和动力性.控制器采用双层控制,包括上层控制和下层控制.在上层控制中,根据驾驶员的输入与车辆状态,采用滑模控制理论计算出控制横摆角速度和质心侧偏角的附加横摆力矩.在下层控制中,根据驱动电机...     

Controller design for vehicle stability enhancement

A Vehicle Dynamics Control (VDC) system is developed for tracking desired vehicle behavior. The cascade structure of control system consists of yaw moment major controller and wheel slip minor controller. The Linear Quadratic Regulator (LQR) theory is exploited for yaw moment controller and the sliding mode theory is applied for wheel slip controller design. The use of yaw moment control was investigated by regulating the wheel slip ratio for improving handling and stability of vehicle. The performance of the control system is evaluated under various emergency maneuvers and road conditions through pure computer simulations and Hardware In-the-Loop Simulation (HILS) system. The results indicate the proposed system can significantly improve vehicle stability for active safety.     

基于自适应MPC算法的轨迹跟踪控制研究

为了保证智能车辆在低附着且变速条件下跟踪控制的精确性和稳定性,提出一种基于自适应模型预测控制（MPC）的轨迹跟踪控制算法。针对低附着条件下轨迹跟踪存在行驶稳定性较差的问题,对车辆动力学模型添加侧偏角软约束,分别设计有无添加侧偏角约束的MPC控制器。仿真结果表明,添加侧偏角约束后MPC控制器性能更优,车辆行驶稳定性得到有效提高。在此基础上,又提出了一种自适应的轨迹跟踪控制策略,能够根据车辆速度的变化,实时产生预测时域[(Hp)],分别设计自适应的MPC控制器与4组定值[Hp]的MPC控制器。仿真结果表明,基于自适应模型预测控制的轨迹跟踪控制算法在提高低附着且变速条件下智能车辆轨迹跟踪控制的精度和稳定性方面具有一定的有效性和先进性。     

防抱制动系统滑模状态观测和控制系统仿真

该文在考虑不平路面随机激励作用下车辆垂向振动的基础上 ,首先建立了四分之一车辆制动模型 ,而后充分运用滑移模式变结构的分析和设计方法 ,提出了车轮最佳滑移率的滑模实时在线辨识滑模优化算法 ,在对系统可观测性论证的基础上 ,设计了非线性滑模状态观测器 ,给出了单通道防抱制动系统基于滑移率的滑模控制算法 ,通过计算机仿真 ,验证了该控制算法的可行性和有效性 ,为设计具有高鲁棒性的防抱制动系统做了一定的理论探索和仿真工作     

有源电力滤波器的自抗扰控制研究

针对采用PI控制器控制有源电力滤波器时存在谐波或基波电流指令而无法实现无静差调节,且数字化后会进一步增大稳态误差,使有源电力滤波器的补偿性能降低的问题,提出一种有源电力滤波器的自抗扰控制策略。该策略利用自抗扰控制器的非线性跟踪-微分器和扩张状态观测器分别处理参考输入和输出,并选择适当的状态误差,实现了对滤波的自动、精确补偿。仿真和实验结果表明,有源电力滤波器采用自抗扰控制策略后具有很强的鲁棒性、稳定性和适应性,控制性能有较大改善。     

基于模型预测控制的电动车辆队列控制研究

针对车辆队列建模时参数不确定导致控制存在误差的问题,以及队列中跟随车辆稳定性问题,分析车辆纵向动力学,设计一个鲁棒MPC控制器和滑移率控制器来提高队列车辆的控制精度和稳定性.首先对纵向MPC控制器进行改进,提高车辆队列控制精度；同时为防止跟随车辆的轮胎打滑,设计一个MPC滑移率控制器对跟随车辆的轮胎滑移率进行控制约束,保证了跟随车辆的纵向稳定性.最后,进行仿真实验验证其有效性.仿真实验结果表明,与传统的LQR、MPC控制器相比,改进的鲁棒MPC纵向控制器控制精度更高,同时MPC滑移率控制器可防止跟随车辆的轮胎打滑,保证了跟随车辆的纵向稳定性.     

