Road Friction Estimation under Complicated Maneuver Conditions for Active Yaw Control

Road friction coefficient is a key factor for the stability control of the vehicle dynamics in the critical conditions. Obviously the vehicle dynamics stability control systems, including the anti-lock brake system（ABS）, the traction control system（TCS）, and the active yaw control（AYC） system, need the accurate tire and road friction information. However, the simplified method based on the linear tire and vehicle model could not obtain the accurate road friction coefficient for the complicated maneuver of the vehicle. Because the active braking control mode of AYC is different from that of ABS, the road friction coefficient cannot be estimated only with the dynamics states of the tire. With the related dynamics states measured by the sensors of AYC, a comprehensive strategy of the road friction estimation for the active yaw control is brought forward with the sensor fusion technique. Firstly, the variations of the dynamics characteristics of vehicle and tire, and the stability control mode in the steering process are considered, and then the proper road friction estimation methods are brought forward according to the vehicle maneuver process. In the steering maneuver without braking, the comprehensive road friction from the four wheels may be estimated based on the multi-sensor signal fusion method. The estimated values of the road friction reflect the road friction characteristic. When the active brake involved, the road friction coefficient of the braked wheel may be estimated based on the brake pressure and tire forces, the estimated values reflect the road friction between the braked wheel and the road. So the optimal control of the wheel slip rate may be obtained according to the road friction coefficient. The methods proposed in the paper are integrated into the real time controller of AYC, which is matched onto the test vehicle. The ground tests validate the accuracy of the proposed method under the complicated maneuver conditions.

Model Predictive Yaw Control Using Fuzzy-Deduced Weighting Factor for Large-Scale Wind Turbines

Yaw control system plays an important role in helping large-scale horizontal wind turbines capture the wind energy.To track the stochastic and fast-changing wind direction,the nacelle is rotated by the yaw control system.Therein,a difficulty consists in the variation speed of the wind direction much faster than the rotation speed of the nacelle.To deal with this difficulty,model predictive control has been recently proposed in the literature,in which the previewed wind direction is employed into the predictive model,and the estimated captured energy and yaw actuator usage are two contradictive objectives.Since the performance of the model predictive control strat-egy relies largely on the weighting factor that is designed to balance the two objectives,the weighting factor should be carefully selected.In this study,a fuzzy-deduced scheme is proposed to derive the weighting factor of the mod-el predictive yaw control.For the proposed fuzzy-deduced strategy,the variation degree and the increment of the wind direction during the predictive horizon are used as the inputs,and the weighting factor is the output,which is dynamically adjusted.The proposed model predictive yaw control is demonstrated by some simulations using real wind data and its performance is compared with the conventional model predictive control with thefixed weighting factor.Comparison results confirm the outweighing performance of the proposed control strategy over the conventional one.

A Genetic Algorithm for Optimizing Yaw Operation Control in Wind Power Plants

A genetic algorithm is proposed to optimize the yaw control system used for the stable and efficient operation of turbines in wind power plants.In particular,the factors that produce yaw static deviation are analyzed.Then,the sought optimization method for the yaw static deviation of the wind turbine is implemented by using a lidar wind meter in the engine room in order to solve the low accuracy problem caused by yaw static deviation.It is shown that fuzzy control can overcome problematic factors such as the randomness of wind direction and track the change of wind direction accurately.Power control implementation is simple,as only the voltage and current of the generator need to be measured.

Design of Yaw Controller for a Small Unmanned Helicopter Based on Improved ADRC

Yaw control is signi¯cant to the attitude control of small unmanned helicopters(SUHs).Since the existing robust control method cannot be applied to the SUH with unknown dynamics and disturbances,this paper proposes an improved active disturbance rejection control(IADRC)to solve the problem.The IADRC obtains the optimal solution of the actuator gain(b0)by gradient descent.Besides,this paper summarizes some experiences during the tuning process of ADRC,which signi¯cantly reduces the di±culty of designing ADRC.Finally,the experimental results show that the proposed method is better than the traditional PID in robust and tracking control performance.

