现代控制理论在汽车防抱制动系统中的应用

汽车防抑制动系统常采用以下三种控制方式：逻辑门限值控制、最优控制及滑动变结构控制。最优控制是基于状态空间法的现代控制理论方法，它可以根据车辆－路面系统的数学模型，用状态空间的概念，在时间域内研究汽车防抱制动系统。它是一种基于模型的分析型的控制系统，它根据防抱制动系统的各项控制要求，按最优化原理求得控制系统的最优控制指标。具体来讲，它将车轮的角速度和角加速度作为状态变量对系统进行优化控制，能达到很好     

驾驶员最优预瞄纵向加速度模型

利用预瞄跟踪理论、模糊决策理论和非线性系统描述函数法建立了一个驾驶员速度控制模型，即加强员最优预瞄纵向加速度模型，仿真结果表明，该模型通过对驾驶安全性、合法性、轻便性、驾驶员自身滞后特性及汽车动力学系统强非线性特性的考虑，可以有效地模拟驾驶员控制汽车速度的行为特性，为人-车-路闭环系统中速度控制研究提供了一条可行途径。     

驾驶员统计特性对人—车闭环系统响应的影响与汽车主动安全性评价

基于预瞄跟随理论，本文应用一般随机摄动法，对考虑驾驶员不确定性的人－车闭环系统进行响应分析，结合实例，说明该方法在汽车主动安全性评价中的应用。     

模糊控制理论在驾驶员—汽车—环境闭环系统操纵稳定性研究中的应用

本文采用模糊控制理论方法，对驾驶员－汽车－环境闭环系统的操纵稳定性进行了研究，建立了驾驶员智能模型，研制了整个闭环系统的仿真软件，模拟了几种典型工况的汽车运行，试验证明闭环系统模型合理，仿真结果正确。     

汽车传动夭最优匹配评价指标的探讨

本文探讨了汽车动力传动系统最优匹配的评价指标，提出了动力性发挥程度的评价指标－驱动功率损失率，经济性发挥程度的评价指标－有效效率利用率、用能量效率指标来统一汽车性与燃油经济性指标，并以上述三个指标作为动力传动系统最优匹配的评价指标。     

基于改进全局优化算法的轮毂液压动力系统能量管理策略

现有针对轮毂液压混合动力系统的能量管理策略均为结合研究人员经验与发动机最优工作区域的简单控制，暂未见优化控制策略的应用，导致实际控制值与最优控制值的偏差较大，无法充分发挥该系统的节油能力。基于此，针对该系统提出了一种基于改进全局优化算法的能量管理策略，探寻该系统的理论最大节油量，进一步挖掘该系统的节能潜力。首先，该策略建立了基于车速-蓄能器荷电状态（SOC）自适应调节等效油耗因子的方法计算目标函数中的罚函数，从而提高系统的制动回收能力，避免计算结果陷入局部最优；随后，根据轮毂液压混合动力系统各模式工作点相对固定的特性，实现了控制变量降维；最后以实测数据进行了仿真测验。结果显示：比起传统的全局最优策略，该方法可以进一步实现3.36%的节油效果；同时，在实现节油的基础上，经过控制变量降维后计算时间减少了35%，而计算精度基本不受影响。     

键图理论在汽车制动驱动系统动态模拟中的应用研究

分析了键图理论的特点及发展概况，论述了键图理论在汽车制动驱动系统动态仿真中的应用，建立了汽车气压制动驱动系统中阀类元件和管路等键图模型库，为制动驱动系统的动态仿真及控制研究提供了理论基础。     

汽车四轮转向系统的H2/H∞混合控制

为使汽车四轮转向系统具有良好的鲁棒性和干扰抑制性能，针对外界干扰，对汽车四轮转向系统模型进行了分析，并将其转化为H2／H∞控制问题，运用Matlab的LMI控制工具箱设计了H2／H∞混合最优控制器。仿真结果表明，设计的最优控制器具有良好控制效果。     

