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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.

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Current pulses are convenient to be actively implemented by a Battery Management System (BMS). However, the Short-Term Features (STF) from current pulses originate from various sensors with uneven qualities, which hinders one powerful and strong learner with STF for the battery SOH estimation. This paper thus proposes an optimized weak learner formulation procedure for Lithium-ion (Li-ion) battery SOH estimation, which further enables the automatic initialization and integration of the weak learners with STF into an efficient SOH estimation framework. A Pareto Front-based Selection Strategy (PFSS) is designed to select the representative solutions from the non-dominated solutions fed by a Knee point driven Evolutionary Algorithm (KnEA), which guarantees both the diversity and accuracy of the weak learners. Afterwards, the weak learners, whose coefficients are obtained by Selfadaptive Differential Evolution (SaDE), are integrated by a weight-based structure. The proposed method utilizes the weak learners with STF to boost the overall performance of SOH estimation. The validation of the proposed method is proved by LiFePO4/C batteries under accelerated cycling ageing test including one mission profile providing Primary Frequency Regulation (PFR) service to the grid and one constant current profile.

The structure and control strategy of a novel twophase brushless exciter were first proposed in this paper to solve the excitation problem of the main generator when threestage brushless synchronous starter/generator starts up. Twophase symmetrical winding was adopted as the field winding of the exciter, and was supplied with two-phase AC or DC by a two-phase inverter. This new exciter and control strategy have the advantages of high excitation efficiency and easy control compared with traditional single-phase and three-phase AC excitation strategy. A two-phase brushless exciter prototype, based on an existing exciter in three-stage starter/generator, was designed and analyzed using FEA. Simulation and experimental results verified the feasibility and advantages of the novel two-phase brushless exciter and control strategy.