面向主动安全的预紧式安全带控制策略研究

发布时间：2018-07-29 07:44

【摘要】：随着我国机动车保有量的飞速增长,人类对交通安全问题的重视程度也愈来愈高,被动安全技术作为传统的安全技术领域已无法满足人类对行车安全的需要,在这样的背景下,主动安全技术领域已被越来越多的人关注。汽车安全带约束系统作为应用最早的汽车被动安全技术,在减轻驾乘人员受损程度方面起着重要的作用,但由于传统式汽车安全带并不具有主动预警和预紧的功能,因此在主动安全技术领域内对传统安全带约束系统的探索意义十分重大。本文所设计的面向主动安全的预紧式安全带集提前预警、主动预紧和限力三大功能于一体,打破了作为被动安全技术的传统安全带系统的局限性,以主动安全技术的姿态及时预测事故的发生并采取主动措施,更有效的保护驾乘人员的生命财产安全。本文研究了面向主动安全的预紧式安全带控制技术。系统的主控芯片是Freescale公司研发的16位MC9S12DP256单片机,预紧信号主要包括超声波测距传感器测得的距离信号和制动踏板力传感器测得的制动信号,而系统控制的反馈信号则是霍尔式电流传感器采集的电机电枢电流信号。采用BP神经网络PID算法对该反馈信号进行恒电流控制,更好实现系统控制功能。本文基于Matlab/Simulink软件对BP神经网络PID的控制性能进行了仿真,并根据仿真结果对传统火药预紧式安全带的机械结构进行设计改造。同时,为了验证控制策略的实际可行性,本文设计制作了基于MC9S12DP256的控制器硬件电路,试制了一套样机,并搭建了预紧式安全带试验台。仿真和试验表明:BP神经网络的PID控制具有较好的跟随性,抗干扰性和鲁棒性,控制性能优于传统PID控制,能够满足实时控制的要求;面向主动安全的预紧式安全带具备提前预警功能,并且通过控制驱动电机来带动安全带卷收器的卷轴卷收,实现对织带的控制,达到主动预紧的目的。系统在预紧的同时还能对安全带织带张力的大小进行控制,避免因织带过紧对驾乘人员造成伤害,起到限力的作用,满足主动安全的保护需求。
[Abstract]:With the rapid growth of the number of motor vehicles in China, people pay more and more attention to traffic safety problems. Passive safety technology, as a traditional field of safety technology, has been unable to meet the needs of human traffic safety. Active safety technology has been paid more and more attention. As the earliest passive safety technology, seat belt restraint system plays an important role in reducing the damage to drivers. However, the traditional seat belt does not have the function of active warning and pre-tightening. Therefore, it is very important to explore the traditional seat belt restraint system in active safety technology. In this paper, the pre-fastening seat belt designed for active safety has three functions: early warning, active preloading and limiting force, which breaks the limitation of traditional seat belt system as passive safety technology. The active safety technology is used to predict the accident in time and take active measures to protect the safety of the driver's life and property more effectively. In this paper, the control technology of pre-fastening seat belt for active safety is studied. The main control chip of the system is a 16-bit MC9S12DP256 microcontroller developed by Freescale Company. The pre-tightening signal mainly includes the distance signal measured by the ultrasonic ranging sensor and the braking signal measured by the brake pedal force sensor. The feedback signal of the system is the armature current signal collected by Hall current sensor. The PID algorithm of BP neural network is used to control the feedback signal with constant current, and the control function of the system is better. In this paper, the control performance of BP neural network PID is simulated based on Matlab/Simulink software, and the mechanical structure of the traditional gunpowder prefastening seat belt is designed and modified according to the simulation results. At the same time, in order to verify the feasibility of the control strategy, the hardware circuit of controller based on MC9S12DP256 is designed and manufactured, a set of prototype is produced, and a pre-tightening seat belt test-bed is built. The simulation and experiment show that the PID control of the BP neural network has better following performance, anti-interference and robustness, and the control performance is better than the traditional PID control, and can meet the requirements of real-time control. The pre-fastening seat belt for active safety has the function of early warning, and can drive the reel of the belt reel by controlling the driving motor, so as to realize the control of the belt and achieve the purpose of active pre-tightening. At the same time, the system can control the tension of the belt, avoid the damage caused by the belt too tight to the driver, play the role of limiting force, and meet the need of active safety protection.
【学位授予单位】：天津职业技术师范大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：U491.61

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