汽车车窗防夹数据的实验获取与分析

Experiments to Get and Analyse Anti-Pinch Data for Vehicle Windows

目前汽车上常用的防夹算法并没有考虑车辆使用时可能遇到的各种环境变化所带来的影响,导致车窗防夹功能在外界条件恶劣的情况下对障碍物误判或者感受不到障碍物,造成防夹功能失效。防夹算法发挥作用的前提是一个合理准确的防夹阈值,而防夹阈值的确定是以大量的实验研究为基础。针对以上问题,基于M atlab/S imu link和dSPACE实时仿真系统,设计防夹电动车窗控制系统的实验测试平台,实验周期长达一年,实现了一年中各种自然条件下的参数测量,保证实验数据的全面性、有效性,并对各个季节的数据进行综合分析比较,总结出外界条件对实验数据的影响规律,为防夹阈值的设置和防夹算法的改进提供依据。并利用幅值法实现的防夹功能,在马自达6和奥迪A6防夹车窗实验系统进行测试。

Now the anti-pinch algorithms commonly used in cars are not considered the impact of environmental change that vehicles may encountered, which led to anti-pinch system malfunction in the case of severe external conditions. A reasonable and accurate antipinch threshold plays an important role in algorithms, which is determined by a large number of experimental studies. For the above mentioned reasons, we design the experimental platform of anti-pinch system based on Matlab/Simulink and dSPACE real-time simulation system. The experiment lasted up to one year to achieve the measurements in the various natural conditions, ensuring the comprehensiveness and reliability of experimental data. Then data is analyzed comprehensively and summarized the relationship between experimental data and external conditions, which provided the basis for setting anti-pinch threshold and improving anti-pinch algorithms. Tests using amplitude method are run under Mazda 6 and Audi A6 experimental system.