International audienceThis paper presents a novel maximum power pointtracking (MPPT) algorithm, based on genetic algorithms (GA).This algorithm is used for searching the global maximum powerpoint (GMPP) for photovoltaic systems affected by partialshading. The “Perturb and Observe” (P&O) algorithm isembedded into the GA function for improving the optimisationprocess. By adding this functionality to the algorithm, thenumber of iterations and the population size is low, thus findingthe MPP in a short time. Description of this algorithm and itsperformances will be detailed in this article, verified throughsimulation and experimental results

Batteries packs made of series-parallel connected cells have developed a lot lately. These new solutions brought along with them some safety issues due to the possibility of overcharging or under-discharging of every individual cell that forms the pack. Balancing is one of the most important issues regarding battery management, as without it the individual cell voltages will draft apart over time and the pack's total capacity will also decrease more quickly. This paper presents some theory behind the balancing methods developed so far and presents a new system used for cell balancing.

A method using a miniature analytical system based on hydride generation capacitively coupled plasma microtorch optical emission spectrometry with a QE65 Pro microspectrometer was developed and evaluated for the simultaneous determination of As and Sb in soil samples. The use of this microspectrometer allows the examination of the spectral range between 190 and 220 nm where the continuum background emission of the plasma is low and the most intense resonance lines As 193.759; 197.262 nm and Sb 206.833; 217.581 nm are located. The method involves microwave-assisted digestion of samples in aqua regia, prereduction of As(V) and Sb(V) to their (+3) species with 0.3% L-cysteine by heating in a boiling water bath at 90 ± 5 °C and hydride generation in 0.01 mol L⁻¹ HCl (pH = 2.00 ± 0.01) medium with 0.5% NaBH₄ solution. The method was optimized in order to provide the simultaneous determination of As and Sb. The figures of merit were evaluated at different emission wavelengths under the optimum conditions of plasma microtorch operation (10 W, 150 mL min⁻¹ Ar), and the best performances were obtained at 193.759 nm (As) and 217.581 nm (Sb). The figures of merit of the method were compared to those of the traditional hydride generation inductively coupled plasma optical emission spectrometry taken as a reference method. Analysis of CRMs revealed recoveries of 101 ± 9% As and 102 ± 3% Sb comparable to 102 ± 7% As and 98 ± 4% Sb in the reference method. The precision of determinations was 2–10% for 90–210 mg kg⁻¹ As and 40–130 mg kg⁻¹ Sb, close to 3–8% in hydride generation inductively coupled plasma optical emission spectrometry. The Bland and Altman test performed on 10 soil samples indicated no significant difference between the results obtained by the two methods, so that the miniature analytical system could be successfully applied for As and Sb monitoring in environmental samples. The proposed method is attractive in terms of analytical costs due to limited consumption of high purity HCl, power and Ar to sustain the plasma, and therefore more advantageous than hydride generation inductively coupled plasma optical emission spectrometry.

This paper reviews the evolution of methodologies and tools for modeling, simulation, and design of digital electronic system-on-chip (SoC) implementations, with a focus on industrial electronics applications. Key technological, economic, and geopolitical trends are presented at the outset, before reviewing SoC design methodologies and tools. The fundamentals of SoC design flows are laid out. The paper then exposes the crucial role of the intellectual property (IP) industry in the relentless improvements in performance, power, area, and cost (PPAC) attributes of SoCs. High abstraction levels in design capture and increasingly automated design tools (e.g., for verification and validation, synthesis, place, and route) continue to push the boundaries. Aerospace and automotive domains are included as brief case studies. This paper also presents current and future trends in SoC design and implementation including the rising, evolution, and usage of machine learning (ML) and artificial intelligence (AI) algorithms, techniques, and tools, which promise even greater PPAC optimizations.