Application Dependent End-of-Life Threshold Definition Methodology for Batteries in Electric Vehicles

The end-of-life event of the battery system of an electric vehicle is defined by a fixed end-of-life threshold value. However, this kind of end-of-life threshold does not capture the application and battery characteristics and, consequently, it has a low accuracy in describing the real end-of-life event. This paper proposes a systematic methodology to determine the end-of-life threshold that describes accurately the end-of-life event. The proposed methodology can be divided into three phases. In the first phase, the health indicators that represent the aging behavior of the battery are defined. In the second phase, the application specifications and battery characteristics are evaluated to generate the end-of-life criteria. Finally, in the third phase, the simulation environment used to calculate the end-of-life threshold is designed. In this third phase, the electric-thermal behavior of the battery at different aging conditions is simulated using an electro-thermal equivalent circuit model. The proposed methodology is applied to a high-energy electric vehicle application and to a high-power electric vehicle application. The stated hypotheses and the calculated end-of-life threshold of the high-energy application are empirically validated. The study shows that commonly assumed 80 or 70% EOL thresholds could lead to mayor under or over lifespan estimations.The iModBatt project has received funding from the European Union’s Horizon 2020 Programme for research and innovation under Grant Agreement No. 770054

Iterative capacity estimation of LiFePO4 cell over the lifecycle based on SoC estimation correction

Real time state of charge (SoC) and state of health (SoH) monitoring plays an essential role in electric vehicles, hybrid electric vehicles and generally in battery powered applications. Between these two state estimations, only the SoC has been studied rigorously until the current dates, while SoH or capacity estimation are much less referenced on the literature. Additionally, the SoC and the SoH estimation are strongly correlated by widely used coulomb counting equation and consequently wrong capacity estimation would lead to a SoC estimation error, which in turn, will lead to a further capacity estimation error. In this sense, the first job was to develop the equivalent electric model, design SoC estimator and to verify both of them experimentally. Then, different alternative techniques for estimating the capacity are analyzed, selecting the best choice considering the observability degree of the object of estimation: capacity. Then, in this paper we propose a new method for estimating the capacity, called iterative transferred charge, which adapts the current capacity estimation value based on the SoC correction made by the corresponding estimator. Finally, the developed algorithm is evaluated by comparing the capacity estimation with the reference over the life of the cell, by extensive experimental tests

Trifluorosulfonylation Cascade in Allenols: Stereocontrolled Synthesis of Bis(triflyl)enones

Herein, we report investigations embodying the first example of reversal of the native regioselectivity in the reaction of allenols with electrophiles. The effortlessness of C−C bond formation, mild reaction conditions, neither catalysts nor light irradiation, and exquisite selectivity, both in terms of functional-group tolerance and chemo-, site-, and stereo-selectivity, converts this trifluorosulfonylation-rearrangement sequence into an appealing protocol for the preparation of novel functionalized enones. The synthetic utility of this method has been validated by the conversion of the initially prepared bis(triflyl)enones into a variety of bis(triflyl)-functionalized molecules such as 1,3-dienes, allylic alcohols, pyrroles, pyrazoles, and chromenes. Besides, DFT calculations have provided a reliable understanding of observed selectivity.This work was supportedinpart by AEI (MICIU) and FEDER (Project PGC2018-095025-B-I00) and KAKENHI (17K08224). C.L.- M. thanks MICIU and UCM for a postdoctoral contract. We are grateful to Prof. B. Alcaide for continued support