The Kriging surrogate model in complex simulation problems uses as few expensive objectives as possible to establish a global or local approximate interpolation. However, due to the inversion of the covariance correlation matrix and the solving of Kriging-related parameters, the Kriging approximation process for high-dimensional problems is time consuming and even impossible to construct. For this reason, a high-dimensional Kriging modeling method through principal component dimension reduction (HDKM-PCDR) is proposed by considering the correlation parameters and the design variables of a Kriging model. It uses PCDR to transform a high-dimensional correlation parameter vector in Kriging into low-dimensional one, which is used to reconstruct a new correlation function. In this way, time consumption of correlation parameter optimization and correlation function matrix construction in the Kriging modeling process is greatly reduced. Compared with the original Kriging method and the high-dimensional Kriging modeling method based on partial least squares, the proposed method can achieve faster modeling efficiency under the premise of meeting certain accuracy requirements.

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This article proposed a position signal-free field current estimation method for brushless synchronous starter/generator (BSSG). Generally, the estimation of the field current of BSSG depends on the position signals provided by a physical sensor or position estimation algorithm. However, there are risks in using the traditional method when the position sensor is broken or using estimated position information to evaluate the field current. To overcome this problem, this paper proposes a position signal-free estimation method. In this method, the mathematical relationship between the field current of the main machine (MM) and the current vector modulus (CVM) of the main exciter (ME) rotor currents are analyzed. The theoretical findings reveal that the average field current of the main machine (MM) equates to the minimum or √3/2 times the maximum of ME's rotor CVM in both rotating and stationary coordinates. Since the ME's rotor CVM is independent of the rotor position information, the estimation of the field current of BSSG can be achieved without the rotor position signal departing in. Finally, an experiment platform is established to emulate the BSSG, and experimental results validate the theoretical findings.