Noninteracting optimal and adaptive torque control using an online parameter estimation with help of polynomials in EKF for a PMSM.

Tanja Zwerger, Paolo Mercorelli
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Abstract

This paper addresses a non-interacting torque control strategy to decouple the d- and q-axis dynamics of a permanent magnet synchronous machine (PMSM). The maximum torque per ampere (MTPA) method is used to determine the reference currents for the desired torque. To realize the noninteracting control, knowledge concerning the inductances Ld and Lq of the electrical machine is necessary. These two inductances are estimated by two extended Kalman filters (EKFs), which use a univariate polynomial as a model to describe the saturation effects of the PMSM. The Kalman filters (KF) are realized within a noninteracting control system to improve the observability of the inductance. Despite the non-perfect decoupling, thanks to the structural stochastic nature of the KFs, noninteracting cancellation errors are represented with its process noise and the inductances are estimated sufficiently well. In this sense, we can speak about KFs for and within noninteracting control. Estimating inductances is fundamental for optimal torque control, which is a viable approach to reducing mechanical vibration and disturbance. Moreover, the control strategy of model-based techniques must be adaptively tuned to work properly. Starting from the existing literature, a viable control structure is proposed in which the stability of the control loop using a Proportional Integral (PI) controller is shown for the resulting time-varying system. In fact, the model is represented as a time-varying system because of the presence of the variable inductances Ld and Lq and because of the presence of the velocity of the rotor which is not considered as a state. In this paper, a forward Euler discretization is used to realize the observer in the discrete experimental setup. Measures realized with hardware in the loop (HIL) show interesting results in the context of inductance estimation, due to the advantage of the reduction of the dimensions of the two decoupled EKFs resulting from the noninteraction control. Using the HIL simulator, the proposed torque control strategy is investigated, showing promising results in terms of increasing observability due to decoupling. This and the usage of univariate polynomials in EKF calculations lead to significant reduction of measurement points, reduction of oscillations and ripples, deviation between desired and achieved torque and reduction of disturbances. Moreover, the proposed control strategy using a very limited calculation load, at the same time, maintains the ripples inside the technical limits of the obtained torque. Both effects are due to the decoupled EKFs with simplified and reduced order of the models using univariate polynomials, which require significantly fewer measuring points in the run-up to the creation of the model of the inductances Ld and Lq.

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基于多项式在线参数估计的永磁同步电机无交互最优自适应转矩控制。
本文研究了一种永磁同步电机d轴和q轴动力学解耦的非相互作用转矩控制策略。最大转矩每安培(MTPA)方法用于确定所需转矩的参考电流。为了实现无交互控制,需要了解电机的电感Ld和Lq。这两个电感由两个扩展卡尔曼滤波器(ekf)估计,该滤波器使用单变量多项式作为模型来描述永磁同步电机的饱和效应。卡尔曼滤波(KF)是在非交互控制系统中实现的,以提高电感的可观测性。尽管存在非完全解耦,但由于KFs的结构随机性,非相互作用抵消误差用其过程噪声表示,并且电感估计得足够好。从这个意义上说,我们可以谈论非交互控制中的KFs。电感的估计是优化转矩控制的基础,是减小机械振动和干扰的可行方法。此外,基于模型的控制策略必须自适应调整才能正常工作。从现有文献出发,提出了一种可行的控制结构,其中使用比例积分(PI)控制器的控制回路的稳定性显示了所得到的时变系统。实际上,由于存在可变电感Ld和Lq以及转子速度的存在,该模型被表示为时变系统,而转子速度不被视为状态。本文采用正演欧拉离散化方法来实现离散实验装置中的观测器。利用硬件在环(HIL)实现的测量在电感估计的背景下显示出有趣的结果,这是由于非交互控制减少了两个解耦ekf的尺寸。利用HIL模拟器对所提出的转矩控制策略进行了研究,结果表明,由于解耦,转矩控制策略在提高可观测性方面取得了良好的效果。这和在EKF计算中使用单变量多项式导致测量点的显著减少,振荡和波纹的减少,期望和实现扭矩之间的偏差以及干扰的减少。此外,所提出的控制策略使用了非常有限的计算负载,同时将波纹保持在获得的转矩的技术限制范围内。这两种效果都是由于解耦ekf使用单变量多项式简化和降低了模型的阶数,这在创建电感Ld和Lq模型之前需要显着减少的测量点。
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