四轮转向汽车自适应模型跟踪控制研究

使用单点预瞄驾驶员模型，针对确定性汽车模型探讨了４ＷＳ汽车在单移线行驶过程中后轮的最优转向控制规律。通过引入状态反馈，改善了整车的转向特性，将实际汽车的前后轮胎侧刚度及外界干扰视为有界的不确定性参数，采用自适应模型跟踪变结构控制方法，使得不确定的实际汽车模型能够很好地跟踪确定的最优理论模型，仿真结果表明该方法的可行性，控制系统能够有效地克服参数摄动及外界干扰对系统稳定性的影响。     

智能网联环境下的混合动力汽车分层能量管理

为实现混合动力汽车的实时最优能量管理,提出一种基于智能网联的分层能量管理控制方法。上层控制器利用交通信号灯正时求解目标车速的范围,而采用快速模型预测控制(F-MPC)算法预测给定时间窗口内的最优目标车速序列。下层控制器根据最优目标车速序列,利用基于威兰斯线方法的等效燃油消耗最小策略(WLECMS)进行混合动力汽车能量管理。硬件在环试验结果表明,所提出的基于智能网联的上层控制器可避免混合动力汽车红灯停车,而F-MPC可实现与MPC相近的最优车速预测和燃油经济性,且每一时间步长的计算时间可缩短到MPC的7.2%;WL-ECMS可实现良好的车速跟随,百公里油耗与ECMS相当,且每一时间步长的计算时间可缩短到ECMS的1.48%。     

On the achievable performance using variable geometry active secondary suspension systems in commercial vehicles

There is a need to further improve driver comfort in commercial vehicles. The variable geometry active suspension offers an interesting option to achieve this in an energy efficient way. However, the optimal control strategy and the overal performance potential remains unclear. The aim of this paper is to quantify the level of performance improvement that can theoretically be obtained by replacing a conventional air sprung cabin suspension design with a variable geometry active suspension. Furthermore, the difference between the use of a linear quadratic (LQ) optimal controller and a classic skyhook controller is investigated. Hereto, an elementary variable geometry actuator model and experimentally validated four degrees of freedom quarter truck model are adopted. The results show that the classic skyhook controller gives a relatively poor performance while a comfort increase of 17–28% can be obtained with the LQ optimal controller, depending on the chosen energy weighting. Furthermore, an additional 75% comfort increase and 77% energy cost reduction can be obtained, with respect to the fixed gain energy optimal controller, using condition-dependent control gains. So, it is concluded that the performance potential using condition-dependent controllers is huge, and that the use of the classic skyhook control strategy should, in general, be avoided when designing active secondary suspensions for commercial vehicles.     

Control and evaluation of active suspension for MDOF vehicle model

The current method for solving the problem of active suspension control for a vehicle often uses a quarter car or a half car model. This kind of model is not suitable for practical applications. In this paper, based on considering the influence of factors such as the engine, seat and passengers, a MDOF (multi-degree-of-freedom model) describing the vehicle motion has been set up, and a controller for this model is designed by using LQ control theory. Furthermore the appropriate control scheme is selected by testing various performance indexes.     

A control strategy for parallel hybrid electric vehicles based on extremum seeking

An energy management control strategy for a parallel hybrid electric vehicle based on the extremum-seeking method for splitting torque between the internal combustion engine and electric motor is proposed in this paper. The control strategy has two levels of operation: the upper and lower levels. The upper level decision-making controller chooses the vehicle operation mode such as the simultaneous use of the internal combustion engine and electric motor, use of only the electric motor, use of only the internal combustion engine, or regenerative braking. In the simultaneous use of the internal combustion engine and electric motor, the optimum energy distribution between these two sources of energy is determined via the extremum-seeking algorithm that searches for maximum drivetrain efficiency. A dynamic programming solution is also obtained and used to form a benchmark for performance evaluation of the proposed method based on extremum seeking. Detailed simulations using a realistic model are presented to illustrate the effectiveness of the methodology.     

