基于卡尔曼滤波的线控汽车转向操纵稳定性关键问题研究

The project uses the variable steering ratio of steer-by-wire vehicle design. Currently steer-by-wire system is lack of active safety, handling stability, and driving feel clearly. By exploring the simulation of driver touch and the closed-loop feedback control of steer-by-wire steering, it will make the vehicle steering easily, smoothly, safety. First, based on four-wheel-five-degrees of vehicle dynamic model and complexity of tire model, to use DEKF estimation algorithm, for the first time, we can accurately estimate the state of the vehicle and the friction of road surface which are difficult to measure. That can ensure the steering more accurate and effectively. Second, to combine with vehicle status and road parameters, we use threshold method to judge the driver's intention to design the force of steering torque. That will improve active safety and the clarity of driving feel. At the same time, based on the structure and the control of steer-by-wire system, and compared with steady control, a closed-loop feedback steering control method of dynamic steer-by-wire vehicle is proposed. Using the weighting method of vehicle status and road parameters and ARIMA for judging the steering intention of driver, a multi- loop feedback control algorithms is built. That makes the steering efficient and reliable. Finally, we will develop a set of closed-loop control system of steer-by-wire vehicle which can be applied to the real car. The project is intended to solve the main problems in steer-by-wire system, providing theoretical and practical basis for practical applications.

本项目采用汽车线控转向变传动比设计理念，针对当前线控转向系统缺乏主动安全性、操纵稳定性、路感不明确等问题，探索驾驶员触感模拟和线控转向闭环反馈控制方法，以满足车辆转向易操纵、平稳、安全的需求。首先以四轮五自由度车辆动力学模型和复杂轮胎模型为基础，利用DEKF仿真估计算法，首次实现难以测量的车辆状态参数和路面附着系数的准确估算，确保线控转向控制更精确、有效；其次综合车辆状态和路面参数，提出利用门限阈值法判断驾驶员意图，设计触感系统方向盘扭矩力调整模型，提高转向主动安全性和路感明确性；同时基于线控转向的结构和控制机理，提出以稳态控制为基础的瞬态转向多层闭环反馈控制策略，采用车辆状态和路面参数权重法与驾驶员转向意图ARIMA判断法相结合的方式，保证汽车转向有效、可靠；最后研发出一整套应用于实车的线控转向人—车闭环控制系统。本项目意在解决线控转向系统的主要问题，为实际应用提供理论和实践依据。

本项目根据转向控制策略与信息融合理论，采用双重扩展卡尔曼滤波技术，实现了对线控汽车的转向控制和运动状态与路面附着系数的精确估计，并经过了试验台的验证。论文的主要研究工作如下。.1、线控汽车转向控制控制策略研究.利用转向传动比的改变来保证横摆角速度对方向盘转角的增益始终为一个定值，加入了具有摆角速度和侧向加速度的反馈转向控制策略，分别在不同路面附着系数下进行了验证。试验结果证明，采用固定横摆角速度增益和横摆角速度与侧向加速度反馈控制，能提高线控汽车的操纵性和稳定性，降低驾驶员的负担。.2、信息融合技术在线控汽车状态参数和路面附着系数估计算法中的应用.建立在三自由度车辆动力学模型上，采用HSRI轮胎模型的双重扩展卡尔曼滤波不但能精准地估算出车辆的状态参数，而且还可以实时估算出轮胎与路面的附着系数。在双重扩展卡尔曼滤波中包含状态与参数两个递推估算模型，两部分并行存在，互相依存，实时交互校正预测信息，能快速趋向仿真估算的真值。.3、线控汽车仿真试验台软、硬件设计.本项目建立了线控汽车仿真试验台，试验台由软、硬件两部分组成。其中软件包括：实时运算的转向动力模型、数据采集系统和控制调用程序；硬件包括：实车线控转向系统、驾驶员操作系统、仪表显示模拟系统等。整个试验台是一个人——车硬件在环仿真平台，在其上可以无危险地进行任何极限工况的实验。为实车场地试验做了充分的前期准备工作。.4、线控汽车状态参数和路面附着系数估计算法验证.结合前面信息融合技术的理论建模，分别在线控汽车仿真试验台和实车场地试验上给予验证。在试验台上，利用Carsim车辆动力学模型与matlab下搭建的Simulink状态估计仿真模型，实时交互车辆状态信息，进行车辆与路面状态的估计，试验台试验结果表明，所采用的算法能够精确估算车速、质心侧偏角和路面附着系数等状态参数。利用实车场地试验数据，同样验证了估算算法的有效性和准确性。