A Mathematical Model for Driver Steering Control,with Design,Tuning and Performance Results

A mathematical model for the steering control of an automobile is described. The structure of the model derives from linear optimal discrete time preview control theory but it is non-linear. Its parameter values are obtained by heuristic methods, using insight gained from the linear optimal control theory. The driver model is joined to a vehicle dynamics model and the path tracking performance is demonstrated, using moderate manoeuvring and racing speeds. The model is shown to be capable of excellent path following and to be robust against changes in the vehicle dynamics. Application to the simulation of manoeuvres specified by an ideal vehicle path and further development of the model to formalise the derivation of its parameter values and to put it to other uses are discussed.     

Linear Quadratic Gaussian Control of a Quarter-Car Suspension

This paper presents a method for designing linear multivariable controllers in the frequency-domain for an intelligent controlled suspension system for a quarter-car model. The design methodology uses singular value inequalities and optimal control theory. The vehicle system is augmented with additional dynamics in the form of an integrator to affect the loop shapes of the system. The measurements are assumed to be obtained in a noisy state, and the optimal control gain and the Kalman filter gain are derived using system dynamics and noise statistics. A combination of singular value analysis, eigenvalue analysis, time response, and power spectral densities of random response is used to describe the performance of the active suspension systems.     

Linear Quadratic Gaussian Control of a Quarter-Car Suspension

This paper presents a method for designing linear multivariable controllers in the frequency-domain for an intelligent controlled suspension system for a quarter-car model. The design methodology uses singular value inequalities and optimal control theory. The vehicle system is augmented with additional dynamics in the form of an integrator to affect the loop shapes of the system. The measurements are assumed to be obtained in a noisy state, and the optimal control gain and the Kalman filter gain are derived using system dynamics and noise statistics. A combination of singular value analysis, eigenvalue analysis, time response, and power spectral densities of random response is used to describe the performance of the active suspension systems.     

车速控制系统自适应油门控制器设计

在分析非线性车辆纵向动力学模型及简化模型基础上，采用一种简化非线件模型设计自适应油门控制器，并应用李亚谱诺夫理论证明了传动系统存在动态过程时控制系统的稳定性。通过对基于简化线性和非线性模燃的自适应控制器的仿真研究，结果表明后者具有更好的收敛性。试验结果也进一步表明，基于非线性模型的自适应控制器可以通过自适应调节减小参数不确定造成的干扰，当传动系统存在动态过程时可以保证车速跟踪误差有界。     

汽车主动悬架与电动助力转向系统多目标优化及集成控制

建立了整车主动悬架和电动助力转向系统动力学模型,构建线性控制的主动悬架和PD控制的电动助力转向系统集成控制器,应用遗传算法对集成控制系统的结构参数和控制参数进行多目标优化。结果表明,经过多目标优化后的集成控制系统,既可保证车辆操纵轻便性,又显著提高了整车操纵稳定性、安全性和行驶平顺性。     

Vehicle stability control system for enhancing steerabilty,lateral stability,and roll stability

The Vehicle stability control system is an active safety system designed to prevent accidents from occurring and to stabilize dynamic maneuvers of a vehicle by generating an artificial yaw moment using differential brakes. In this paper, in order to enhance vehicle steerability, lateral stability, and roll stability, each reference yaw rate is designed and combined into a target yaw rate depending on the driving situation. A yaw rate controller is designed to track the target yaw rate based on sliding mode control theory. To generate the total yaw moment required from the proposed yaw rate controller, each brake pressure is properly distributed with effective control wheel decision. Estimators are developed to identify the roll angle and body sideslip angle of a vehicle based on the simplified roll dynamics model and parameter adaptation approach. The performance of the proposed vehicle stability control system and estimation algorithms is verified with simulation results and experimental results.     

Optimal motion control for collision avoidance at Left Turn Across Path/Opposite Direction intersection scenarios using electric propulsion

Collision avoidance at intersections involving a host vehicle turning left across the path of an oncoming vehicle (Left Turn Across Path/Opposite Direction) have been studied in the past, but mostly using simplified interventions and rarely considering the possibility of crossing the intersection ahead of a bullet vehicle. Such a scenario where the driver preference is to avoid a collision by crossing the intersection ahead of a bullet vehicle is considered in this work. The optimal vehicle motion for collision avoidance in this scenario is determined analytically using a particle model within an optimal control framework. The optimal manoeuvres are then verified through numerical optimisations using a two-track vehicle model, where it was seen that the wheel forces followed the analytical global force angle result independently of the other wheels. A Modified Hamiltonian Algorithm controller for collision avoidance that uses the analytical optimal control solution is then implemented and tested in CarMaker simulations using a validated Volvo XC90 vehicle model. Simulation results showed that collision risk can be significantly reduced in this scenario using the proposed controller, and that more benefit can be expected in scenarios that require larger speed changes.     

