Multiple-Iteration Search Sensorless Control for Linear Motor in Vehicle Regenerative Suspension
Xiaodong Sun, Minkai Wu, Chunfang Yin, Shaohua Wang, Xiang Tian
Abstract
This article presents a sensorless control for the permanent-magnet linear synchronous motor (PMLSM) under the energy-feeding mode in vehicle regenerative suspension. The proposed method is based on a multiple-iterative search algorithm to obtain a limited quantity of mover position signals (electrical angle) precisely, which are utilized to observe the d-axis back electromotive force (EMF). Then, the optimal mover position signal selected from the estimated mover position is restrained by the cost function applied in the multiple-iteration search algorithm. The accuracy of the mover position signal increases geometrically in the effect of an increase in the iterations. The proposed search algorithm is superior to the existing search algorithm in the terms of the computational burden. Different from the conventional phase-locked loop (PLL), the new strategy removes the need for a proportional-integral controller. The proposed control method and the conventional control method are experimentally tested under different conditions. Results prove that the proposed PLL has the effectiveness to realize the estimated parameters corresponding to the actual parameters.