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Parameter identification of photovoltaic (PV) modules plays a vital role in modeling PV systems. This study aims to propose a novel hybrid approach to identify the seven parameters of the two-diode model of PV modules with high accuracy.

The proposed hybrid approach combines an improved particle swarm optimization (IPSO) algorithm with an analytical approach. Three parameters are optimized using IPSO, whereas the other four are analytically determined. To improve the performance of IPSO, three improvements are adopted, that is, evaluating the particles with two evaluation functions, adaptive evolutionary learning and adaptive mutation.

The performance of proposed approach is first verified by comparing with several well-established algorithms for two case studies. Then, the proposed method is applied to extract the seven parameters of CSUN340-72M under different operating conditions. The comprehensively experimental results and comparison with other methods verify the effectiveness and precision of the proposed method. Furthermore, the performance of IPSO is evaluated against that of several popular intelligent algorithms. The results indicate that IPSO obtains the best performance in terms of the accuracy and robustness.

An improved hybrid approach for parameter identification of the two-diode model of PV modules is proposed. The proposed approach considers the recombination saturation current of the p–n junction in the depletion region and makes no assumptions or ignores certain parameters, which results in higher precision. The proposed method can be applied to the modeling and simulation for research and development of PV systems.

This paper aims to study the wear properties of electron beam melted Ti6Al4V (EBM-Ti6Al4V) in simulated body fluids for orthopedic implant biomedical applications compared with wrought Ti6Al4V (Wr-Ti6Al4V).

Wear properties of EBM-Ti6Al4V compared with Wr-Ti6Al4V against ZrO₂ and Al₂O₃ have been investigated under dry friction and the 25 Wt.% newborn calf serum (NCS) lubricated condition using a ball-on-disc apparatus reciprocating motion. The microstructure, composition and hardness of the samples were characterized using scanning electron microscopy (SEM), x-ray diffraction and a hardness tester, respectively. The contact angles with 25 Wt.% NCS were measured by a contact angle apparatus. The wear parameters, wear 2D and 3D morphology were obtained using a 3D white light interferometer and SEM.

EBM-Ti6Al4V yields a higher contact angle than the Wr-Ti6Al4V with the 25 Wt.% NCS. EBM-Ti6Al4V couplings exhibit lower coefficients of friction compared with the Wr-Ti6Al4V couplings under both conditions. There is only a slight difference in the wear resistance between the Wr-Ti6Al4V and EBM-Ti6Al4V alloys. Both Wr-Ti6Al4V and EBM-Ti6Al4V suffer from similar friction and wear mechanisms, i.e. adhesive and abrasive wear in dry friction, while abrasive wear under the NCS condition. The wear depth and wear volume of the ZrO₂ couplings are lower than those of the Al₂O₃ couplings under both conditions.

This paper helps to establish baseline bio-tribological data of additively manufactured Ti6Al4V by electron beam melting in simulated body fluids for orthopedic applications, which will promote the application of additive manufacturing in producing the orthopedic implant.