Loss reduction in converters is one of main targets in power electronics to obtain higher efficiency and lower thermal stress, which can enhance the lifetime of devices. This paper presents a variable switching frequency technique for switching loss reduction in a three-phase voltage source inverter, obtaining similar output current quality as that of a space vector pulse width modulation (SVPWM) algorithm. This type of optimization has not been applied for a three-phase system before. Simulation and experimental results are also shown. The output current ripple rms value of three-phase SVPWM is used as the optimization constraint. Results of the optimization of the switching losses with quality constraints in the switching frequency as the variable are presented for different load angles and compared with classical SVPWM. Experimental results show that this technique can save up to nearly 19% in switching losses with similar total harmonic distortion of the output current, concluding that converter losses are reduced without reducing output current quality.

As worldwide awareness about global climate change spreads, green electronics are becoming increasingly popular as an alternative to diminish pollution. Thus, nowadays energy efficiency is a paramount characteristic in electronics systems to obtain such a goal. Harvesting wasted energy from human activities and world physical phenomena is an alternative to deal with the aforementioned problem. Energy harvesters constitute a feasible solution to harvesting part of the energy being spared. The present research work provides the tools for characterizing, designing and implementing such devices in electronic systems through their equivalent structural models.

The evolution of technology enables the design of smarter medical devices. Embedded Sensor Systems play an important role, both in monitoring and diagnostic devices for healthcare. The design and development of Embedded Sensor Systems for medical devices are subjected to standards and regulations that will depend on the intended use of the device as well as the used technology. This article summarizes the challenges to be faced when designing Embedded Sensor Systems for the medical sector. With this aim, it presents the innovation context of the sector, the stages of new medical device development, the technological components that make up an Embedded Sensor System and the regulatory framework that applies to it. Finally, this article highlights the need to define new medical product design and development methodologies that help companies to successfully introduce new technologies in medical devices.

Low power electronic systems, whenever feasible, use supercapacitors to store energy instead of batteries due to their fast charging capability, low maintenance and low environmental footprint. To decide if supercapacitors are feasible requires characterising their behaviour and performance for the load profiles and conditions of the target. Traditional supercapacitor models are electromechanical, require complex equations and knowledge of the physics and chemical processes involved. Models based on equivalent circuits and mathematical equations are less complex and could provide enough accuracy. The present work uses the latter techniques to characterize supercapacitors. The data required to parametrize the mathematical model is obtained through tests that provide the capacitors charge and discharge profiles under different conditions. The parameters identified are life cycle, voltage, time, temperature, moisture, Equivalent Series Resistance (ESR) and leakage resistance. The accuracy of this electro-mathematical model is improved with a remodelling based on artificial neuronal networks. The experimental data and the results obtained with both models are compared to verify and weigh their accuracy. Results show that the models presented determine the behaviour of supercapacitors with similar accuracy and less complexity than electromechanical ones, thus, helping scaling low power systems for given conditions.