基于最佳制动效果的并联式混合动力汽车再生制动控制策略

在遵循制动力分配原则的基础上,提出了基于最佳制动效果和模糊控制的再生制动控制策略,使机械制动和再生制动可以很好地协同工作,实现前后轮制动力合理分配。设计了以制动强度和蓄电池荷电状态为输入变量,以期望再生制动力为输出变量的模糊控制器。利用仿真软件ADVISOR,对所设计的控制策略进行了部件性能、制动能量回收、制动感觉三方面仿真分析。同时,为验证ADVISOR仿真结果的有效性,搭建了硬件在环仿真实验平台。结果表明,所设计的控制策略在保证汽车制动稳定性的前提下,能够使驾驶员获得满意的制动感觉,同时有效提高了汽车能量利用率,最终达到了最佳制动效果。     

事件触发的自适应移动机器人轨迹跟踪控制

针对纵向滑转对移动机器人轨迹跟踪控制的影响,提出了一种基于事件触发的自适应轨迹跟踪控制方法。引入自适应估计策略,通过两个滑转参数自适应估计驱动轮的纵向滑转情况,克服纵向滑转带来的运动扰动。同时结合事件触发思想,设计触发函数,降低通信频次,节约计算资源。最后,利用Lyapunov稳定性理论对系统的稳定性进行证明。仿真及实验结果表明,在纵向滑转使得位置误差最大值的均方根提升56.85%的情况下,控制系统仍能在短时间内迅速收敛,提高了运动系统的稳定性。     

Design,implementation, and test of skid steering-based autonomous driving controller for a robotic vehicle with articulated suspension

This paper describes an autonomous driving control algorithm based on skid steering for a Robotic Vehicle with Articulated Suspension (RVAS). The driving control algorithm consisted of four parts: speed controller for following the desired speed, trajectory tracking controller to track the desired trajectory, longitudinal tire force distribution algorithm which determines the optimal desired longitudinal tire force and wheel torque controller which determines the wheel torque command at each wheel to keep the slip ratio below the limit value as well as to track the desired tire force. The longitudinal and vertical tire force estimators were designed for optimal tire force distribution and wheel slip control. The dynamic model of the RVAS is validated using vehicle test data. Simulation and vehicle tests were conducted in order to evaluate the proposed driving control algorithm. Based on the simulation and test results, the proposed driving controller was shown to produces satisfactory trajectory tracking performance.     

科氏质量流量计振动幅值的仿人智能控制方法

测量管振动的稳定性、可靠性是科氏质量流量计实现精确计量的基础。针对科氏质量流量计振动幅值控制问题,设计了一种仿人智能控制方法,将科氏质量流量计测量管振动分为起振稳幅和干扰抑制两个阶段,根据幅值偏差及偏差变化率分别划分出5种和3种不同的特征状态,构建特征状态集;对于不同的特征状态,分别设计相应控制模态,构建控制模态集,同时设计启发式搜索和直觉推理规则集。控制过程中,先根据偏差及偏差变化率辨识出当前振动状态,依据推理规则集选择相应的控制模态进行振动控制。实验结果表明,所提方法可以实现科氏质量流量计快速起振,且振幅稳定,验证了方法优越性和工程实用性。     

四轮轮毂电机驱动电动汽车纵侧向稳定性协调控制策略研究

结合四轮轮毂电机驱动电动汽车四轮转矩独立可控的特点,针对加速同时转向时地面附着力不足的情况,研究车辆纵向和侧向稳定性协调控制策略。针对未知和复杂多变的路面附着情况,设计对路面附着变化具有良好鲁棒性的滑转率自寻优驱动防滑控制策略,采用滑模控制方法实现了对路面最优滑转率的自适应追踪。在此基础上,构建稳定性协调控制策略,通过对车辆纵、侧向动力学目标进行优先级判断和多目标协调控制,有效提升了车辆纵向和侧向稳定性。通过CarSim-Simulink联合仿真验证了驱动防滑控制策略在未知路面附着情况下的有效性,提出的纵侧向稳定性协调控制策略能够有效提升车辆的纵向和侧向稳定性,控制效果优于直接横摆力矩控制。     

车辆动力学稳定性系统变结构滑模控制研究

探讨了转弯车辆行驶在极限运动工况下时，依靠施加各车轮不同纵向制动力从而产生辅助横摆力矩来提高车辆动力学稳定性的基本原理，推导了两自由度车辆横向动力学方程，提出了车辆侧滑速度的3种实时估计方案（积分法，代数法和Luenberger观察器法），视实际车辆前后轮胎侧偏刚度为有界不确定性参数，为跟踪线性两自由度理想车辆模型的稳态输出响应，设计了车辆动力学稳定性变结构控制策略，通过仿真验证了该方案可行性。     

