Design and Implementation of Parameter Estimation and Start Control of Brushless Synchronous Starter/Generators Under Sudden Excitation Change

The stator winding structure of the main exciter of the brushless synchronous starter/generator (BSSG) is changed at high speed for flux weakening, leading to a sudden excitation decrease of the main generator (MG) of BSSG. Consequently, when proportional-integral (PI) current loop-based control strategies are applied, large current overshoots will occur due to the lack of fast current control ability. This paper adopts model predictive current control (MPCC) to replace PI current control for a better dynamic performance. Besides, a parameter estimation scheme, based on the recursive least square (RLS) algorithm, is proposed to provide MG parameters for MPCC. An effectiveness analysis of the RLS algorithm is performed and two rules are given. According to the two rules, rather than the parameter dynamic characteristics adopted by traditional methods, three MG parameters, dq-axes inductances, and excitation flux linkage are estimated with two decoupled RLS estimators. In addition, a method is proposed to adjust the forgetting factor to track fast changing parameters of MG when the excitation changes suddenly. With the estimated parameters, MPCC is conducted to start BSSG. Experimental results show that fast current control of MG is achieved and large current overshoots caused by the sudden excitation change are avoided.