In conventional adaptive variable step size (VSS) maximum power point tracking (MPPT) algorithms, a scaling factor is utilized to determine the required perturbation step. However, the performance of the adaptive VSS MPPT algorithm is essentially decided by the choice of scaling factor. In this paper, a neural network assisted variable step size (VSS) incremental conductance (IncCond) MPPT method is proposed. The proposed method utilizes a neural network to obtain an optimal scaling factor that should be used in current irradiance level for the VSS IncCond MPPT method. Only two operating points on the characteristic curve are needed to acquire the optimal scaling factor. Hence, expensive irradiance and temperature sensors are not required. By adopting a proper scaling factor, the performance of the conventional VSS IncCond method can be improved, especially under rapid varying irradiance conditions. To validate the studied algorithm, a 400 W prototyping circuit is built and experiments are carried out accordingly. Comparing with perturb and observe (P&O), α-P&O, golden section and conventional VSS IncCond MPPT methods, the proposed method can improve the tracking loss by 95.58%, 42.51%, 93.66%, and 66.14% under EN50530 testing condition, respectively.

In this paper, a fast equalizer for series-connected battery packs with adaptive balancing current control is proposed. As the duty cycle of the power switch in conventional equalizers is kept constant during the equalization process, smaller voltage difference between cells will decrease balancing current and consequently result in extended balancing time, especially in the later phase of equalization. To deal with this problem and take the battery nonlinearity and circuit parameter non-ideality into consideration, an adaptive balancing current control based on a fuzzy logic inference is proposed. The presented approach can adjust the duty ratio adaptively, according to voltages of individual cells and pack, to keep the balancing current nearly constant: Therefore, the balancing time can be shortened and the balancing efficiency can be improved. Finally, experimental results of three compared methods will be given and discussed to validate the feasibility, effectiveness, and performance improvement of the studied method.

In this study, an active inductive equalizer with fast energy transfer based on adaptive balancing current control is proposed to rapidly equilibrate lithium-ion battery packs. A multiphase structure of equalizer formed by many specific parallel converter legs (PCLs) with bidirectional energy conversion serves as the power transfer stage to make the charge shuttle back and forth between the cell and sub-pack or sub-pack and sub-pack more flexible and efficient. This article focuses on dealing with the problem of slow balancing rate, which inherently arises from the reduction of balancing current as the voltage difference between the cells or sub-packs decreases, especially in the later period of equalization. An adaptive varied-duty-cycle (AVDC) algorithm is put forward here to accelerate the balance process. The devised method has taken the battery nonlinear behavior and the nonideality of circuit component into consideration and can adaptively modulate the duty cycle with the change of voltage differences to maintain balancing current nearly constant in the whole equilibrating procedure. Test results derived from simulations and experiments are provided to demonstrate the validity and effectiveness of the equalizer prototype constructed. Comparing with the conventional fixed duty cycle (FDC) method, the improvements of 68.3% and 8.3% in terms of balance time and efficiency have been achieved.

In this study, an adaptive driving method for synchronous rectification in bidirectional full-bridge LLC resonant converters used in railway applications is proposed. The drain to source voltage of the synchronous rectifier is utilized to detect the conduction of the body diode, and a suitable driving signal for synchronous rectification is generated accordingly. The proposed driving scheme is simple and can be realized using a low-cost digital signal processor (DSP). According to the experimental results, which averaged 0.4625% and 1.097%, improvement can be observed under charging and discharging mode, respectively.

In a wind power plant of a wind power plant limited liability company, the fixed shaft of the torsion arm of the gear box broke during the operation of a wind power generator set. In order to find out the cause of fracture, the fracture fixed shaft of torsion arm was comprehensively detected and analyzed by means of appearance morphology analysis, chemical composition analysis, mechanical properties testing, microstructure testing and fracture micro-area analysis. The results show that the main reasons for the fracture of the fixed shaft of the torsion arm of the fan gear box are as follows: improper heat treatment process of the fixed shaft of the torsion arm of the gear box causes a large amount of massive ferrite in the material structure, resulting in insufficient strength of the material; the inclusion in the material is serious, resulting in unqualified impact toughness; Shaft surface surfacing Cr - Mn stainless steel material causes the fusion zone C migration form brittle layer, at the same time the vast difference between the state of welding layer and substrate organization fusion zone caused by larger remnants stress, the embrittlement in bond layer to form the intergranular crack crack source, and in the process of the equipment operation under the action of cyclic torsional and impact load, Cracks propagate in a fatiguing manner and lead to eventual fracture.