Direct yaw moment control for distributed drive electric vehicle handling performance improvement

For a distributed drive electric vehicle (DDEV) driven by four in-wheel motors, advanced vehicle dynamic control methods can be realized easily because motors can be controlled independently, quickly and precisely. And direct yaw-moment control (DYC) has been widely studied and applied to vehicle stability control. Good vehicle handling performance: quick yaw rate transient response, small overshoot, high steady yaw rate gain, etc, is required by drivers under normal conditions, which is less concerned, however. Based on the hierarchical control methodology, a novel control system using direct yaw moment control for improving handling performance of a distributed drive electric vehicle especially under normal driving conditions has been proposed. The upper-loop control system consists of two parts: a state feedback controller, which aims to realize the ideal transient response of yaw rate, with a vehicle sideslip angle observer; and a steering wheel angle feedforward controller designed to achieve a desired yaw rate steady gain. Under the restriction of the effect of poles and zeros in the closed-loop transfer function on the system response and the capacity of in-wheel motors, the integrated time and absolute error (ITAE) function is utilized as the cost function in the optimal control to calculate the ideal eigen frequency and damper coefficient of the system and obtain optimal feedback matrix and feedforward matrix. Simulations and experiments with a DDEV under multiple maneuvers are carried out and show the effectiveness of the proposed method: yaw rate rising time is reduced, steady yaw rate gain is increased, vehicle steering characteristic is close to neutral steer and drivers burdens are also reduced. The control system improves vehicle handling performance under normal conditions in both transient and steady response. State feedback control instead of model following control is introduced in the control system so that the sense of control intervention to drivers is relieved.     

考虑路面影响的车辆稳定性控制质心侧偏角动态边界控制

路面附着系数与车辆稳定性控制的效果紧密联系,因此有必要在考虑路面影响的情况下设计一种能够适用于多种路面的质心侧偏角控制策略。在7自由度非线性动力学模型的基础上,由车轮侧向力与路面附着的关系,分析不同路面对质心侧偏角控制的影响。根据路面附着系数的不同,通过定义极限边界和线性区域边界,设计变化的动态质心侧偏角安全边界。根据横摆角速度增益判断车辆是否处于非线性状态,并在有逼近安全边界的趋势时提前施加控制,以避免产生由车轮纵向力增加引起的侧向力减小所造成的加剧车辆侧滑的趋势。基于非线性输入的滑模控制算法设计质心侧偏角控制器。通过Matlab/Simulink仿真和实车试验验证了该控制方法能够在不同附着路面条件下的有效地保证汽车的行驶稳定性。     

基于鲁棒积分滑模的四轮轮毂电机驱动电动汽车电液复合制动防抱死控制研究

为了充分发挥四轮轮毂电机驱动电动汽车电机制动与液压摩擦制动响应快且独立可控的优势,提高紧急制动时车辆稳定性与安全性,提出一种基于鲁棒积分滑模的电液复合制动防抱死控制策略。采用分层控制架构,上层控制器为基于鲁棒积分滑模的车轮滑移率控制,下层控制器为电液复合制动力协调分配。建立整车动力学与电液复合制动系统模型,基于Simulink-AMESim-Carsim联合仿真平台,在四种典型制动工况下对上述电液复合制动防抱死控制策略进行仿真验证。结果表明,在无需实时获取路面附着系数与轮胎纵向力的情况下,所提出的控制策略仍能消除外界干扰使车轮滑移率收敛至期望值,适用于多种紧急制动工况,响应迅速且鲁棒性强;电机再生制动与液压摩擦制动可稳定协同工作,在保证制动可靠性的同时提升了乘坐舒适性。     

增程式电动汽车增程器转速切换/功率跟随协调控制

针对电动汽车增程器系统中的发动机、发电机协调控制问题,提出了一种转速切换/功率跟随增程器协调控制策略。首先根据发动机的最佳制动燃油消耗率曲线设计了发动机的功率-转速切换表。然后,分别设计了基于发动机平均值模型的发动机转速二阶滑模控制系统和基于电压定向直接功率控制的PWM整流器功率控制系统。通过对发动机转速和PWM整流器输出功率的闭环控制,使发动机沿着最佳制动燃油消耗率曲线运行。最后,在AVL Cruise和MATLAB/Simulink仿真环境下搭建了系统的联合仿真模型,仿真结果从增程器功率跟随效果,发动机转速控制效果,动力电池电压、电流和SOC波动范围以及发动机工作点分布等方面验证了该策略的有效性。     

