基于轴间预瞄的主动悬架研究

以某型汽车的1／2车辆模型为研究对象，提出了一种轴间预瞄控制的方法，并结合最优控制理论设计了车辆悬架的控制策略。通过模拟和仿真分析，验证了所提出的轴间预瞄比传统的轴距预瞄具有更好的控制效果。     

Optimisation of active suspension control inputs for improved vehicle ride performance

A collocation-type control variable optimisation method is used in the paper to analyse to which extent the fully active suspension (FAS) can improve the vehicle ride comfort while preserving the wheel holding ability. The method is first applied for a cosine-shaped bump road disturbance of different heights, and for both quarter-car and full 10 degree-of-freedom vehicle models. A nonlinear anti-wheel hop constraint is considered, and the influence of bump preview time period is analysed. The analysis is then extended to the case of square- or cosine-shaped pothole with different lengths, and the quarter-car model. In this case, the cost function is extended with FAS energy consumption and wheel damage resilience costs. The FAS action is found to be such to provide a wheel hop over the pothole, in order to avoid or minimise the damage at the pothole trailing edge. In the case of long pothole, when the FAS cannot provide the wheel hop, the wheel is travelling over the pothole bottom and then hops over the pothole trailing edge. The numerical optimisation results are accompanied by a simplified algebraic analysis.     

混合动力汽车匀速下坡再生制动模型预测控制

基于车载导航系统(GPS/CIS等)所提供的未来一段预测路线上的汽车运行状态信息,建立中度混合动力汽车再生制动能量回收的全局优化动态规划模型;采用模型预测控制方法,将动态规划的全局优化控制策略转化成预测视距内的局部优化算法,实现滚动优化控制;为解决动态规划中的维数灾问题,确定了电池荷电状态和温度的可达区域;对模型预测控制策略、全局优化控制策略和瞬时优化控制策略进行了计算比较,在不同坡度、不同坡长的匀速下坡工况下的仿真表明:模型预测算法的计算效率显著高于全局优化策略的;应用模型预测控制策略的再生制动能量回收效率明显高于瞬时优化控制策略的,相比全局优化策略的降低不到1.31%,且采用档位提示的模型预测控制策略能量回收效果更好.     

Optimal control to modelling motorcycle rider steering: local versus global coordinate systems in rider preview

The response of a motorcycle is heavily dependent on the rider’s control actions, and consequently a means of replicating the rider’s behaviour provides an important extension to motorcycle dynamics. The primary objective here is to develop effective path-following simulations and to understand how riders control motorcycles. Optimal control theory is applied to the tracking of roadway by a motorcycle, using a non-linear motorcycle model operating in free control by steering torque input. A path-following controller with road preview is designed by minimising tracking errors and control effort. Tight controls with high weightings on performance and loose controls with high weightings on control power are defined. Special attention is paid to the modelling of multipoint preview in local and global coordinate systems. The controller model is simulated over a standard single lane-change manoeuvre. It is argued that the local coordinates point of view is more representative of the way that a human rider operates and interprets information. The simulations suggest that for accurate path following, using optimal control, the problem must be solved by the local coordinates approach in order to achieve accurate results with short preview horizons. Furthermore, some weaknesses of the optimal control approach are highlighted here.     

Models and methodology for optimal trajectory generation in safety-critical road–vehicle manoeuvres

There is currently a strongly growing interest in obtaining optimal control solutions for vehicle manoeuvres, both in order to understand optimal vehicle behaviour and, perhaps more importantly, to devise improved safety systems, either by direct deployment of the solutions or by including mimicked driving techniques of professional drivers. However, it is non-trivial to find the right combination of models, optimisation criteria, and optimisation tools to get useful results for the above purposes. Here, a platform for investigation of these aspects is developed based on a state-of-the-art optimisation tool together with adoption of existing vehicle chassis and tyre models. A minimum-time optimisation criterion is chosen for the purpose of gaining an insight into at-the-limit manoeuvres, with the overall aim of finding improved fundamental principles for future active safety systems. The proposed method to trajectory generation is evaluated in time-manoeuvres using vehicle models established in the literature. We determine the optimal control solutions for three manoeuvres using tyre and chassis models of different complexities. The results are extensively analysed and discussed. Our main conclusion is that the tyre model has a fundamental influence on the resulting control inputs. Also, for some combinations of chassis and tyre models, inherently different behaviour is obtained. However, certain variables important in vehicle safety-systems, such as the yaw moment and the body-slip angle, are similar for several of the considered model configurations in aggressive manoeuvring situations.     

