A new off-board electrical vehicle battery charger: topology, analysis and design

The extensive use of electric vehicles (EVs) can reduce concerns about climate change and fossil fuel shortages. One of the main obstacles to accepting EVs is the limitation of charging stations, which consists of high-charge batteries and high-energy charging infrastructure. A new transformer-less topology for boost dc-dc converters with higher power density and lower switch stress is proposed in this paper, which may be a suitable candidate for high-power fast-charging battery chargers of EVs. Throughout this paper, two operating modes of the proposed converter, continuous current mode (CCM) and discontinuous current mode (DCM), are analyzed in detail. Additionally, critical inductances and design considerations for the proposed converter are calculated. Finally, real-time verifications based on hardware-in-loop (HiL) simulation are carried out to assess the correctness of the proposed theoretical concepts

Sliding Mode Control based Support Vector Machine RBF Kernel Parameter Optimization

Support Vector Machine (SVM) is a learning-based algorithm, which is widely used for classification in many applications. Despite its advantages, its application to large scale datasets is limited due to its use of large number of support vectors and dependency of its performance on its kernel parameter. This paper presents a Sliding Mode Control based Support Vector Machine Radial Basis Function’s kernel parameter optimization (SMC-SVM-RBF) method, inspired by sliding mode closed loop control theory, which has demonstrated significantly higher performance to that of the standard closed loop control technique. The proposed method first defines an error equation and a sliding surface and then iteratively updates the RBF’s kernel parameter based on the sliding mode control theory, forcing SVM training error to converge below a predefined threshold value. The closed loop nature of the proposed algorithm increases the robustness of the technique to uncertainty and improves its convergence speed. Experimental results were generated using nine standard benchmark datasets covering wide range of applications. Results show the proposed SMC-SVM-RBF method is significantly faster than those of classical SVM based techniques. Moreover, it generates more accurate results than most of the state of the art SVM based methods

An optimal approach for load-frequency control of islanded microgrids based on nonlinear model

Due to the increased environmental and economic challenges, in recent years, renewable based distribution generation has been developed. More penetrations from the side of consumers caused a new concept called microgrids which are able to stand with or without connection to the bulk power system. Control of microgrids in islanded mode is very crucial for decreasing the amplitude of frequency deviations as well as damping speed. This chapter aims to propose an optimal combination of FOPD and fuzzy pre-compensated FOPI approach for load-frequency control of microgrids in islanded mode. The optimization parameter of the control scheme is designed by the differential evolution (DE) algorithm which has been improved by a fuzzy approach. In the optimization, control effort is considered as a constraint. Due to the robustness and flexibility of the proposed method, the simulation results have been improved substantially. Robust performance of the proposed control method is examined through sensitivity analysis.fi=vertaisarvioitu|en=peerReviewed

Patterns of Sports Supplement Use among Iranian Female Athletes

Supplement use is common in athletes. Besides their cost, they may have side effects on health and performance. 250 questionnaires were distributed among female athletes (mean age 27.08 years). The questionnaire aimed to explore the frequency, type, believes, attitudes and knowledge regarding dietary supplements. Knowledge was good in 30.3%, fair in 60.2%, and poor in 9.1% of respondents. 65.3% of athletes did not use supplements regularly. The most widely used supplements were vitamins (48.4%), minerals (42.9%), energy supplements (21.3%), and herbals (20.9%). 68.9% of athletes believed in their efficacy. 34.4% experienced performance enhancement and 6.8% of reported side effects. 68.2% reported little knowledge and 60.9% were eager to learn more. In conclusion, many of the female athletes believe in the efficacy of supplements and think they are an unavoidable part of competitive sports. However, their information is not sufficient. We have to stress on education, consulting sessions, and rational prescription