The Filter-Based Method (FBM) is one of the most simple and effective approaches for energy management in hybrid energy storage systems (HESS) composed of batteries and supercapacitors (SC). The FBM has evolved from its conventional form in such a manner that more flexibility and functionalities have been added. A comparative study and analysis of the most recent and relevant proposals based on the FBM for HESS are provided in this paper. In this way, the improvements for this energy management system (EMS) are in the form of adaptive filters, rules, Fuzzy logic control, sharing coefficients, and additional control loops. It is shown how these enhancements seek to avoid the premature degradation of the storage devices that are caused by deep discharge, overcharge, and fast current variations in the case of batteries and overcharge in the SC case. Therefore, the enhancements are focused on keeping the battery and SC working within safe operational limits. This paper presents new comparisons regarding the SoC evolution in the storage devices, specifically how the SC SoC is used in the EMS to establish the power sharing. Numerical simulations are added to compare the performance of the different EMS structures. The analysis of the results shows the effectiveness of the FBM in achieving power allocation and how the latest proposed improvements help to add flexibility to HESS as well as to avoid premature degradation of the storage devices.

Digital repetitive control is a technique which allows to track periodic references and/or reject periodic disturbances. Repetitive controllers are usually designed assuming a fixed frequency for the signals to be tracked/rejected, its main drawback being a dramatic performance decay when this frequency varies. A common approach to overcome this problem consists of an adaptive change of the sampling time according to reference/disturbance period variations. However, the sampling period adaptation implies structural changes that may degrade the closed-loop time response. This article presents a design strategy which allows to compensate for the effect of non-uniform sampling and forces the closed-loop behavior to coincide with that of the system operating under an a priori selected nominal sampling period. The stability of the overall closed-loop system is also analyzed. Experimental results obtained from a mechatronic plant model validate the proposal.

Redox flow batteries are one of the most relevant emerging large-scale energy storage technologies. Developing control methods for them is an open research topic; optimizing their operation is the main objective to be achieved. In this paper, a strategy that is based on regulating the output voltage is proposed. The proposed architecture reduces the number of required sensors. A rigorous design methodology that is based on linear $H_{\infty }$ synthesis is introduced. Finally, some simulations are presented in order to analyse the performance of the proposed control system. The results show that the obtained controller guaranties robust stability and performance, thus allowing the battery to operate over a wide range of operating conditions. Attending to the design specifications, the controlled voltage follows the reference with great accuracy and it quickly rejects the effect of sudden current changes.