汽车智能化和网联化的发展将导致以数据融合和集成化控制为特征的新型智能底盘电子架构出现。通过底盘多系统的数据融合和冗余控制，可以实现更安全、更舒适、更智能的车辆动力学控制。本课题研究聚焦于线控制动系统的制动动力学研究，通过底盘多系统的数据融合，对车辆关键状态参数进行准确预估，基于线控制动系统实现高品质的制动动力学和高冗余的制动稳定性控制。首先，针对课题研究需求，建立基于电子助力器和防抱死制动系统的十五自由度车辆动力学非线性数学模型，主要包括汽车动力学整车模型、线控制动系统模型、轮胎模型和驾驶员模型。为后续研究提供了良好的仿真平台。其次，针对传统制动系统无法配合智能汽车实现主动制动、精准压力控制和快速压力调整的问题，自主研发了一款电子助力制动系统。基于负载扰动前馈的滑模变结构控制算法，实现对底层驱动电机的控制。基于变增益PID控制算法，以目标压力位调度变量和目标压力控制频率为增益变量，实现电子助力制动系统对制动主缸压力的精准控制与快速调整。再次，针对制动临停工况车辆纵向振动幅值较大和舒适性较差的问题，基于模型预测控制算法，实现制动过程纵向减速度的准确观测。基于模糊推理控制算法实现驾驶员制动意图识别。以保证制动强度和制动安全为约束条件，改善制动临停舒适性为控制目标，基于滑模变结构控制算法，提出一种纵向减速度控制算法和安全控制策略，实现车辆制动临停阶段舒适性提升。此外，针对传统汽车车辆稳定性控制系统存在失效风险、关键参数估计偏差较大、难以满足智能汽车高冗余的制动安全控制需求等问题，以电子助力器为作动机构，构建了一种综合考虑底盘多系统数据融合、关键状态参数准确估计的冗余ABS控制算法和安全控制策略，实现了智能汽车高冗余的制动稳定性控制。最后，基于哈弗H6进行试验平台车改装，搭载线控制动、线控转向和线控驱动系统，使其具备自动驾驶试验能力。在特定工况下完成基于线控制动系统的制动动力学控制算法验证。实车试验表明，所开发的线控制动系统，可以搭载整车实现精准快速的制动压力控制。所提出的基于线控制动系统的制动临停舒适性控制，可以在保证制动安全的前提下，大幅提高制动舒适性。所提出的基于线控制动系统的冗余ABS控制算法和安全控制策略能够有效协同整车达到冗余ABS控制的目的，智能汽车在制动过程中的稳定性和冗余安全性得到大幅提升。
The development of intelligent and networked vehicle brings out a new intelligent classis electronic architecture featured with data fusion and integrated control. The data fusion and redundancy control of the classis multiple system can realize safer, more comfortable and more intelligent vehicle dynamics control. This study focuses on braking dynamics of the linear control system to accurately predict key state parameters of vehicles through data fusion of the classis multiple system and achieve high-quality braking dynamics and high-redundancy braking stability control based on the linear control system.To start with, according to research needs, nonlinear mathematical models of 15 dof vehicle dynamics are established based on the electronic booster and the anti-lock braking system, including the vehicle dynamics model, the linear control system model, the tire model and the driver model, which provides a favorable simulation platform for follow-up studies.Then, an electronic power assisted braking system is developed independently aiming at the problem that the traditional braking system cannot coordinate with intelligent vehicles to realize active braking, precise pressure control and rapid pressure adjustment. The sliding mode variable structure control algorithm based on load disturbance feedforward is applied to realize control on the underlying driving motor. The PID control algorithm based on variable-gain is used to realize accurate control and rapid adjustment of the electronic power braking system on the master cylinder pressure by taking target pressure level scheduling variables and target pressure control frequency as gain variables.Further, in regard with large amplitude of longitudinal vibration and poor comfort of braking vehicles in stopping condition, the predictive control algorithm based on models is adopted to realize accurate observation of longitudinal deceleration in braking process. And the fuzzy reasoning control algorithm is used to identify drivers’ braking intentions. Based on the sliding mode variable structure control algorithm, a longitudinal deceleration control algorithm and a safety control strategy are proposed by taking guaranteeing braking strength and safety as the constraint conditions and improving temporary comfort as the control objective to enhance the comfort of vehicles in the braking condition. In addition, aiming at the failure risk existed in stability control of traditional vehicles, on the basis of data fusion of the intelligent vehicle multiple system, a redundant ABS control algorithm and a safety control strategy based on master cylinder pressure adjustment are proposed by taking the electronic booster as the actuating mechanism to realize the high-redundancy braking stability control of intelligent vehicles. Finally, the test platform car is modified based on Haval H16, which is equipped with brake-by-wire, steer-by-wire and the wire drive system to have automatic driving test capability. The braking dynamics control algorithm validation based on the linear control system is completed under certain conditions. The real vehicle test indicates that the developed linear control system can help the loaded vehicle to achieve accurate and fast braking pressure control. The proposed braking comfort control based on the linear control system can greatly improve braking comfort at the time of guaranteeing braking safety. The proposed redundant ABS control algorithm sand the safety control strategy based on the linear control system can effectively coordinate with the full vehicle to achieve redundant ABS control. The stability and redundancy safety of intelligent vehicles are greatly improved in the braking process.
