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Robust Fault Detection Algorithm for the Smart Anti-pinch Window of Pure Electric Vehicles

机译:纯电动汽车智能防夹死窗的鲁棒故障检测算法

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In order to effectively solve the risk of safety on power window, an improved pinch detection algorithm based on the fault detection observer estimation is proposed for an anti-pinch window control system. In designing a residual generator, the proposed fault detection algorithm makes use of the pinch torque rate information by establishing the mathematical model of DC, considered as a fault under the pinched condition. By comparing the residual signal with the pre-designed threshold, the occurrence of pinch is detected. The fault detection observer takes into account robustness against disturbances and sensitivity to faults, simultaneously, both of which are regarded as optimization problems. In this study, the mixed H-/H∞ performance index and reference model fault detection method are advanced to solve the optimization problem in the Linear Matrix Inequality (LMI) which transforms a mathematical problem. The simulation results of the detection time obtained from the two methods are 0.15 and 0.07s, respectively, proving that the use of the fault detection algorithm is effective for an anti-pinch window. The co-simulation based on CANoe-MATLAB is proposed to verify the algorithm again. Moreover, under the premise of strong robustness, the reference model method is superior to the mixed H-/H∞ performance.
机译:为了有效解决电动车窗安全隐患,提出了一种基于故障检测观察者估计的改进的捏防车算法。在设计残差发电机时,所提出的故障检测算法通过建立被认为是在挤压条件下的故障的直流数学模型来利用挤压扭矩率信息。通过将残留信号与预先设计的阈值进行比较,可以检测到夹点的发生。故障检测观察器同时考虑了对干扰的鲁棒性和对故障的敏感性,这两者均被视为优化问题。为了解决线性矩阵不等式(LMI)中的优化问题,提出了一种混合的H- /H∞性能指标和参考模型故障检测方法,以解决数学问题。通过这两种方法获得的检测时间的仿真结果分别为0.15和0.07s,证明使用故障检测算法对防夹窗口是有效的。提出了基于CANoe-MATLAB的协同仿真算法。此外,在强鲁棒性的前提下,参考模型方法优于混合H- /H∞性能。

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