智能分布式驱动汽车路径跟踪/制动能量回收协同控制策略研究

为了解决智能分布式驱动汽车路径跟踪与制动能量回收系统间的协同控制难题,充分考虑分布式驱动汽车四轮扭矩独立可控在智能驾驶系统中的优势,设计适应不同路面附着条件的智能分布式驱动汽车转向、制动分层协同控制策略。上层控制器依据不同的路面类型设计差异化的多目标代价函数,以综合优化各工况下的控制目标。高附路面下,制定满足最大能量回收值的全局参考车速,在线优化路径跟踪指令,实现最优能量回收的同时减小系统运算负荷;低附路面下,优先考虑车辆的路径跟踪性能和行驶稳定性,在多目标代价函数中取消对全局参考车速的跟随要求,增设终端速度约束与能量回收项性能指标并减小能量回收项性能指标的权重系数。上层控制器基于模型预测控制方法对多目标代价函数进行滚动优化与预测求解,得到期望的前轮转角及4个车轮的总制动扭矩需求。下层控制器根据制动扭矩需求对四轮的液压制动扭矩和电机制动扭矩进行分配,最终完成整个复合制动过程。基于MATLAB/Simulink和CarSim软件,搭建控制器在环仿真平台,并在高附和低附路面条件下对所提出的策略进行试验验证。研究结果表明：高附路面下,所提出的控制策略在准确跟踪期望路径的同时相较固定比例制动力分配方法可提升2.7%的能量回收值并减少约0.02 s的单次计算时间;低附路面下,与使用高附控制策略相比,能够保证车辆的路径跟踪准确性与行驶稳定性,同时可提升7.8%的能量回收值;控制器在环试验结果证明了该协同控制策略对车辆性能提升的有效性。     

Designing a non-linear tracking controller for vehicle active suspension systems using an optimization process

In this paper, a new non-linear tracking controller for vehicle active suspension systems is analytically designed using an optimization process. The proposed scheme employs a realistic non-linear quarter-car model, which is composed of a hardening spring and a quadratic damping force. The control input is the external active suspension force and is determined by minimizing a performance index defined as a weighted combination of conflicting objectives, namely ride quality, handling performance and control energy. A linear skyhook model with standard parameters is used as the reference model to be tracked by the controller. The robustness of the proposed controller in the presence of modeling uncertainties is investigated. The performed analysis and the simulation results indicate that both vehicle ride comfort and handling performance can be improved using the minimum external force when the proposed non-linear controller is engaged with the model. Meanwhile, a compromise between different objectives and control energy can easily be made by regulating their respective weighting factors, which are the free parameters of the control law.     

A Comparison of Alternative Obstacle Avoidance Strategies for Vehicle Control

In Alleyne (1996) several vehicle control options were considered for Unintended Roadway Departure (URD) prevention and conclusions were drawn as to the efficacy of each method. This companion paper investigates the use of several different inputs for the control of a vehicle, in the context of Obstacle Avoidance for autonomous vehicles. In this investigation, the goal of the controller is to provide an intervention in the event of the vehicle detecting an obstacle in its path. The five types of inputs that will be considered are (i) Four Wheel Steering; (ii) Front Wheel Steering; (iii) Four Wheel Brake Steering; (iv) Front Wheel Brake Steering; and (v) Rear Wheel Brake Steering. The controller design is an LQ controller based on the simplified dynamics of a 2 degree of freedom bicycle model. However, the analysis of the different strategies are performed on a more complete, nonlinear vehicle model. A key contribution of this paper is the quantitative evaluation of the relative efficiencies of each of these input strategies being examined. Unlike most control schemes, an important metric of performance is the ratio of peak tire force used versus available tire force. The conclusions reached in this paper shed additional light on appropriate input actuator methods for vehicle guidance and control.     

