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     

基于模糊控制的分布式电动车辆横摆力矩研究

为提高多轮分布式电驱动车辆在不同工况下的操纵稳定性,设计了一种基于直接横摆力矩控制的分层控制策略。上层以横摆角速度和质心侧偏角为控制变量,采用模糊控制进行目标运动状态跟踪,决策出所需要的横摆力矩。下层按设计的规则进行转矩分配。应用TruckSim和Matlab/Simulink建立车辆和控制器模型,分别在高、低附着等工况下进行联合仿真。仿真结果表明,设计的模糊控制方法能对车辆目标状态进行良好跟踪,相较于无控制状态能够提高车辆的操纵稳定性。     

车辆直接横摆力矩的预测控制研究

针对车辆高速过弯时发生的侧滑问题,将预测控制运用于汽车ESP控制系统中,以2自由度车辆模型为预测内部模型,以车辆直接横摆力矩为输出作用于车轮来控制整车的行驶状态。结合Matlab/Simulink建立的七自由度整车模型以及轮胎模型对所设计的ESP控制器进行分析调整。实验结果表明,预测控制器能很好地控制汽车的横摆角速度和限制质心侧偏角,提高了汽车的稳定性和安全性。     

An MPC-based manoeuvre stability controller for full drive-by-wire vehicles

Aiming at the actuator time delay caused by the drive-by-wire technology, a novel manoeuvre stability controller based on model predictive control is proposed for full drive-by-wire vehicles. Firstly, the future vehicle dynamics are predicted by a two-degree-of-freedom vehicle model with input delay. Secondly, in order to prevent the vehicle from destabilizing due to excessive side slip angles, the determined ideal yaw rate and side slip angle are tracked simultaneously by optimizing the front wheel angle and additional yaw moment. Moreover, in order to improve the trajectory tracking ability, a side slip angle constraint determined by phase plane stability boundaries is added to the cost function. The results of Matlab and veDYNA co-simulation show that the regulated yaw rate can track the reference value well and the side slip angle decreases. Meanwhile, the trajectory tracking ability is improved obviously by compensating the time delay.     

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.     

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,根据驱动电机失效程度,考虑各约束条件,将计算出的附加横摆力矩合理地分配给各个驱动轮。利用Carsim和MATLAB/Simulink的联合仿真,选择直线、转弯以及Sine wave等工况对提出的转矩分配控制策略进行仿真分析,仿真结果表明所提控制策略能够在提高驱动系统利用率和消除前轮左右输出转矩不同对方向影响的基础上保证车辆的稳定性。     

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.     

后轴双电机扭矩矢量控制研究

车辆的横摆响应受到转向系统、悬架系统、制动系统及驱动系统影响,传统车辆主要以转向输入进行主动控制,随着线控底盘的发展,ESC、后轮转向、扭矩矢量等技术逐步参与到车辆横摆的主动控制中;相对于ESC以制动力差产生横摆力矩,扭矩矢量可在不降低总驱动力的前提下产生横摆力矩,不会引起车辆的制动效应;通过后轴双电机扭矩矢量控制（TVC）产生主动横摆力矩,旨在改善车辆横摆响应,TVC采用前馈与反馈结合控制,基于二自由度车辆模型、目标稳态增益K及横摆角速度-速度修正因子K1建立目标横摆角速度;利用车辆模型逆函数计算横摆力矩前馈值,PID计算横摆力矩反馈值,总横摆力矩转换得到左右车轮纵向力调整量;纵向力调整量与驱动力分量叠加获得左右轮总纵向力;左右轮驱动力过大时可能会受到滑移率、电机扭矩等限制,为保证横摆力矩偏差在要求范围内,需要根据限制情况对左右轮纵向力进行调整;通过仿真验证,TVC可明显改变车辆横摆响应     

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.     

Studies on improving vehicle handling and lane keeping performance of closed-loop driver–vehicle system with integrated chassis control

This study proposes a new integrated robust model matching chassis controller to improve vehicle handling performance and lane keep ability. The design framework of the H_∞ controller is based on linear matrix inequalities (LMIs), which integrates active rear wheel steering control, longitudinal force compensation and active yaw moment control. To comprehensively evaluate the performance of the integrated chassis control system, a closed-loop driver–vehicle system is used. The effectiveness of the integrated controller on handling performance improvement is tested by a vehicle without driver model under a crosswind disturbance. At the same time, both the handling and lane keeping improving performance of the closed-loop driver–vehicle system is evaluated by tracking an S shape winding road. The simulation results reveal that the integrated chassis controller not only achieves preferable handling performance and stability, but also improves the vehicle lane keep ability significantly, and can alleviate the working load of the driver.     

