Power sources coordination through multivariable LPV/Hinf control with application to multi-source electric vehicles

International audienceIn this paper the problem of multi-source power sharing strategy within electric vehicles is considered. Three different kinds of power sources - fuel cell, battery and supercapacitor - compose the power supply system, where all sources are current-controlled and paralleled together with their associated DC-DC converters on a common DC-link. The DC-link voltage must be regulated regardless of load variations corresponding to the driving cycle. The proposed strategy is a robust control solution using a MIMO LPV/H-inf controller which provides the three current references with respect to source frequency characteristics. The selection of the weighting functions is guided by a genetic algorithm whose optimization criterion expresses the frequency separation requirements. A reduced-order version of the LPV/H-inf controller is also proposed to handle an embedded implementation with limited computational burden. The nonlinear multi-source system is simulated in MATLAB® / Simulink® using two different types of driving cycles: the driving cycle of IFSTTAR (Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux) and a constant load profile used in order to illustrate system steady-state behaviour. Simulation results show good performance in supplying the load at constant DC-link voltage according to user-configured frequency-separation power sharing strategy. When assessed against the classical-PI-based filtering strategy taken as base-line, the proposed strategy offers the possibility of integrating a variety of constraints into a systematic design procedure, whose result guarantees stability and performance robustness

Intelligent control of battery energy storage for microgrid energy management using ANN

In this paper, an intelligent control strategy for a microgrid system consisting of Photovoltaic panels, grid-connected, and li-ion battery energy storage systems proposed. The energy management based on the managing of battery charging and discharging by integration of a smart controller for DC/DC bidirectional converter. The main novelty of this solution are the integration of artificial neural network (ANN) for the estimation of the battery state of charge (SOC) and for the control of bidirectional converter. The simulation results obtained in the MATLAB/Simulink environment explain the performance and the robust of the proposed control technique

A review of energy management strategies for renewable hybrid energy systems with hydrogen backup

Hybrid systems are presented as a viable, safe and effective solution to minimize the associated problems of the dependence on renewable energies with the environmental resources. In this way different renewable systems such as photovoltaic, wind, hydrogen and so on, can work together to configure hybrid renewable systems. However, to make them work properly in a holistic way by creating synergies among them is not an easy task. Recently hydrogen technology has appeared as a promising technology to hybridize renewable energy systems, since it allows the generation (by electrolyzers) and storage of hydrogen when there is a surplus of energy in the system, and at a later time (e.g. when there are insufficient renewable resources available) using the stored hydrogen to generate electrical energy by fuel cells. The choice of a correct energy management strategy should guarantee an optimum performance of the whole hybrid renewable system; therefore, it is necessary to know the most important criteria in order to define a management strategy that ensures the best solution from a technical and economic point of view. This paper presents a critical review and analysis of different energy management strategies for hybrid renewable systems based on hydrogen backup. In the same way, a review is also presented of the most important technical and economic optimization criteria, as well as problems and solutions studied in the scientific literature