This paper presents a review of advanced architectures based on the partial power processing concept, whose main objective is to achieve a reduction of the power processed by the converter. If the power processed by the converter is decreased, the power losses generated by the power converter are reduced, obtaining lower sized converters and higher system efficiencies. Through the review 3 different partial power processing strategies are distinguished: Differential Power Converters, Partial Power Converters and Mixed strategies. Each strategy is subdivided into smaller groups that entail different architectures with their own advantages and disadvantages. Also, due to the lack of agreement that exists in the sources around the naming of the different architectures, this paper seeks to stablish a nomenclature that avoids confusion when indexing this type of architectures. Regarding Partial Power Converters an extensive application oriented description is also developed. Finally, the main conclusions obtained through the review are presented.

Several models for estimating the lifetimes of lead-acid and Li-ion (LiFePO₄) batteries are analyzed and applied to a photovoltaic (PV)-battery standalone system. This kind of system usually includes a battery bank sized for 2.5 autonomy days or more. The results obtained by each model in different locations with very different average temperatures are compared. Two different locations have been considered: the Pyrenees mountains in Spain and Tindouf in Argelia. Classical battery aging models (equivalent full cycles model and rainflow cycle count model) generally used by researchers and software tools are not adequate as they overestimate the battery life in all cases. For OPzS lead-acid batteries, an advanced weighted Ah-throughput model is necessary to correctly estimate its lifetime, obtaining a battery life of roughly 12 years for the Pyrenees and around 5 years for the case Tindouf. For Li-ion batteries, both the cycle and calendar aging must be considered, obtaining more than 20 years of battery life estimation for the Pyrenees and 13 years for Tindouf. In the cases studied, the lifetime of LiFePO₄ batteries is around two times the OPzS lifetime. As nowadays the cost of LiFePO₄ batteries is around two times the OPzS ones, Li-ion batteries can be competitive with OPzS batteries in PV-battery standalone systems.

The increasing deployment of battery storage applications in both grid storage and electric vehicle fields is generating a vast used battery market. These batteries are typically recycled but could be reused in second-life applications. One of the challenges is to obtain an accurate remaining useful life (RUL) estimation algorithm, which determines whether a battery is suitable for reuse and estimates the number of second-life cycles the battery will last. In this article, the RUL estimation problem is considered. We propose several health indicators (HIs), some of which have not been explored before, along with simple yet effective estimation and classification algorithms. These algorithms include classification techniques such as regularized logistic regression (RLR), and regression techniques such as multivariable linear regression (MLR) and multilayer perceptron (MLP). As a more advanced solution, a multiple expert system combining said techniques is proposed. The performance of the algorithms and features is evaluated on a recent lithium iron phosphate (LFP) data set from Toyota Research Institute. We obtain satisfactory results in the estimation of RUL cycles with errors down to 49 root mean square error (RMSE) cycles for cells that live up to 1200 cycles, and 0.24% mean relative error (MRE) for the prediction of the evolution of capacity.