An Adaptive Nonsingular Fast Terminal Sliding Mode Control for Yaw Stability Control of Bus Based on STI Tire Model

Due to the bus characteristics of large quality,high center of gravity and narrow wheelbase,the research of its yaw stability control(YSC)system has become the focus in the field of vehicle system dynamics.However,the tire nonlinear mechanical properties and the effectiveness of the YSC control system are not considered carefully in the current research.In this paper,a novel adaptive nonsingular fast terminal sliding mode(ANFTSM)control scheme for YSC is proposed to improve the bus curve driving stability and safety on slippery roads.Firstly,the STI(Systems Technologies Inc.)tire model,which can effectively reflect the nonlinear coupling relationship between the tire longitudinal force and lateral force,is established based on experimental data and firstly adopted in the bus YSC system design.On this basis,a more accurate bus lateral dynamics model is built and a novel YSC strategy based on ANFTSM,which has the merits of fast transient response,finite time convergence and high robustness against uncertainties and external disturbances,is designed.Thirdly,to solve the optimal allocation problem of the tire forces,whose objective is to achieve the desired direct yaw moment through the effective distribution of the brake force of each tire,the robust least-squares allocation method is adopted.To verify the feasibility,effectiveness and practicality of the proposed bus YSC approach,the TruckSim-Simulink co-simulation results are finally provided.The co-simulation results show that the lateral stability of bus under special driving conditions has been significantly improved.This research proposes a more effective design method for bus YSC system based on a more accurate tire model.

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.

Research on Direct Yaw Moment Control Strategy of Distributed-Drive Electric Vehicle Based on Joint Observer

Combined with the characteristics of the distributed-drive electric vehicle and direct yaw moment control,a double-layer structure direct yaw moment controller is designed.The upper additional yaw moment controller is constructed based on model predictive control.Aiming at minimizing the utilization rate of tire adhesion and constrained by the working characteristics of motor system and brake system,a quadratic programming active set was designed to optimize the distribution of additional yaw moments.The road surface adhesion coefficient has a great impact on the reliability of direct yaw moment control,for which joint observer of vehicle state parameters and road surface parameters is designed by using unscented Kalman filter algorithm,which correlates vehicle state observer and road surface parameter observer to form closed-loop feedback correction.The results show that compared to the“feedforward+feedback”control,the vehicle’s error of yaw rate and sideslip angle by the model predictive control is smaller,which can improve the vehicle stability effectively.In addition,according to the results of the docking road simulation test,the joint observer of vehicle state and road surface parameters can improve the adaptability of the vehicle stability controller to the road conditions with variable adhesion coefficients.

车辆稳定性因数自学习策略研究

稳定性因数是表征汽车稳态响应的关键参数,对车辆横摆控制至关重要。由于影响稳定性因数的因素众多,如整车质量、质心位置、轮胎气压和侧偏刚度等,准确获取稳定性因数颇具难度。同时,车辆行驶过程中,轮胎磨损、胎压变化或轮胎型号改变等都会导致稳定性因数变化,进而影响车辆横摆控制。基于此背景,文章以稳定性因数理论模型为基础,结合车辆运动学方程,开发车辆稳定性因数自学习策略。实车测试表明,该方法能有效修正车辆稳定性因数,提升横摆控制效果。

A Novel Pre-control Method of Vehicle Dynamics Stability Based on Critical Stable Velocity during Transient Steering Maneuvering

The current research of direct yaw moment control（DYC） system focus on the design of target yaw moment and the distribution of wheel brake force. The differential braking intervention can effectively improve the lateral stability of the vehicle, however, the effect of DYC can be improved a step further by applying the control of vehicle longitudinal velocity. In this paper, the relationship between the vehicle longitudinal velocity and lateral stability is studied, and the simulation results show that a decrease of 5 km/h of longitudinal velocity at a particular situation can bring 100° increasing of stable steering upper limit. A critical stable velocity considering the effect of steering and yaw rate measurement is defined to evaluate the risk of losing steer-ability or stability. A novel velocity pre-control method is proposed by using a hierarchical pre-control logic and is integrated with the traditional DYC system. The control algorithm is verified through a hardware in-the-loop simulation system. Double lane change（DLC） test results on both high friction coefficient（μ） and low μ roads show that by using the pre-control method, the steering effort in DLC test can be reduced by 38% and 51% and the peak value of brake pressure control can be reduced by 20% and 12% respectively on high μ and low μ roads, the lateral stability is also improved. This research proposes a novel DYC system with lighter control effort and better control effect.

Trajectory Tracking of Autonomous Vehicle with the Fusion of DYC and Longitudinal–Lateral Control

The current research of autonomous vehicle motion control mainly focuses on trajectory tracking and velocity tracking. However, numerous studies deal with trajectory tracking and velocity tracking separately, and the yaw stability is seldom considered during trajectory tracking. In this research, a combination of the longitudinal–lateral control method with the yaw stability in the trajectory tracking for autonomous vehicles is studied. Based on the vehicle dynamics, considering the longitudinal and lateral motion of the vehicle, the velocity tracking and trajectory tracking problems can be attributed to the longitudinal and lateral control. A sliding mode variable structure control method is used in the longitudinal control. The total driving force is obtained from the velocity error in order to carry out velocity tracking. A linear time-varying model predictive control method is used in the lateral control to predict the required front wheel angle for trajectory tracking. Furthermore, a combined control framework is established to control the longitudinal and lateral motions and improve the reliability of the longitudinal and lateral direction control. On this basis, the driving force of a tire is allocated reasonably by using the direct yaw moment control, which ensures good yaw stability of the vehicle when tracking the trajectory. Simulation results indicate that the proposed control strategy is good in tracking the reference velocity and trajectory and improves the performance of the stability of the vehicle.

