基于EHB和EMB的复合制动系统特性分析及制动力控制研究

发布时间：2018-03-04 12:38

本文选题：EHB　切入点：EMB　出处：《吉林大学》2016年硕士论文　论文类型：学位论文

【摘要】：线控制动已经成为汽车制动系统研究和生产的主要方向,已经得到广泛的应用。比较成熟的线控制动系统有EHB和EMB,这两个制动系统有着各自的优点和局限性,当前,如何改进这两个系统是汽车制动一直领域关注的焦点,同时,机械-液压复合制动也成为最新的线控制动系统发展理念而被提出。本文提出了前轴为EHB,后轴为EMB的复合制动系统,此系统兼具两个系统的优势,同时弥补了两个系统的不足,是功能性更加优越的线控制动系统。本文首先分别对EHB系统和EMB系统进行机理分析并搭建相关的试验台架,其次对系统进行详细的特性测试,通过特性分析的结果分别对两个系统进行精确的制动力跟随控制算法研究,通过快速原型试验平台完成算法调试与验证;随后对复合制动系统进行前后轴制动力协调控制算法研究,提出制动力协调分配的控制策略,最后基于FlexRay网络以及Simulator搭建复合制动系统试验平台,并完成算法调试与验证。对于前轴EHB系统,本文首先对选定的HCU进行机理分析,其次进行特性测试,包括基频的选择、电磁阀线控区间的确定、高压蓄能器建压特性测试、电磁阀建压特性测试。根据特性分析结果,对系统进行制动力精确控制算法研究:首先使用压力、电流双闭环PID控制,随后使用模糊算法获得自整定的PID参数,最后对非线性特性进行前馈补偿控制。对于后轴EMB系统,本文先对系统进行机理分析,其次进行特性测试,进而对系统进行参数辨识,包括系统传动比、直流无刷电机力矩系数、转动惯量、刚度特性参数、摩擦特性参数,其中摩擦模型选用的是LuGre摩擦模型,通过遗传算法进行的参数辨识。根据参数辨识结果,对系统进行制动力精确控制算法研究,首先使用力、速度、电流、三闭环PID控制,随后使用模糊算法获得自整定的PID参数,最后对非线性特性进行优化补偿控制。最后,基于前后轴不同执行器特性进行制动力协调分配控制算法研究,在搭建的复合制动系统试验平台上进行实时的算法调试与验证。
[Abstract]:Wire controlled braking has become the main direction of automobile braking system research and production, and has been widely used. The more mature wire control braking system has EHB and Emb, which have their own advantages and limitations. At present, the two braking systems have their own advantages and limitations. How to improve the two systems has been the focus of attention in the field of automobile braking, at the same time, The mechanical-hydraulic compound brake has been put forward as the newest idea of the development of the wire control braking system. This paper puts forward the compound braking system with the front axle as the EMB and the rear axle as the EMB. This system has the advantages of the two systems and makes up for the deficiency of the two systems at the same time. This paper firstly analyzes the mechanism of EHB system and EMB system and sets up the related test-bed, and then carries on the detailed characteristic test to the system. According to the results of characteristic analysis, the precise braking force following control algorithm is studied, and the algorithm is debugged and verified by the rapid prototyping test platform. Then, the coordinated control algorithm of front and rear axle braking force is studied, and the control strategy of coordinated braking force distribution is put forward. Finally, the test platform of compound braking system is built based on FlexRay network and Simulator. For the front-axle EHB system, the mechanism of the selected HCU is analyzed firstly, and then the characteristics are tested, including the selection of the fundamental frequency, the determination of the electromagnetic valve line control section, the test of the built-up pressure characteristic of the high-voltage accumulator. According to the characteristic analysis results, the braking force precise control algorithm is studied: firstly, the pressure and current are controlled by double closed-loop PID, then the self-tuning PID parameters are obtained by using fuzzy algorithm. Finally, feedforward compensation control for nonlinear characteristics is carried out. For the rear axle EMB system, the mechanism of the system is analyzed first, then the characteristics are tested, and then the system parameters are identified, including the transmission ratio of the system. The torque coefficient, moment of inertia, stiffness characteristic parameter and friction characteristic parameter of brushless DC motor are selected. The friction model is LuGre friction model, which is identified by genetic algorithm. The braking force precise control algorithm is studied. First, the force, speed, current and three closed-loop PID control are used, then the self-tuning PID parameters are obtained by using fuzzy algorithm. Finally, the nonlinear characteristics are optimized and compensated. Based on the characteristics of different actuators of front and rear shafts, the control algorithm of coordinated distribution of braking force is studied, and the algorithm is debugged and verified in real time on the test platform of compound braking system.
【学位授予单位】：吉林大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：U463.5

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