一种基于前馈－反馈复合控制方式的制动稳定性控制方法

设计了一种前馈—反馈复合控制结构，将直接横摆力矩控制和主动前轮转向控制相结合以提高制动稳定性．控制器将前轮转向角视为输入，将外部侧向干扰力和力矩作用视为扰动，通过前馈校正补偿转向角引起的状态变化；同时建立扰动状态观测器，采用反馈控制校正消除外部扰动引起的状态误差．仿真试验证实这种控制方法在提高制动稳定性方面有良好的效果．     

提高车辆安全性的输出反馈自适应控制

研究含有时变参数的车辆动力学模型的输出跟踪控制问题.控制目标是使车辆的横摆角速度和质心侧偏角分别跟踪理想的设定值,通过反推方法设计输出反馈自适应控制器.控制器的输出为主动横摆力矩,通过控制主动横摆力矩来控制车辆的输出响应跟踪理想的输出信号,从而提高车辆的安全性.仿真结果表明,该控制器能更好地适应车速和路况的变化,鲁棒性强.     

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.     

Integrated stability control of AFS and DYC for electric vehicle based on non-smooth control

A controller which ensures the driving stability of a four-wheel-independent-drive electric vehicle (4WID-EV) is designed in this paper. The controller is structurally hierarchically designed. In order to keep the 4WID-EV running steadily, an upper-level controller integrating the active front-wheel steering control method (AFS) and direct yaw moment control method (DYC) is designed to keep the sideslip angle and yaw rate tracking the ideal values. A non-smooth control method is used to improve the closed-loop system's convergence and anti-disturbance performance. The additional yaw moment generated by the upper-level controller is distributed to four driving wheels by the lower-level controller. An optimal control algorithm is used in the lower-level controller to achieve the minimum sum of tire utilisation, and ensure the power performance and driving stability of the 4WID-EV. In order to verify the effectiveness of the designed controller, a simulation model of the stability control system is established based on Carsim-Matlab/Simulink. And the simulation is performed under double lane change road considering the disturbances. The results of the simulation show that the 4WID-EV with the designed controller achieves smaller sideslip angle than sliding-mode control and the actuator chatter is slight. Then the stability and safety of the 4WID-EV are greatly improved.     

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。     

MPC-based compensation control system for the yaw stability of distributed drive electric vehicle

Conventional yaw stability strategy of distributed drive electric vehicle (DDEV) is usually realised by torque distribution strategy. However, the instantaneous variations of four independent tyres slip ratio and the effect of disturbance have not been considered sufficiently. Therefore, it is difficult to realise the robustness of yaw stability for DDEV under various operating conditions. To solve this problem, a novel model predictive controller-based compensation control system (MPC-CCS) is proposed in this paper. The proposed MPC-CCS consists of two parts, an MPC based-feedback controller and a Kalman filter based-feedforward controller. In the feedback controller, a dual torque distribution scheme is adopted to obtain optimal torque values derived from the real-time signals of four independent tyres slip ratio, an MPC is designed to realise optimal torque values for vehicle yaw motion. In the feedforward controller, a Kalman filter is employed to attenuate the effect of the disturbance on yaw performance. In this way, the robustness of yaw stability for DDEV can be guaranteed by the proposed MPC-CCS. The proposed MPC-CCS is evaluated on eight degrees of freedom simulation platform and simulation results of different conditions show the effectiveness of the MPC-CCS.     

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。     

A novel integrated control framework of AFS,ASS, and DYC based on ideal roll angle to improve vehicle stability

The current research on vehicle stability control mainly focuses on following the ideal yaw rate and sideslip angle, without considering the potential of ideal roll angle in improving the vehicle stability. In addition, the mutation of tire-road friction coefficient promotes a great challenge to the stability control. To improve the vehicle stability, in this study, firstly, the three-dimensional stability region of “lateral speed-yaw rate-roll angle” was studied, and a method to determine the ideal roll angle was proposed. Secondly, a novel integrated control framework of AFS, ASS, and DYC based on ideal roll angle was proposed to actively control the front tire slip angles, suspension forces, and motor torques: In the upper-level controller, model predictive control and tire force distribution algorithm were used to obtain the optimal four-tire longitudinal forces, front tire lateral forces and additional roll moment under constraints; In the lower-level controller, the upper virtual target was realized by the optimal allocation algorithm of actuators and the tire slip controller. Finally, the proposed control framework was verified on the varied-µ road. The results indicated that compared with the two existing control strategies, the proposed framework can significantly improve the vehicle following performance and stability.     

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.     

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.