A Comparison of Alternative Obstacle Avoidance Strategies for Vehicle Control

SUMMARY

In Alleyne (1996) several vehicle control options were considered for Unintended Roadway Departure (URD) prevention and conclusions were drawn as to the efficacy of each method. This companion paper investigates the use of several different inputs for the control of a vehicle, in the context of Obstacle Avoidance for autonomous vehicles. In this investigation, the goal of the controller is to provide an intervention in the event of the vehicle detecting an obstacle in its path. The five types of inputs that will be considered are (i) Four Wheel Steering; (ii) Front Wheel Steering; (iii) Four Wheel Brake Steering; (iv) Front Wheel Brake Steering; and (v) Rear Wheel Brake Steering. The controller design is an LQ controller based on the simplified dynamics of a 2 degree of freedom bicycle model. However, the analysis of the different strategies are performed on a more complete, nonlinear vehicle model. A key contribution of this paper is the quantitative evaluation of the relative efficiencies of each of these input strategies being examined. Unlike most control schemes, an important metric of performance is the ratio of peak tire force used versus available tire force. The conclusions reached in this paper shed additional light on appropriate input actuator methods for vehicle guidance and control.     

A Comparison of Alternative Intervention Strategies for Unintended Roadway Departure (URD) Control

This paper investigates the use of several different inputs for the control of a vehicle, in the context of URD. In this investigation, the goal of the URD controller is to provide an intervention in the event of the vehicle leaving the road. The types of inputs that will be considered are (i) Four Wheel Steering, (ii) Front Wheel Steering, (iii) Four Wheel Brake Steering, (iv) Front Wheel Brake Steering, and (v) Rear Wheel Brake Steering. The controller design is an LQ controller based on the simplified dynamics of a 2 degree of freedom bicycle model. However, the analysis of the different strategies are performed on a 7 degree-of-freedom nonlinear vehicle model. The key contribution of this paper is the quantitative evaluation of the relative efficiencies of each of these input strategies being examined. Unlike most control schemes, the performance measure to be used will not be the output tracking error of the system. Instead, the metric of performance is the ratio of peak tire force used versus available tire force or, in other words, the actuator response relative to the maximum available actuator capability.     

考虑发动机起停优化的PHEV能量管理策略

针对某新型双电机行星耦合插电式混合动力汽车(PHEV)中发动机在起停及怠速运行状态下会导致油耗增加的问题,基于等效燃油消耗最小能量管理策略,加入发动机起停优化控制模块,以进一步改善整车燃油经济性。建立了整车动力学和传动模型并加入发动机起停优化控制模块,对ECMS能量管理策略输出的发动机及电机最优目标转矩进行重新优化分配后,再输出给发动机及电机控制器以控制其工作状态。针对起停优化控制中影响起停频次的关键时间参数,采用粒子群优化算法对其进行优化。仿真结果表明,相比优化前,所提出的能量管理优化策略能够实现对发动机起停或怠速状态的有效控制,减少发动机的起停频次,减少恶化油耗,验证了本文所提出的能量管理优化策略能够进一步优化整车燃油经济性。     

A novel vehicle dynamics stability control algorithm based on the hierarchical strategy with constrain of nonlinear tyre forces

Direct yaw moment control (DYC), which differentially brakes the wheels to produce a yaw moment for the vehicle stability in a steering process, is an important part of electric stability control system. In this field, most control methods utilise the active brake pressure with a feedback controller to adjust the braked wheel. However, the method might lead to a control delay or overshoot because of the lack of a quantitative project relationship between target values from the upper stability controller to the lower pressure controller. Meanwhile, the stability controller usually ignores the implementing ability of the tyre forces, which might be restrained by the combined-slip dynamics of the tyre. Therefore, a novel control algorithm of DYC based on the hierarchical control strategy is brought forward in this paper. As for the upper controller, a correctional linear quadratic regulator, which not only contains feedback control but also contains feed forward control, is introduced to deduce the object of the stability yaw moment in order to guarantee the yaw rate and side-slip angle stability. As for the medium and lower controller, the quantitative relationship between the vehicle stability object and the target tyre forces of controlled wheels is proposed to achieve smooth control performance based on a combined-slip tyre model. The simulations with the hardware-in-the-loop platform validate that the proposed algorithm can improve the stability of the vehicle effectively.