Unified decision-making and control for highway collision avoidance using active front steer and individual wheel torque control

ABSTRACT

Collision avoidance is a crucial function for all ground vehicles, and using integrated chassis systems to support the driver presents a growing opportunity in active safety. With actuators such as in-wheel electric motors, active front steer and individual wheel brake control, there is an opportunity to develop integrated chassis systems that fully support the driver in safety critical situations. Here we consider the scenario of an impending frontal collision with a stationary or slower moving vehicle in the same driving lane. Traditionally, researchers have approached the required collision avoidance manoeuver as a hierarchical scheme, which separates the decision-making, path planning and path tracking. In this context, a key decision is whether to perform straight-line braking, or steer to change lanes, or indeed perform combined braking and steering. This paper approaches the collision avoidance directly from the perspective of constrained dynamic optimisation, using a single optimisation procedure to cover these aspects within a single online optimisation scheme of model predictive control (MPC). While the new approach is demonstrated in the context of a fully autonomous safety system, it is expected that the same approach can incorporate driver inputs as additional constraints, yielding a flexible and coherent driver assistance system.     

基于驾驶员行为模拟的ACC控制算法

基于驾驶员最优预瞄加速度模型建立了一种适用于多种典型行驶工况的ACC控制算法。该算法采用基于多目标模糊决策方法的驾驶安全性、工效性、轻便性与合法性评价指标以及基于预瞄跟随理论的微分校正函数，描述了ACC控制系统对自由工况、跟随工况和切入工况等不同行驶条件及汽车动力学系统强非线性特性的考虑。     

应用模糊自适应PID和预瞄策略的自主车辆转向控制

文中结合智能车辆路径跟踪过程中转向控制方面的特点，提出了一种将模糊逻辑、预瞄规律和自适应PID控制相结合的控制策略，建立起了相应的模型，验证了该方法的可行性和有效性，并提出了进一步改进的方向。     

汽车主动悬架的最优预见控制

本文针对1/2车辆模型,应用最优预见控制理论对汽车主动悬架进行控制系统的设计和研究。计算机仿真结果表明,所提出的系统能有效改善汽车乘坐舒适性。     

Hierarchical optimisation on scissor seat suspension characteristic and structure

Scissor seat suspension has been applied widely to attenuate the cab vibrations of commercial vehicles, while its design generally needs a trade-off between the seat acceleration and suspension travel, which creates a typical optimisation issue. A complexity for this issue is that the optimal dynamics parameters are not easy to approach solutions fast and unequivocally. Hence, the hierarchical optimisation on scissor seat suspension characteristic and structure is proposed, providing a top-down methodology with the globally optimal and fast convergent solutions to compromise these design contradictions. In details, a characteristic-oriented non-parametric dynamics model of the scissor seat suspension is formulated firstly via databases, describing its vertical dynamics accurately. Then, the ideal vertical stiffness-damping characteristic is cascaded via the characteristic-oriented model, and the structure parameters are optimised in accordance with a structure-oriented multi-body dynamics model of the scissor seat suspension. Eventually, the seat effective amplitude transmissibility factor, suspension travel and the CPU time for solving are evaluated. The results show the seat suspension performance and convergent speed of the globally optimal solutions are improved well. Hence, the proposed hierarchical optimisation methodology regarding characteristic and structure of the scissor seat suspension is promising for its virtual development.     

Optimal preview game theory approach to vehicle stability controller design

Dynamic game theory brings together different features that are keys to many situations in control design: optimisation behaviour, the presence of multiple agents/players, enduring consequences of decisions and robustness with respect to variability in the environment, etc. In the presented methodology, vehicle stability is represented by a cooperative dynamic/difference game such that its two agents (players), namely the driver and the direct yaw controller (DYC), are working together to provide more stability to the vehicle system. While the driver provides the steering wheel control, the DYC control algorithm is obtained by the Nash game theory to ensure optimal performance as well as robustness to disturbances. The common two-degrees-of-freedom vehicle-handling performance model is put into discrete form to develop the game equations of motion. To evaluate the developed control algorithm, CarSim with its built-in nonlinear vehicle model along with the Pacejka tire model is used. The control algorithm is evaluated for a lane change manoeuvre, and the optimal set of steering angle and corrective yaw moment is calculated and fed to the test vehicle. Simulation results show that the optimal preview control algorithm can significantly reduce lateral velocity, yaw rate, and roll angle, which all contribute to enhancing vehicle stability.     

Road disturbance estimation for the optimal preview control of an active suspension systems based on tracked vehicle model

This research investigates stochastic estimation of a look-ahead sensor scheme using the optimal preview control for an active suspension system of a full tracked vehicle (FTV). In this scheme, wheel disturbance input to the front wheels are estimated using the dynamic equations of the system. The estimated road disturbance input at the front wheels are utilized as preview information for the control of subsequently following wheels of FTV. The design of optimal preview control is used as a classical linear quadratic Gaussian problem by combining dynamics of the original system and estimation of previewed road inputs. The effectiveness of the preview controller is evaluated by comparing the estimated information with the measured information for different road profiles, where Kalman filter is used for the state-variables estimation of the FTV. This research also considers the reduced order estimation using commonly available sensors in order to decrease the number of sensors and measurements. The simulation results’ using an active suspension system with different preview information shows that the proposed system can be beneficial for the improvement of ride comfort of tracked vehicles without using any specialized sensors for preview information calculation.     