Output feedback model predictive control of hydraulic systems with disturbances compensation

Enhancing the robustness of output feedback control has always been an important issue in hydraulic servo systems. In this paper, an output feedback model predictive controller (MPC) with the integration of an extended state observer (ESO) is proposed for hydraulic systems. The ESO was designed to estimate not only the unmeasured system states but also the disturbances, which will be synthesized into the design of the output prediction equation. Based on the mechanism of receding horizon and repeating optimization of MPC, the output prediction equation will be updated in real time and the future behavior of the system will be accurately predicted since the disturbances are compensated effectively. Hence, the ability of the traditional MPC to suppress disturbances will be improved evidently. The experiment results show that the proposed controller has high-performance nature and strong robustness against various model uncertainties, which verifies the effectiveness of the proposed control strategy.     

基于变预测时域MPC的自动驾驶汽车轨迹跟踪控制研究

为了保证自动驾驶汽车轨迹跟踪的精度及行驶过程中的稳定性,提出一种基于车辆横向稳定状态在线识别和模糊算法的变预测时域模型预测控制（MPC）方法。针对车辆稳定状态的在线识别,采用k-means聚类算法对车辆行驶状态参数进行聚类分析,得到聚类质心,通过在线对比当前车辆状态量与不同聚类质心之间的欧氏距离获取车辆的实时安全等级。同时计算出当前车辆的轨迹跟踪横向偏移量,以这二者为输入,通过模糊控制算法在线计算出预测时域的变化量并输出给MPC控制器实现预测时域的自适应调整,最后求解出自动驾驶车辆跟踪轨迹的最优的控制序列,以达到在保持车辆稳定的前提下实现高精度轨迹跟踪控制的目的。CarSim/Simulink联合仿真结果表明,改进后的变预测时域MPC算法在提高自动驾驶汽车轨迹跟踪精度及横向稳定性方面的表现优于传统MPC控制器。     

基于ANFIS及MPC的车辆转向换道控制系统设计

为提高智能车辆在高速工况下进行转向换道避撞时的行驶稳定性,设计了一种基于ANFIS及MPC的车辆转向换道控制系统。车辆转向换道控制系统是以模型预测控制(Model Predictive Control, MPC)算法为基础,结合五阶多项式换道路径和最小车距安全模型搭建的;以理想横摆角速度与实际横摆角速度的偏差及其变化率为双输入,利用自适应神经模糊系统(Adaptive Network-based Fuzzy Inference System, ANFIS)规则输出所需的附加横摆力矩,对车轮进行差动制动,以修正车身姿态,实现行车稳定。仿真结果对比表明,此车辆转向换道控制系统可显著提高车辆在高速工况下进行转向换道避撞时的行驶稳定性。     

基于无级变速器的混合动力汽车动态模式切换研究

对基于无级变速器的混合动力系统的结构及其工作模式进行分析,建立了动力学模型。针对伴随发动机启动的混合动力模式切换问题,提出了一种模糊推理与最优控制理论相接合的综合控制策略。首先基于驾驶意图采用模糊控制得到离合器接合时长,然后基于动力学模型采用动态规划得到离合器的最优传递转矩和发动机的最优目标转矩,再根据离合器最优传递转矩利用电机的快速响应性来实时调整电机输出转矩。通过试验对上述模式切换控制策略进行了验证。试验结果表明：该策略能够优化离合器滑摩时间,体现驾驶意图,实现模式切换的平顺性。     

基于模型预测的感应电机弱磁控制研究

考虑工业场合对感应电机高速运行的实际需求,分析了感应电机在不同区域运行时的特点,特别对电机高速运行时的弱磁特性进行了研究,提出了一种基于模型预测算法的感应电机弱磁控制方法.首先预测被控对象未来的状态,再由滚动优化求出最优控制变量.仿真结果表明,基于模型预测算法的弱磁控制方法有更快的响应速度和较强的鲁棒性.     