Disturbance Observer Based Control for Four Wheel Steering Vehicles With Model Reference

This paper presents a disturbance observer based control strategy for four wheel steering systems in order to improve vehicle handling stability. By combination of feedforward control and feedback control, the front and rear wheel steering angles are controlled simultaneously to follow both the desired sideslip angle and the yaw rate of the reference vehicle model. A nonlinear three degree-of-freedom four wheel steering vehicle model containing lateral, yaw and roll motions is built up, which also takes the dynamic effects of crosswind into consideration. The disturbance observer based control method is provided to cope with ignored nonlinear dynamics and to handle exogenous disturbances. Finally, a simulation experiment is carried out, which shows that the proposed four wheel steering vehicle can guarantee handling stability and present strong robustness against external disturbances.      

基于无迹卡尔曼滤波的旋转倒立摆LQR控制

LQR控制器在含有系统噪声与量测噪声的旋转倒立摆系统应用中,难以获得精确的状态向量实现对系统的最优控制.为了提高LQR的控制精度,引入了无迹卡尔曼滤波(UKF)状态观测器,以获得系统的最优状态估计量,实现基于动态规划的自抗扰二次型最优反馈控策略.与卡尔曼滤波(KF)相比,UKF用于非线性系统的状态估计的主要优势是不需要线性化去计算状态转移矩阵,避免了系统线性化带来的模型误差.在含有系统噪声与量测噪声的旋转倒立摆仿真模型下,对基于KF和UKF的LQR控制器进行了仿真对比分析.仿真结果表明,UKF对系统响应时间、控制精度、鲁棒性的优化效果更好.     

Yaw Moment Control Strategy for Four Wheel Side Driven EV

When four wheel side driven EV travals in steering or changes lanes in high speed, the vehicle is easy to side-slip or flick due to the difference of wheel hub motor and a direct effect of vehicle nonlinear factors on vehicle yaw motion, which would affect vehicle handling and stability seriously. To solve this problem, a joint control strategy, combined with the linear programming algorithm and improved sliding mode algorithm, which combines the exponential reaching law and saturation function was proposed. Firstly, the vehicle dynamics model and the reference model according with the structure and driving characteristics of four wheel side driven EV were set up. Then, introduced the basic method of the improved sliding mode variable structure control and complete the sliding mode variable structure controller design basic on vehicle sideslip angle and yaw velocity.The controller accomplish optimal allocation of vehicle braking force through a linear programming algorithm, according to yaw moment produced by the vehicle motion state. Single lane driving simulation results show that the proposed control strategy can not only control vehicle sideslip angle and yaw velocity well, but also accomplish good controlling of the vehicle yaw moment, so as to significantly improve the handling and stability of vehicle.     

汽车操纵稳定性的自适应控制策略研究

针对汽车系统的非线性和参数不确定性,设计了一种“前馈+反馈”自适应神经模糊控制器,通过ESP和AFS的协调控制来提高汽车操纵稳定性.ESP反馈控制器采用模糊控制策略,以横摆角速度和质心侧偏角为控制目标;AFS前馈控制器采用径向基神经网络控制,以反馈控制器的输出作为误差进行学习,从而实现自适应控制.仿真结果表明,上述控制策略是可行和有效的,能显著改善汽车在高速或湿滑路面上的操纵稳定性.     

An intelligent approach to the lateral forces usage in controlling the vehicle yaw rate