新型视觉区域智能车辆导航控制器设计

简要介绍了基于机器视觉导航区域智能车辆(CyberCar)的导航原理和组成。首先采用逆M序列作为辨识输入信号和最小二乘算法得到车辆转向系统的系统辨识特征方程,结合预瞄运动学模型和车辆二自由度转向动力学模型,从而建立车辆基于视觉预瞄的转向动力学控制数学模型,根据线性二次型最优控制理论得到状态线性反馈的最优控制规律。通过仿真分析和试验,验证了最优控制器在CyberCar户外路径跟踪过程中平稳、可靠。     

DCT直线型换挡动力学仿真（续1）

为了使汽车冲击度和离合器滑摩功能够满足换挡品质的要求,文章对装有双离合器自动变速器（DCT）的汽车进行了动力学仿真分析,建立其变速器动力传动系统模型。并针对变速器直线型换挡过程中冲击度和滑摩功难以同时达到最优的问题,采用遗传算法对离合器油压值进行优化控制,获得油压-时间的最优控制曲线,将优化后的控制曲线代入仿真模型,结果表明,冲击度和滑摩功均达到较为理想的状态。     

Vehicle handling dynamics modelling by a data-driven identification method

Modelling of vehicle handling dynamics has received a renewed attention in recent years. Different from traditional vehicle modelling, a novel data-driven identification method for vehicle handling dynamics is proposed, which can avoid the problems of the under-modelling and parameter uncertainties in the first-principle modelling process. By first-order Taylor expansion, the nonlinear vehicle system can be linearised as a slowly linear time-varying system with fourth-order. In order to identify the derived identifiable model structure, a recursive subspace method is presented. Derived by optimal version of predictor-based subspace identification (PBSID_opt) and projection approximation subspace tracking (PAST), the identification method is numerical stability and gives an unbiased estimation for the closed-loop system. Based on standard road tests, the proposed modelling method is proven effective and the obtained model has good predictive ability. Additionally, it is noted that the model obtained from the initial phase of straight driving is just a mathematical model to describe the relationship between input and output. And when the vehicle is steering, the model can converge to a stable phase quickly and represent vehicle dynamic performance.     

Effect of vehicle model on the estimation of lateral vehicle dynamics

A methodology is presented for estimating vehicle handling dynamics, which are important to control system design and safety measures. The methodology, which is based on an extended Kalman filter (EKF), makes it possible to estimate lateral vehicle states and tire forces on the basis of the results obtained from sinusoidal steering stroke tests that are widely used in the evaluation of vehicle and tire handling performances. This paper investigates the effect of vehicle-road system models on the estimation of lateral vehicle dynamics in the EKF. Various vehicle-road system models are considered in this study: vehicle models (2-DOF, 3-DOF, 4-DOF), tire models (linear, non-linear) and relaxation lengths. Handling tests are performed with a vehicle equipped with sensors that are widely used by vehicle and tire manufacturers for handling maneuvers. The test data are then used in the estimation of the EKF and identification of lateral tire model coefficients. The accuracy of the identified values is validated by comparing the RMS error between experimentally measured states and regenerated states simulated using the identified coefficients. The results show that the relaxation length of the tire model has a notable impact on the estimation of lateral vehicle dynamics.     

Formulation and interpretation of optimal braking and steering patterns towards autonomous safety-critical manoeuvres

ABSTRACT

Stability control of a vehicle in autonomous safety-critical at-the-limit manoeuvres is analysed from the perspective of lane keeping or lane changing, rather than that of yaw control as in traditional ESC systems. An optimal control formulation is developed, where the optimisation criterion is a linear combination of the initial and final velocity of the manoeuvre. Varying the interpolation parameter in this formulation turns out to result in an interesting family of optimal braking and steering patterns in stabilising manoeuvres. The two different strategies of optimal lane-keeping control and optimal yaw control are shown to be embedded in the formulation and result from the boundary values of the parameter. The results provide new insights and have the potential to be used for future safety systems that adapt the level of braking to the situation at hand, which is demonstrated through examples of how to exploit theresults.     

