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As a favorable energy storage component, Lithium-ion (Li-ion) battery has been widely used in the Battery Energy Storage Systems (BESS) and Electric Vehicles (EV). Data driven methods estimate the battery State of Health (SOH) with the features extracted from the measurement. However, excessive features may reduce the estimation accuracy and also increases the human labor in the lab. By proposing an optimization process with Non-dominated Sorting Genetic Algorithm II (NSGA-II), this paper is able to establish a more efficient SOH estimator with Support Vector Regression (SVR) and the short-term features from the current pulse test. NSGA-II optimizes the entire process of establishing a SOH estimator considering both the measurement cost of the feature and the estimation accuracy. A series of non-dominated solutions are obtained by solving the multi-objective optimization problem, which also provides more flexibility to establish the SOH estimator at various conditions.The degradation features in this paper are the knee points at the transfer instants of the voltage in the short-term current pulse test, which is fairly convenient and easy to be obtained in real applications. The proposed method is validated on the measurement from two LiFePO4/C batteries aged with the mission profile providing the Primary Frequency Regulation (PFR) service to the grid. 1

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This study focuses on the identification of the rotating diode failures of an aircraft wound-field synchronous starter-generator system. Owing to the difference in topography between the DC field excitation system and the threephase brushless asynchronous excitation system (TBAES), the rotating diodes failure identification methods for the DC field excitation system cannot be implemented in TBAES. To solve this problem, this study presents the theoretical analysis of the effects of diode failures on the TBAES rotor current. The theoretical analysis shows that the third and the fundamental components of rotor current could be treated as diode failure features. When a rotating diode operates in open-circuit conditions, the third harmonic current of the normal phase windings increases, but it does not increase while in the fault phase. Meanwhile, the amplitude of the fundamental current of failure phase reduces. Under short-circuit conditions, both the third harmonic and the fundamental component of the rotor current of TBAES rotorwindings increase. On the basis of the theoretical findings, the detection of rotating diode failures is achieved by the harmonic analysis of the estimated rotor currents.