Map-based control method for vehicle stability enhancement

This work proposes a map-based control method to improve a vehicle's lateral stability, and the performance of the proposed method is compared with that of the conventional model-referenced control method. Model-referenced control uses the sliding mode method to determine the compensated yaw moment; in contrast, the proposed map-based control uses the compensated yaw moment map acquired by vehicle stability analysis. The vehicle stability region is calculated by a topological method based on the trajectory reversal method. A 2-DOF vehicle model and Pacejka's tire model are used to evaluate the proposed map-based control method. The properties of model-referenced control and map-based control are compared under various road conditions and driving inputs. Model-referenced control uses a control input to satisfy the linear reference model, and it generates unnecessary tire lateral forces that may lead to worse performance than an uncontrolled vehicle with step steering input on a road with a low friction coefficient. However, map-based control determines a compensated yaw moment to maintain the vehicle within the stability region,so the typical responses of vehicle enable to converge rapidly. The simulation results with sine and step steering show that map-based control provides better the tracking responsibility and control performance than model-referenced control.

基于主动尾流控制的风电机群协同优化调度

针对机组间尾流效应严重影响风电机组发电效率的问题,提出了风电机组安全偏航约束计算方法、尾流特性混合半机理建模方法以及风电机群多目标协同优化调度方法。基于FAST.FARM平台完善了多自由度可控机组与尾流的动态交互集成仿真环境,对比分析了2台机组串列式排布以及华东地区某海上风电场7台机组实际排布下的协同运行优化性能。结果表明:所建立的集成仿真模型能够合理表征风电机群与空气流场的多领域动态交互特性,所提方法能够有效提升风电机群发电效能,促进经济效益、资源利用和成本控制的均衡优化。

新能源汽车电机节能直接横摆力矩控制研究

为了降低电动汽车在行驶过程中的电机能量消耗,采用直接横摆力矩控制方法,并对车辆的车轮力矩和电机功率变化进行仿真验证。建立了车辆模型简图,根据牛顿第二定律推导出车辆转向运动方程式。针对传统两轮等力矩控制方法进行改进,提出了一种主动直接横摆力矩控制方法,推导出车辆连续行驶和转弯过程中的力矩分配律。利用转弯过程中车辆车轮的力矩变化来调节电机的功率变化,从而降低车辆电机的能量消耗。采用MATLAB软件对车辆横摆角速度、车轮力矩和电机能量消耗进行仿真,与两轮等力矩控制方法进行对比。结果显示:采用两轮等力矩控制方法,车辆横摆角速度跟踪误差较大,车轮力矩变化幅度较小,自适应调节能力较差,导致电机能量消耗较多;采用直接横摆力矩控制方法,车辆横摆角速度跟踪误差较小,车轮力矩变化幅度较大,自适应调节能力较好,使电机能量消耗较少。采用直接横摆力矩控制方法,能够自适应调整车轮力矩的变化,从而达到降低电机能量消耗目的。

分布驱动式纯电动汽车电子差速控制策略研究

以轮毂电机直接驱动的分布驱动式电动车为研究对象,为解决汽车转向行驶稳定性和主动安全性的问题,对其电子差速控制策略进行研究。将汽车转向时的横摆稳定性和车轮滑动率相结合,基于动力学计算转矩输出,使用模糊控制算法确定变量范围并设计出模糊控制器,采用双移线和方向盘角阶跃两种输入工况,通过CarSim搭建整车仿真联合模型,对两种电子差速控制策略的对比分析及仿真验证。结果表明,采用DYC+S控制策略比采用DYC+T控制策略的性能更加优越,提高了整车的驾驶性能。