基于ADAMS与Matlab的ABS模糊控制仿真研究

将多体系统动力学与智能控制理论相结合对汽车制动防抱死控制系统进行了研究，利用ADAMS／CAR建立了汽车整车的多体力学模型，模型包含了前后悬架、动力总成、转向系统、稳定杆、制动系、轮胎力学模型以及车身，同时也考虑了轮胎、衬套、弹簧、减震器等部件的非线性，准确地表达了车辆的动态特性；利用Matlab／Simulink模糊控制工具箱建立了制动防抱死控制系统的模糊控制策略，利用ADAMS／Control接口进行模型的集成、协同仿真，并将仿真结果与另一种控制策略一逻辑门限值控制的仿真结果进行了比较和分析，仿真反映出模糊控制在整车制动防抱死控制系统上的应用效果，结果表明该控制算法稳定好并具有较强的鲁棒性。     

Effect of handling characteristics on minimum time cornering with torque vectoring

In this paper, the effect of both passive and actively-modified vehicle handling characteristics on minimum time manoeuvring for vehicles with 4-wheel torque vectoring (TV) capability is studied. First, a baseline optimal TV strategy is sought, independent of any causal control law. An optimal control problem (OCP) is initially formulated considering 4 independent wheel torque inputs, together with the steering angle rate, as the control variables. Using this formulation, the performance benefit using TV against an electric drive train with a fixed torque distribution, is demonstrated. The sensitivity of TV-controlled manoeuvre time to the passive understeer gradient of the vehicle is then studied. A second formulation of the OCP is introduced where a closed-loop TV controller is incorporated into the system dynamics of the OCP. This formulation allows the effect of actively modifying a vehicle's handling characteristic via TV on its minimum time cornering performance of the vehicle to be assessed. In particular, the effect of the target understeer gradient as the key tuning parameter of the literature-standard steady-state linear single-track model yaw rate reference is analysed.     

Optimization of curving performance of rail vehicles

The curving performance of a transit rail vehicle model with 21 degrees of freedom is optimized using a combination of multibody dynamics and a genetic algorithm (GA). The design optimization is to search for optimal design variables so that the noise or wear, arising from misalignment of the wheelsets with the track, is reduced to a minimum level during curve negotiations with flange contact forces guiding the rail vehicle. The objective function is a weighted combination of angle of attack on wheelsets and ratios of lateral to vertical forces on wheels. Using the combination of the GA and a multibody dynamics modelling program, A’GEM, the generation of governing equations of motion for complex nonlinear dynamic rail vehicle models and the search for global optimal design variables can be carried out automatically. To demonstrate the feasibility and efficacy of the proposed approach of using the combination of multibody dynamics and GAs, the numerical simulation results of the optimization are offered, the selected objective function is justified, and the sensitivity analysis of different design parameters and different design parameter sets on curving performance is performed. Numerical results show that compared with suspension and inertial parameter sets, the geometric parameter set has the most significant effect on curving performance.     

Optimization of curving performance of rail vehicles

The curving performance of a transit rail vehicle model with 21 degrees of freedom is optimized using a combination of multibody dynamics and a genetic algorithm (GA). The design optimization is to search for optimal design variables so that the noise or wear, arising from misalignment of the wheelsets with the track, is reduced to a minimum level during curve negotiations with flange contact forces guiding the rail vehicle. The objective function is a weighted combination of angle of attack on wheelsets and ratios of lateral to vertical forces on wheels. Using the combination of the GA and a multibody dynamics modelling program, A'GEM, the generation of governing equations of motion for complex nonlinear dynamic rail vehicle models and the search for global optimal design variables can be carried out automatically. To demonstrate the feasibility and efficacy of the proposed approach of using the combination of multibody dynamics and GAs, the numerical simulation results of the optimization are offered, the selected objective function is justified, and the sensitivity analysis of different design parameters and different design parameter sets on curving performance is performed. Numerical results show that compared with suspension and inertial parameter sets, the geometric parameter set has the most significant effect on curving performance.     

Research on automated lane tracking using linear quadratic control:: control procedure for a curved path

When an automated vehicle is travelling along a curved path, the yaw rate and yaw angle do not have values of zero. This means that it is impossible to apply a simple regulator that converges the values of all state variables to zero. This paper describes the use of a set point regulator, which applies linear quadratic control theory while shifting the equilibrium point in a situation where the road curvature is given as feed-forward information. It also proposes a control method that enables an automated vehicle to navigate curves without feed-forward information by estimating the road curvature as it proceeds.     

基于SIMPACK的汽车操纵稳定性仿真分析

本文根据多体动力学理论基础,应用多体系统动力学仿真分析软件SIMPACK建立了汽车的整车模型,将驾驶员前方预描距离作为控制参数输入到转向操纵系统中,进而形成人-车闭路系统的仿真。