A direct yaw moment control system (DYC) is designed to improve the handling and stability of a four‐wheel‐drive electric vehicle. The main task of this paper is to use the lateral forces in the process of optimally controlling vehicle stability. This is performed by defining a variable optimum region for the slip ratio of each wheel. A hierarchical structure is selected to design the control system. The higher‐level control system controls the yaw rate of the vehicle based on the fuzzy logic technique. The lower‐level control system, installed in each wheel, maintains the slip ratio of the same wheel within an optimum region using the fuzzy logic technique. This optimum region for each wheel is continuously modified based on the impact of the lateral force on the generated control yaw moment and the friction coefficient of the road. Therefore, an algorithm for estimation of the friction coefficient is proposed. Computer simulations are carried out to investigate the effectiveness of the proposed method. This is accomplished by comparison of the results of control methods with a fixed slip ratio region and the results of the proposed method with a variable slip ratio region in some maneuvers. The robustness of the proposed controller against hard braking and noise contamination, as well as the effect of steering wheel angle amplitude, is verified. The simulation results show that the influence of the proposed method on enhancing vehicle performance is significant. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

基于高阶滑模速度控制器的异步电机模型预测转矩控制

针对三相异步电机驱动系统,提出一种基于高阶滑模速度控制器的模型预测转矩控制策略.为了降低负载扰动对系统运行性能的影响,设计一种基于二阶Super-Twisting滑模技术的速度环控制器,以代替传统PI速度控制器,并应用Lyapunov稳定性理论对其稳定性和鲁棒性进行分析,得到使速度控制系统收敛的参数范围.为了提升转矩控制精度,基于异步电机的数学模型,采用模型预测转矩控制理论,以转矩和定子磁链为控制目标设计评价函数,得到最优输出电压矢量驱动电机运行.仿真结果表明,所提出的控制方法能有效提升系统对负载扰动的鲁棒性,并有效降低转矩波动,使电机具有良好的动态和静态运行性能.     

Integrated vehicle dynamics management for distributed‐drive electric vehicles with active front steering using adaptive neural approaches against unknown nonlinearity

This paper proposes a new integrated vehicle dynamics management for enhancing the yaw stability and wheel slip regulation of the distributed‐drive electric vehicle with active front steering. To cope with the unknown nonlinear tire dynamics with uncertain disturbances in integrated control problem of vehicle dynamics, a neuro‐adaptive predictive control is therefore proposed for multiobjective coordination of constrained systems with unknown nonlinearity. Unknown nonlinearity with unmodeled dynamics is modeled using a random projection neural network via adaptive machine learning, where a new adaptation law is designed in premise of Lyapunov stability. Given the computational efficiency, a neurodynamic method is extended to solve the constrained programming problem with unknown nonlinearity. To test the performance of the proposed control method, simulations were conducted using a validated vehicle model. Simulation results show that the proposed neuro‐adaptive predictive controller outperforms the classical model predictive controller in tracking nominal wheel slip ratio, desired vehicle yaw rate and sideslip angle, showing its significance in vehicle yaw stability enhancement and wheels slip regulation.     

电动汽车TCS滑模控制器设计

针对电动汽车在冰雪低附着极端工况极易出现的驱动轮过度滑转问题,以电动汽车驱动电机转矩为控制变量,设计了一种电动汽车驱动防滑防牵引力控制系统(Traction control system,TCS)滑模控制器,控制器通过调节驱动电机转矩,将滑转率控制在目标值附近,使汽车持续获得最大路面附着,防止车轮过度滑转,对应用滑模控制出现的抖振问题,设计了一种改进的指数型趋近律,用以削弱系统抖振。仿真结果表明,设计的TCS滑模控制器通过控制驱动电机转矩能将汽车的滑转率控制在目标值附近,使得汽车持续获得最大的路面附着,充分抑制汽车打滑,提高了汽车行驶稳定性,在整个控制过程中驱动电机转矩和状态变量收敛快速且十分平滑,抖振削弱效果良好。     

联合仿真技术在车辆稳定控制程序开发中的应用

该文首先介绍了目前车辆稳定控制程序的研究现状并提出了通过联合仿真进行控制策略开发的新思路，然后详细阐述联合仿真技术的实现原理及方法。接着设计了基于线性二次最优控制理论的直接横摆力矩状态反馈控制策略并引入横摆角速度和质心侧偏角的限值控制以提高车辆在危险工况下的稳定性及可控性。最后通过ADAMS／Car和Matlab／simulink的联合仿真验证了该控制策略的正确性，并为今后复杂机电系统控制策略的开发提供了一条新的途径。     

