电梯永磁电机曳引机速度性能优化控制研究

Speed Performance Optimization Control of Permanent Magnet Elevator Traction Machine

现行的电梯永磁曳引机大都或通过增加外围辅助硬件,或采用高精度的驱动装置来提高电梯运行舒适度。显然上述控制策略都增加了控制难度和制造成本。为了降低电梯制造成本,同时又不影响运行舒适度,提出了一种基于缓存选层信号优化的电梯转子转速估测策略。针对经典同步电机模型强耦合、高阶次及非线性等特征,导致卡尔曼滤波器存在求解难、滤波差等问题,建立新型的降阶扩展卡尔曼模型,简化求解过程,提高滤波效果。在用降阶卡尔曼滤波器估计转速时,引进遗传算法对其测量噪声和内部噪声分别优化处理,有效地降低滤波器对噪声的敏感性。通过将基于缓存选层信号优化的转速估测策略与经遗传算法优化的滤波器相结合,准确地估计出了转子转速、磁通角等关键信息,且能够在抱闸释放瞬间输出理想的电磁转矩,从而提高了乘梯舒适性。最后,在仿真结果部分验证了所提策略的有效性。

The existing elevator traction machine with permanent magnet synchronous motor （PMSM） mostly improve the comfort of elevator running either by increasing peripheral hardware or by using high precision driving device,it may increase the manufacturing cost.To reduce the manufacturing cost and not affect the comfort of the elevator running,a speed estimation based on buffered layer selection signal optimization strategy is proposed.For classical synchronous motor model existing strong coupling,higher-order and non-linear characteristics,its solution is difficult to obtain and filtering effect of the EKM is poor.In order to overcome these mismatches,a novel reduced-order EKM is used as the new filter.With reduced-order Kalman filter estimating speed,the genetic algorithm effectively reducing filter sensitivity is introduced to optimize the measurement noise and internal noise.Therefore,by combining the speed estimation based on buffered layer selection signal optimization strategy with the novel reduced-order EKM,the precise estimate information of the rotor speed and the flux angle can be obtained.Moreover,ideal electromagnetic torque generated by the motor can be quickly generated.So it can achieve superior riding comfort.Finally,simulation results indicate that the proposed section strategy is very effective and reliable.