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Miniaturised piezoelectric devices are emerging energy harvesting sources that are appropriate for various implantable and wearable applications. However, these piezoelectric devices exhibit considerable internal resistance due to their internal impedance, which leads to self-start and low-energy conversion failures. This paper describes a dual-stage boost converter circuit by facilitating self-powering features and boosting the low voltage harvested by the piezoelectric devices into dc. The proposed circuit comprises conversion stages of ac-dc and dc-dc in Stages I and II, respectively. In addition, the proposed circuit does not require employing the auxiliary circuits to generate the train pulses by triggering the bidirectional switches to envelop the current being stored in Stage II and kick-start the self-powered circuit for piezoelectric energy harvesting systems. Theoretical assumptions and control strategies were tested and verified with ideal and impedance input sources. The proposed circuit could convert a low voltage of 3 Vac into 19 Vdc. The maximum attained output power by the proposed circuit was 3.61 mW. The outcome depicted that the proposed circuit boosted the low voltage and outperformed the existing literature circuits in terms of output voltage and power. [ABSTRACT FROM AUTHOR]

In this study, a complete model for a miniature excitation-powered piezoelectric generator (PG), analysis modes of operation and control of a full-bridge joule thief (FBRJT) circuit to identify the optimal points were investigated. The proposed model revealed the PG's power dependency on mechanical excitation, acceleration, and frequency and defined the load behaviour for power optimisation. The proposed circuit, namely FBRJT, was integrated with the conventional full-bridge rectifier (FBR) in Stage 1 for AC-DC conversion and with the joule thief circuit in Stage 2 for DC-DC conversion. This integration acted as a boost converter without utilising the duty cycles and additional switching components. The electrical nature of the input of FBRJT with a simple structure, sensor-less control and auxiliary circuits showed a consistent agreement with the investigated testing scenarios using both ideal and impedance power sources. Additionally, the performance of the proposed circuit was also verified against the published results of power electronics circuits. The developed versatile circuit and control system can be utilised for many applications, such as mobile battery charging and energy harvesting. [ABSTRACT FROM AUTHOR]

In this article, a modified control structure for a single-stage three phase grid-connected photovoltaic (PV) system is presented. In the proposed system, the maximum power point tracking (MPPT) function is developed using a new adaptive model-based technique, in which the maximum power point (MPP) voltage can be precisely located based on the characteristics of the PV source. By doing so, the drift problem associated with the traditional perturb and observe (P&O) technique can be easily solved. Moreover, the inverter control is accomplished using a predictive dead-beat function, which directly estimates the required reference voltages from the commanded reference currents. Then, the reference voltages are applied to a space vector pulse width modulator (SVPWM) for switching state generation. Furthermore, the proposed inverter control avoids the conventional and known cascaded loop structure of the voltage oriented control (VOC) method by elimination of the outer PI controller, and hence the overall control strategy is simplified. The proposed system is compared with different MPPT techniques, including the conventional P&O method and other techniques intended for drift avoidance. The evaluation of the suggested control methodology depends on various radiation profiles created in MATLAB. The proposed technique succeeds at capturing the maximum available power from the PV source with no drift in comparison with other methods. [ABSTRACT FROM AUTHOR]

Electric vehicles are set to be the dominant form of transportation in the near future and Lithium-based rechargeable battery packs have been widely adopted in them. Battery packs need to be constantly monitored and managed in order to maintain the safety, efficiency and reliability of the overall electric vehicle system. A battery management system consists of a battery fuel gauge, optimal charging algorithm, and cell/thermal balancing circuitry. It uses three non-invasive measurements from the battery, voltage, current and temperature, in order to estimate crucial states and parameters of the battery system, such as battery impedance, battery capacity, state of charge, state of health, power fade, and remaining useful life. These estimates are important for the proper functioning of optimal charging algorithms, charge and thermal balancing strategies, and battery safety mechanisms. Approach to robust battery management consists of accurate characterization, robust estimation of battery states and parameters, and optimal battery control strategies. This paper describes some recent approaches developed by the authors towards developing a robust battery management system. [ABSTRACT FROM AUTHOR]