汽车转向/防抱死制动协同控制

为了解决汽车转向过程中防抱死制动稳定性问题,提出一种新的协同控制系统.该协同控制结构由转向控制器和制动控制器组成.在转向控制中设计滑模鲁棒自适应控制器和横摆力矩控制器力求改善汽车动态响应,鲁棒自适应性和稳定性.此外定义协同误差,建立汽车协同误差模型并设计汽车防抱死制动鲁棒自适应控制系统.为了减少转向系统和制动系统之间的补偿控制律难以确定的困难,提出耦合误差补偿原理与同一给定控制相结合的新的耦合控制策略.最后用仿真结果验证所设计控制算法的有效性.     

横摆力矩和主动前轮转向结合的车辆横向稳定性模糊控制仿真

提出一种基于横摆力矩和主动前轮转向相结合的车辆横向稳定性控制方法,以横摆角速度和侧偏角为控制目标,利用前馈补偿和模糊控制产生横摆力矩和附加的前轮转角,通过控制制动力的分配以及对转向角的修正,使车辆转向行驶时的横摆角速度和侧偏角很好地跟踪参考模型.对转向轮阶跃输入和正弦输入两种工况分别进行了仿真研究,采用横摆力矩和主动前轮转向相结合控制方法,车辆转向时的瞬态及稳态响应优于单独的横摆力矩控制,表明该方法能有效地控制车辆横摆角速度和侧偏角,提高车辆转向时的横向稳定性,同时能有效地减轻驾驶员操纵负担.     

四轮驱动电动汽车稳定性预测控制器快速实现

为解决四轮驱动电动汽车在高速情况下易发生甩尾失控的安全性问题,针对整车和执行器间的动力学耦合、控制系统非线性、多变量、实时性等问题,本文采用集中式的控制策略,设计了一种车辆横摆稳定的快速非线性预测控制器,实现了整车横摆稳定和电机转矩分配的一体化控制.为了控制系统的实时实现,将非线性规划问题转化为代数方程组求解,通过解耦预测时域间方程组的耦合关系,实现时域间优化问题的并行求解,提高了控制器的计算速度.最后给出了控制器的硬件并行加速实验,完成了控制系统的硬件在环实验,实现了车辆横摆稳定系统的实时控制.实验结果表明该控制器不仅具有良好的控制性能,而且明显提升了系统实时性.     

对开路面制动车辆稳定性的控制方法及仿真

汽车在对开路面上紧急制动是汽车制动非常恶劣的一种工况.文中分析了车辆在对开路面上制动的稳定性问题并提出了相应的解决办法,根据简化车辆模型建立了相应状态空间方程,采用最优控制方法解决车辆稳定性问题.结合制动车辆的ABS(防抱制动系统),调整相应车轮的目标滑移率,通过对车辆的横摆力矩控制和相应的车轮滑移率和附着系数的调节使车辆保持制动稳定性,从而可以在不增加硬件成本的条件下完成车辆的稳定性控制.对车辆在对开路面的制动工况进行了仿真,结果表明,所提出的方法能有效改善对开路面上车辆的制动稳定性.     

A novel method for non-linear control of wheel slip in anti-lock braking systems

Anti-lock braking system (ABS) provides active safety for vehicles during braking by regulation of the wheel slip at its optimum value. Due to the non-linear characteristics and model uncertainties in vehicle dynamics, a non-linear controller with increased robustness should be designed for ABS. In this paper, to achieve this aim, an optimization-based braking torque control law is developed for ABS using the prediction of the wheel slip response from a continuous non-linear vehicle dynamics model. To increase the robustness of the controller, the integral feedback technique is appended to the design method. The derived control law and its special cases are evaluated and discussed. At the end, the performance of the proposed controller is compared with that of a sliding mode controller, reported in the literature, through simulations of braking on dry and slippery roads. The simulation results indicate that, the wheel slip tracking error is remarkably decreased by the proposed controller. Moreover, the achieved control input is entirely smooth and suitable for implementation.