风力机偏航对尾迹演化影响的实验研究

【目的】风力机尾流影响风电场的整体功率输出,对尾流特性进行分析是研究偏航控制对尾流影响的关键。为此,研究了上游风力机不同偏航角对尾流特征(如湍流积分尺度、功率谱密度等)以及尾流中涡流运动等方面的影响,以深入了解偏航状态下风力机尾流特性。【方法】采用风洞对0°、15°、30°偏航角的风力机下游尾迹演化规律进行研究。使用湍流积分尺度及功率谱密度等描述尾流特征,并以此分析不同特征点之间的相关性。【结果】偏航角对水平方向的尾流影响较小,湍流积分尺度变化不大;垂直方向上的湍流积分尺度在不同偏航角下具有较大的波动。通过对功率谱密度的分析,进一步量化了涡流运动对尾流湍动能的贡献。0°偏航时的来流受风力机旋转的扰动程度比15°偏航时小;但偏航角的增大并不总是导致风轮对来流的破坏程度增加,30°偏航时对来流涡结构的解耦作用比15°偏航时小。【结论】偏航角对风力机尾流在水平和垂直方向上的影响具有明显差异;功率谱密度分析为理解涡流运动对尾流湍动能的贡献提供了量化依据,有助于深入研究尾流中的能量传递和流动机制;偏航角与风轮对来流的扰动和解耦作用之间并非简单的正相关关系,这为风力机的优化运行和风电场的布局提供了参考依据。

电动汽车行驶稳定性模型预测控制仿真研究

为了提高电动汽车行驶的稳定性,提出了一种集成的汽车和车轮稳定性控制系统,并对汽车行驶的稳定性控制效果进行仿真。创建电动汽车模型简图,给出电动汽车动力学方程式。采用模型预测控制技术,设计了一种集成的汽车和车轮稳定性控制器。采用MATLAB软件对电动汽车横摆角速度、行驶速度和侧滑角进行仿真,与无模型预测控制器输出结果进行对比。结果显示:采用无模型预测控制器,电动汽车横摆角速度、行驶速度跟踪误差较大,振动幅度较大,产生的侧滑角较大。采用模型预测控制器,电动汽车横摆角速度、行驶速度跟踪误差较小,振动幅度较小,产生的侧滑角较小。采用模型预测控制器,能够提高电动汽车行驶的稳定性,避免汽车在突然转弯时发生侧翻现象。

基于风况预测误差自适应的海上风电场尾流偏转控制方法

风电场尾流偏转控制是降低尾流效应、提升整场发电量的重要手段。风况预测值是风电场尾流偏转控制的重要输入,其误差给实际控制效果带来巨大影响,甚至导致全场发电量“不增反降”,极大限制了风电场尾流偏转控制技术的工程应用。以某海上风电场实际运行数据为例,探索了分钟级风速和风向预测误差对风电场尾流偏转控制效果的影响,提出了风况预测误差自适应的海上风电场尾流偏转控制方法及基于深度神经网络的控制模型。研究结果表明:与不考虑风况预测误差自适应的传统风电场尾流偏转控制方法相比,所提方法的全场发电量提高了1.77%。

分布驱动无人车在极限工况下的稳定跟踪控制

针对分布式驱动无人车在低附着、高速的极限工况下行驶时偏离目标路径和失稳的现象,提出一种稳定-跟踪联合控制策略,策略包含路径跟踪控制和横向稳定控制,使无人车在提高跟踪精度的同时又使其稳定性得到保障。路径跟踪模块在汽车二自由度模型的基础上,建立了最优LQR路径跟踪控制器,并引入前馈用以改善稳态误差,其次考虑误差变化的规律和路-车位置关系以及驾驶员预瞄模型,设计了改进的权重参数自适应LQR控制器;稳定性模块基于可以减小系统抖振的滑模模糊控制原理,并结合汽车稳定性参数的实际值与期望值的差值,求解出横摆力矩。其次在分配各轮转矩时建立约束条件,使得轮胎负荷率最小用以提升汽车的操纵稳定性。CarSim/Simulink仿真表明在高速、低附着的换道工况下,改进后的LQR控制器有效地改善跟踪误差,具有良好的鲁棒性。且在加入稳定性控制器后,横摆角速度与质心侧偏角的调节时间变短,极大改善了无人车在极限工况下的稳定性。

考虑稳定性的4WD/4WS无人车路径跟踪控制策略研究

根据分布式四轮驱动/转向的无人车单轮独可控的特点,提出一种考虑稳定性的路径跟踪控制策略,以提升无人车在高速、低附着工况下的车辆稳定性:具体通过预瞄-跟随理论搭建路径跟踪控制器,实现对无人车规划路径的实时跟踪;并通过滑模控制理论对后轮转角和直接横摆力矩进行集成控制,考虑前后轴荷及路面附着系数实现转矩分配,提高车身稳定性。仿真结果表明:相对于未考虑稳定性的路径跟踪控制策略,考虑稳定性的路径跟踪策略在高速双移线工况下,平均横向跟踪误差下降5.2%,质心侧偏角峰值下降57.4%,横摆角速度峰值下降23%;在低附着山路工况下,平均横向跟踪误差下降9.1%,质心侧偏角峰值下降54.3%,横摆角速度峰值下降1.4%,车辆能够保持良好的跟踪能力和行驶稳定性。