A nonlinear model predictive control formulation for obstacle avoidance in high-speed autonomous ground vehicles in unstructured environments

This paper presents a nonlinear model predictive control (MPC) formulation for obstacle avoidance in high-speed, large-size autono-mous ground vehicles (AGVs) with high centre of gravity (CoG) that operate in unstructured environments, such as military vehicles. The term ‘unstructured’ in this context denotes that there are no lanes or traffic rules to follow. Existing MPC formulations for passenger vehicles in structured environments do not readily apply to this context. Thus, a new nonlinear MPC formulation is developed to navigate an AGV from its initial position to a target position at high-speed safely. First, a new cost function formulation is used that aims to find the shortest path to the target position, since no reference trajectory exists in unstructured environments. Second, a region partitioning approach is used in conjunction with a multi-phase optimal control formulation to accommodate the complicated forms the obstacle-free region can assume due to the presence of multiple obstacles in the prediction horizon in an unstructured environment. Third, the no-wheel-lift-off condition, which is the major dynamical safety concern for high-speed, high-CoG AGVs, is ensured by limiting the steering angle within a range obtained offline using a 14 degrees-of-freedom vehicle dynamics model. Thus, a safe, high-speed navigation is enabled in an unstructured environment. Simulations of an AGV approaching multiple obstacles are provided to demonstrate the effectiveness of the algorithm.     

Hydro-pneumatic Slow-active Suspension with Preview Control

In this work, the preview control problem is considered for fully active and hydro-pneumatic slow-active systems. Based on the quarter car model, linear optimal control theory is used to derive the control laws. The Pade approximation technique is used to represent the preview time resulting from a preview sensor mounted at the front bumper to measure the road irregularities ahead of the front wheels. The results for the slow-active system with preview showed that there is 15% improvement in ride comfort compared to slow-active without preview and 28.5% improvement over passive system at similar root mean square (r.m.s) dynamic tyre load and suspension working space. The performance gains are, however, lower by about 15% than those obtainable with the theoretically ideal, fully active system with preview. The power results for slow active with and without preview showed that a 2kW fixed displacement hydraulic pump is enough for full vehicle requirements.     

Output feedback H ∞/GH 2 preview control of active vehicle suspensions: a comparison study of LQG preview

This study concerns with multi-objective H _∞/GH ₂ preview control of active vehicle suspensions. This control scheme has two main aspects: first, it allows constrained outputs of the system to vary freely as long as they remain within their given bounds, in order that the best possible performance could be delivered. Secondly, the optimisation as well as constraint fulfilment is done for the worst-case road disturbances to cover all road types. To design a system to perform satisfactorily for a wide range of road irregularities, H _∞-norm is used wherever minimisation is required, and generalised H ₂-norm is used to care for the constraints on suspension working space. Moreover, to ensure desired stability margins for the system, pole location constraints are considered in the design. The proposed approach is evaluated on a quarter-car model and compared with the state-of-the-art preview control algorithm in the literature, namely, Linear quadratic Gaussian preview. Simulation results demonstrate the effectiveness of the proposed approach.     

Performance Index for a Preview Active Suspension Applied to a Quarter-Car Model

A simple and convenient matrix expression is derived for the performance index in the case of a linear vehicle model with two degrees of freedom and a preview active suspension, subject to a unit step road input and employing optimal control. The usual quadratic integral-type performance index is assumed and the effect of an additional form of constraint is described briefly. The effects of preview time on the performance index and the optimal feed-forward control are illustrated graphically for a particular example.     

Performance Index for a Preview Active Suspension Applied to a Quarter-Car Model

A simple and convenient matrix expression is derived for the performance index in the case of a linear vehicle model with two degrees of freedom and a preview active suspension, subject to a unit step road input and employing optimal control. The usual quadratic integral-type performance index is assumed and the effect of an additional form of constraint is described briefly. The effects of preview time on the performance index and the optimal feed-forward control are illustrated graphically for a particular example.     

Logical control approach to fuel efficiency optimization for commuting vehicles

A novel gearshift control approach for improving the fuel efficiency of the conventional commuting vehicles is addressed in this paper, where the optimization problem for gear control is formulated in the framework of stochastic logical dynamic system. By extracting the stochastic features of the driver acceleration intention in the specific route, the Markov process model is deduced and then applied for the optimization algorithm. Based on the logical system framework, the finite horizon optimization problem is solved by means of the algebraic expression of the dynamic programming algorithm with a lower computational complexity, thereby resulting in an optimal gearshift decision law in statistical sense. The software simulation and engine-in-the-loop based experiment results demonstrate the better fuel economy performance can be achieved by the proposed logic control scheme.