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In this work, a new model of Darrieus wind turbines with an oscillating gurney flap (OGF) is proposed. A detailed 2D computational fluid dynamics (CFD) investigation is carried out using ANSYS-Fluent 22.0 to assess the turbine performance. The OGF can alter its position between the upper and lower blade surfaces during the turbine rotation. Equations related to the combined motion are implemented through a user-defined function (UDF). The proposed model is validated where a good coincidence is achieved. The overset dynamic mesh method is used. It was found that a judicious synchronization of OGF and turbine blades creates beneficial vortex interactions, which correct the pressure distribution and lead to an overall improvement in the lift force. The magnitude of the improvement is highly dependent on the OGF length and the phase motion φ. The average torque coefficient Cm for the controlled case increased by more than 19% in comparison with the nominal case.

Lithium-ion battery State of Health (SOH) estimation is an essential issue in battery management systems. In order to better estimate battery SOH, Extreme Learning Machine (ELM) is used to establish a model to estimate lithium-ion battery SOH. The Swarm Optimization algorithm (PSO) is used to automatically adjust and optimize the parameters of ELM to improve estimation accuracy. Firstly, collect cyclic aging data of the battery and extract five characteristic quantities related to battery capacity from the battery charging curve and increment capacity curve. Use Grey Relation Analysis (GRA) method to analyze the correlation between battery capacity and five characteristic quantities. Then, an ELM is used to build the capacity estimation model of the lithium-ion battery based on five characteristics, and a PSO is introduced to optimize the parameters of the capacity estimation model. The proposed method is validated by the degradation experiment of the lithium-ion battery under different conditions. The results show that the battery capacity estimation model based on ELM and PSO has better accuracy and stability in capacity estimation, and the average absolute percentage error is less than 1%.

This paper presents a comprehensive review of advanced control methods specifically designed for floating offshore wind turbines (FOWTs) above the rated wind speed. Focusing on primary control objectives, including power regulation at rated values, platform pitch mitigation, and structural load reduction, this paper begins by outlining the requirements and challenges inherent in FOWT control systems. It delves into the fundamental aspects of the FOWT system control framework, thereby highlighting challenges, control objectives, and conventional methods derived from bottom-fixed wind turbines. Our review then categorizes advanced control methods above the rated wind speed into three distinct approaches: model-based control, data-driven model-based control, and data-driven model-free control. Each approach is examined in terms of its specific strengths and weaknesses in practical application. The insights provided in this review contribute to a deeper understanding of the dynamic landscape of control strategies for FOWTs, thus offering guidance for researchers and practitioners in the field.

In this paper, a sliding mode observer (SMO) for the speed-sensorless direct torque vector control of linear induction motor(LIM) is proposed, considering the influence of dynamic end effects. The proposed SMO estimate the motor speed, the rotor flux, the angular position of the rotor flux, and the speed dependent parameter $w$ , only by using the measured stator voltages and stator currents. The nonlinear sliding mode technique guarantees very good performance for different situations of motor speed. The proposed SMO does not use complicated observer gains and robust to the parameter variation over the full-speed range. Moreover, the convergence of SMO is proven by using the Lyapunov theory. Furthermore, LIM Drive state observability is presented with detailed analysis. The performance of the proposed SMO is verified by hardware-in-the-loop test (HIL) system. Furthermore, a comparative study with and Luenberger observer(LO) and model reference adaptive system(MRAS) is presented.

This article proposes a review of the modeling approaches for floating offshore wind turbines (FOWTs) for nonlinear control design. The aerodynamic, hydrodynamic and mooring line dynamic modules for the FOWT have been reviewed to provide an overview of several modeling approaches with their respective features. Next, three control-oriented models from the literature are revisited by presenting their methodological approaches to modeling and identification. These three models cover the three most popular types of FOWTs. Then, the performances of these models are validated with the open fatigue, aerodynamics, structures, and turbulence (OpenFAST) code, and their performances are evaluated according to several criteria. Finally, one of the three models is used to illustrate a nonlinear second-order sliding mode control based on the twisting algorithm to optimize the performance of the FOWT in terms of energy extraction and reduction in the platform pitch oscillation.

In order to improve the durability and economy of a hybrid power system composed of a battery and supercapacitors, a control strategy that can reduce fluctuations of the battery current is regarded as a significant tool to deal with this issue. This paper puts forwards a disturbance rejection control strategy for a hybrid power system taking into account the degradation of the battery. First, the degradation estimation of the battery is done by the model-driven method based on the degradation model and Cubature Kalman Filter (CKF). Considering the transient and sinusoidal disturbance from the load in such a hybrid system, it is indispensable to smooth the behavior of the battery current in order to ensure the lifespan of the battery. Moreover, the constraints for the hybrid system should be considered for safety purposes. In order to deal with these demands, a cascaded voltage control loop based on a super twisting controller and proportional integral controller with an anti-windup scheme is designed for regulating the DC bus voltage in an inner voltage loop and supercapacitors’ voltage in an outer voltage loop, respectively. The specific feature of the proposed control method is that it operates like a low-pass filter so as to reduce the oscillations on the DC bus.