[分布式驱动电动汽车动力学控制]基于转矩协调分配的分布式驱动电动汽车稳定性控制

A hierarchical vehicle-stability-control method was presented based on the longitudinal force distribution optimization for the handling and stability control of the distributed-driven electric vehicles. The eight-degree-freedom vehicle models and the three-layer control systems were developed. By selecting the sideslip angle and the yaw rate as the state variables and introducting the virtual control to decouple two control variables,  the integral 2-DOF vehicle models were adopted to calculate the equivalent yaw moments for the vehicle stability in upper controllers. The linear quadratic regulator （LQR） method was utilized to optimize the distribution of the front and rear steering angles and the tire longitudinal forces in middle controllers. The sliding-mode-based slip controller in the lower layer was also designed to reallocate the wheel torques. Simulation results show that the control system may make full use of the adhesion potential of the tire under high speed and extreme conditions, realize the coordinated distribution of wheel torques and improve the steering stability of the vehicles. When the actuators fail, the system may reconstruct effectively and realize the reallocation of control inputs to improve the safety of the vehicles.     

基于EMB和路面自动识别的汽车ABS仿真

针对电子机械制动系统(EMB)车辆进行研究,给出了简化的车辆仿真模型和EMB制动器仿真模型,并结合路面识别技术为之设计了相应的ABS模糊PID控制器仿真模型.ABS制动控制器模型采用基于车轮最优滑移率的控制策略,最优滑移率由路面自动识别系统准实时的得出,ABS控制算法采用模糊PID控制,对EMB制动器进行滑移率S和制动压力F的闭环控制.仿真采用Matlab中的simulink工具箱建模,仿真结果证明路面识别系统能够正确识别路面并确定最优滑移率,基于EMB制动控制器的车辆的ABS控制器始终将制动过程滑移率控制在路面识别系统确定的最优滑移率附近.     

汽车防抱死制动系统分级智能控制

在分析车辆制动时轮胎与地面接触力学特性的基础上,提出一种用轮速峰值连线来求解参考车速和参考滑移率的方法。为了解决汽车防抱死制动系统(ABS)在各种条件下复杂的控制问题,设计出一种由运行控制、参数校正和组织协调构成的分级智能控制系统。在运行控制级,给出参考滑移率误差的目标轨迹,建立特征模型、控制模态集和推理规则集,以此设计出基于参考滑移率的仿人智能控制器。在参数校正级,为了弥补只针对参考滑移率控制的不足,用车轮角减速度对仿人智能控制量进行校正。在组织协调级,设计出基于轮减速度和参考滑移率的模糊智能控制器来自动辨别制动时的路面信息,给出四轮制动的协调控制规则。运用Matlab进行汽车ABS的仿人智能控制系统研究,搭建出汽车ABS全车测控系统,参照国际标准,在不同条件下进行道路试验。试验结果表明,相对于逻辑门限控制,ABS分级智能控制具有良好的制动平稳性和自适应性,可提高控制精度,是一种有效的新的ABS控制方法。     

基于控制分配的主动前轮独立转向车辆转角分配算法

针对新近提出的主动前轮独立转向(AIFS)系统基于规则的转角分配方法自适应性差、无法实现最优分配的问题,提出了一种基于控制分配的转角分配算法。指出了传统主动前轮转向(AFS)存在的问题,阐述了主动前轮独立转向系统的结构和工作原理;在MATLAB/Simulink中建立了整车四自由度数学模型,设计了AIFS滑模控制器和转角分配模块;通过阶跃转向工况对所提出的转角分配算法进行了仿真验证。结果表明：该分配算法可以使AIFS自适应内外轮载荷转移变化,自动调整内外轮转角大小,较AFS可以更好地跟踪理想横摆角速度和理想运动轨迹,实现了“能力越大的轮胎贡献越大”的控制目标,提高了车辆极限转弯时的侧向稳定性。       

Estimation of Road Friction Coefficient in Different Road Conditions Based on Vehicle Braking Dynamics

The accurate estimation of road friction coefficient in the active safety control system has become increasingly prominent. Most previous studies on road friction estimation have only used vehicle longitudinal or lateral dynamics and often ignored the load transfer, which tends to cause inaccurate of the actual road friction coefficient. A novel method considering load transfer of front and rear axles is proposed to estimate road friction coefficient based on braking dynamic model of two-wheeled vehicle. Sliding mode control technique is used to build the ideal braking torque controller, which control target is to control the actual wheel slip ratio of front and rear wheels tracking the ideal wheel slip ratio. In order to eliminate the chattering problem of the sliding mode controller, integral switching surface is used to design the sliding mode surface. A second order linear extended state observer is designed to observe road friction coefficient based on wheel speed and braking torque of front and rear wheels.The proposed road friction coefficient estimation schemes are evaluated by simulation in ADAMS/Car. The results show that the estimated values can well agree with the actual values in different road conditions. The observer can estimate road friction coefficient exactly in real-time andresist external disturbance. The proposed research provides a novel method to estimate road friction coefficient with strong robustness and more accurate.