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摘要:
针对低地板有轨电车电子机械制动(EMB)系统压力传感器故障问题，提出一种强耦合条件下的无压力传感器制动力伺服控制策略。基于系统转矩特征曲线，提出一种不依赖于附加机械调节机构及压力检测装置的EMB间隙调整方法。同时，考虑系统制动和缓解过程中存在的“迟滞”特性，在EMB系统刚度特征曲线的基础上，提出一种强耦合条件下的制动力估算策略，与传统方法相比，其可有效地改善制动力的估计精度，能够作为备份制动方案，提高系统的可靠性。在此基础上，设计基于Sigmoid函数的改进型扩张状态观测器(ESO)对系统中的未建模部分与外界扰动进行估计与补偿，并将观测值前馈补偿至积分反步控制器，消除系统的观测误差，提高系统的鲁棒性。通过静态实验平台验证了所提控制策略的有效性。
Abstract:A clamping force sensorless servo control strategy under strong coupling conditions is proposed for low-floor trams with an electromechanical brake (EMB) system. Firstly, based on the torque characteristic curve of the system, an EMB clearance adjustment strategy is proposed, which does not depend on an additional mechanical adjustment mechanism and clamping force detection device. Considering the inherent hysteresis characteristics during braking and mitigation of the system, a braking force estimation method is also proposed under strong coupling conditions based on the stiffness characteristic curve of the EMB system. Compared with traditional control method, the proposed method can effectively improve the estimation accuracy of braking force and be used as a backup braking scheme to enhance the reliability of the system. In addition, an enhanced extended state observer (ESO) based on Sigmoid functions is designed to estimate and compensate the unmodeled parts and external disturbances in the system. The observed values are feedforward compensated to the integral backstepping controller to eliminate the observation errors of the system and improve the robustness of the system. Finally, the effectiveness of the proposed control strategy is verified through a static experimental platform.
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图 3 输出转矩分别与制动力和电机旋转角度关系曲线
Figure 3. Relations of output torque with braking force and rotation angle of motor
图 4 无压力传感器制动间隙调整流程
Figure 4. Flow chart of gap distance adjustment without pressure sensor
图 8 无压力传感器制动间隙调整实验曲线
Figure 8. Experimental curves of gap distance adjustment without pressure sensor
表 1 刚度模型拟合曲线系数表
Table 1. Coefficient of fitting curve of stiffness model
i $ {a_{5 - i}} $ $ {a_{4 - i}} $ $ {a_{3 - i}} $ $ {a_{2 - i}} $ $ {a_{1 - i}} $ 1 $ 7.49 \times {10^{ - 6}} $ $ - 5.88 \times {10^{ - 4}} $ $ 1.74 \times {10^{ - 2}} $ $ - 2.49 \times {10^{ - 1}} $ 2.49 2 $ - 1.55 \times {10^{ - 6}} $ $ 1.21 \times {10^{ - 4}} $ $ - 2.93 \times {10^{ - 3}} $ $ 4.62 \times {10^{ - 3}} $ 1.32 3 $ 1.44 \times {10^{ - 5}} $ $ - 1.14 \times {10^{ - 3}} $ $ 3.38 \times {10^{ - 2}} $ $ - 4.61 \times {10^{ - 1}} $ 3.51 
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