Flying Capacitor Voltage Balancing Control Strategy Based on Logic-equations in Five Level ANPC Inverter

This paper proposes a novel voltage balancing control approach for the flying capacitors in a five-level Active-Neutral-Point-Clamped inverter (ANPC). The projected method is based on the control signal of the flying capacitor (FC) voltage. A Staircase reference voltage-based Phase-Shifted PWM (PS-PWM) technique is used to generate the different levels and simple logic-equations. The proposed control can regulate the voltage of the FC at the requested reference value and generate the required five-level output voltage with fast dynamics. It requires fewer and simpler calculations and it has a fast execution time. The Simulations are performed using MATLAB and Simulink. The obtained results demonstrate the good performance of the FC voltage control and the high quality of the output voltages and current spectrum

Efficient power-electronic converters for electric vehicle applications

This paper introduces advanced power-electronic converter topologies for Electric Vehicles (EVs) using a four-phase DC/DC interleaved boost converter (FP-IBC) and a five-level T-type DC/AC multilevel converter. A comparison between the proposed topologies and other converter topologies is performed and discussed. The simulation results are analysed to evaluate the converters based on power loss calculations and harmonic analysis. The converters are studied at different switching frequencies and various loading conditions to reflect their effects on the converter losses. The results highlight the proposed converters' higher efficiency compared to other studied converter topologies in electric vehicle applications

Power Electronic Converters in Particle Accelerator Applications: A Review

International audienceIn particle accelerator (PA) applications, a continuous, reliable, efficient and sustainable power supply solution is required. This supply should guarantee the availability of high power quality through reliable and high energy efficient power electronic stage .This paper presents a review on different power electronic converters for particle accelerator applications and provides an account of research in areas related to main power converters' topologies, operating modes control systems, fault detection and isolation methods and reliability analysis. The paper can be also considered as a guidance to assist in the power converter selection process of the next generations of particle accelerators

State-of-charge and state-of-health prediction of lead-acid batteries with genetic algorithms

International audienceIn this paper, a state of charge (SoC) and state of health (SoH) estimator is presented for lead-acid batteries. The estimation strategy is based on adaptive control theory for online parameters identification. To speed up the estimator's convergence, the adaptation law is replaced by a genetic algorithm (GA). Therefore, robustness to parameters variation is also achieved and thus, accurate prediction with battery aging. Unlike other estimation strategies, only battery terminal voltage and current measurements are required. Results show high convergence and highlight the performance of the proposed estimator in predicting the SoC and SoH with high accuracy

Adaptive Fuzzy Logic Control Mixing Strategy of DC/DC Converters in Both Discontinuous and Continuous Conduction Modes

International audienceIn this paper, a bidirectional DC/DC converter with two voltage source at both ends operating in both discontinuous conduction mode (DCM) and continuous conduction mode (CCM) is discussed. The average model for each topology, i.e., buck, boost, and buck–boost, is derived. Due to the contradictory nature of DCM and CCM, conventional controllers fail to achieve smooth transition while crossing between these modes. Two adaptive fuzzy logic controllers (FLC) incorporated into a local model network (LMN) are proposed to achieve accurate and smooth control of the converter in both DCM and CCM. The proposed control scheme does not require any a priori offline training, weights initialization, and parameters knowledge. The adaptive fuzzy logic control strategy is compared against its proportional integral (PI) control counterpart, and their performance is verified under parameter variations

Non linear classification with neural networks

International audienc

State-of-charge and state-of-health prediction of lead-acid batteries with genetic algorithms

International audienceIn this paper, a state of charge (SoC) and state of health (SoH) estimator is presented for lead-acid batteries. The estimation strategy is based on adaptive control theory for online parameters identification. To speed up the estimator's convergence, the adaptation law is replaced by a genetic algorithm (GA). Therefore, robustness to parameters variation is also achieved and thus, accurate prediction with battery aging. Unlike other estimation strategies, only battery terminal voltage and current measurements are required. Results show high convergence and highlight the performance of the proposed estimator in predicting the SoC and SoH with high accuracy

Nouvelle version adaptative de l’algorithme du boosting : optimisation du critère d’erreur et comparaison avec un perceptron multicouches

International audienc

Energy management and optimization in microgrid system based on green energy

International audienceCurrent research activities witness a special focus on the integration of DERs (distributed energy resources) and ESSs (energy storage systems) in MG (micro-grid) applications. In this paper, the coordination between MG and main grid for the required variable load demands is accomplished using EMS (Energy Management System). For this purpose, an advanced EMS in a typical MG working in grid connected mode is introduced. The developed EMS is able to determine the optimal operating strategies that minimize the energy costs, pollutant emissions, and hence maximizing the output of the available renewable energy resources. The established EMS is formulated as a nonlinear optimization model with different equality and inequality constraints for proper solution based on the AIMMS (Advanced Integrated Multidimensional Modeling Software). The performance of AIMMS is compared with other commonly used algorithm such as GA (genetic algorithms) to clarify the efficient and robustness of AIMMS solver