Optimal control strategy for excitation parameters of SRGs
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ORIGINAL ARTICLE
Optimal control strategy for excitation parameters of SRGs Yuyu Dou1 · Dong Chen2 Received: 30 April 2020 / Revised: 25 August 2020 / Accepted: 31 August 2020 / Published online: 17 September 2020 © The Korean Institute of Power Electronics 2020
Abstract To solve the inherent contradiction between convergence speed and optimization accuracy in the traditional optimal control strategy for the excitation parameters of SRGs, a novel optimal control strategy for the excitation parameters is proposed. In this strategy, the turn-off angle is fixed at its optimal value and kept constant, and the turn-on angle is optimized through two steps. In the first step, the optimal searching region of the turn-on angle is calculated by a fitting formula. Then in the second step, the golden section algorithm is used to optimize the turn-on angle. Meanwhile, the phase current amplitude is used as the degree of freedom necessary to regulate the generation power. Experimental results indicate that the novel optimal control strategy for excitation parameters can effectively improve convergence speed and efficiency of SRGs. Keywords Switched reluctance generator (SRG) · Optimal control strategy · Golden section algorithm · Excitation parameters
1 Introduction The SRG has been successfully applied in many fields due to its advantages such as simple structure, low manufacturing cost, convenient maintenance, strong fault tolerance and high operation reliability [1–7]. However, the power density and efficiency of SRGs are relatively low, which further limits their application. In order to improve the performance of SRGs, experts and scholars at home and abroad have done a lot of research on optimal control for excitation parameters [8–13]. Due to its doubly salient structure, the electromagnetic characteristics of SRGs are very nonlinear. In other words, there is a highly nonlinear mapping relationship between the flux linkage of the winding (ψph), the current (iph) and the rotor position angle (θ), as shown in Fig. 1, which is difficult to express in analytical form. In view of this, present optimal control strategies for the excitation parameters are mainly divided into two categories: offline optimization methods and on-line optimization methods. The off-line optimization methods store the optimal * Yuyu Dou [email protected] 1
State Grid East Inner Mongolia Electric Power Research Institute, Hohhot, Inner Mongolia, China
State Grid Weifang Electric Power Company, Weifang, Shandong, China
2
13
Vol:.(1234567890)
excitation parameters of SRGs under various operation conditions in a look-up table. Thus, the optimal excitation parameters can be automatically obtained with the look-up table. The accuracy of off-line optimization is related to the dimension and data quantity of the look up table. A high dimension look-up table can effectively improve the optimization accuracy. However, such look up tables occupy a lot of memory and consume more computing resources. In addition, the parameters of SRGs change with
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