Fast Computing Flow Battery Modeling to Optimize the Choice of Electrolytes and Operating Conditions – Application to Aqueous Organic Electrolytes - Archive ouverte HAL Access content directly
Journal Articles Electrochimica Acta Year : 2021

Fast Computing Flow Battery Modeling to Optimize the Choice of Electrolytes and Operating Conditions – Application to Aqueous Organic Electrolytes

(1) , (1) , (1)
1
Martin Petit
David Pasquier

Abstract

We have developed a 0D model of aqueous organic redox flow battery to have a better understanding of the impact of oxygen and hydrogen evolution as a parasitic side reaction on the evolution of the battery performances. This lumped approach model is able to account for multiple redox processes at each electrode, which, to our knowledge has not been described in the literature. In this article the study is focused on alkaline battery and the model has been validated on 2,6-dihydroanthraquinone/ferrocyanide electrolytes at laboratory full cell level. The model considers the electrochemical reactions, the electrolyte flow rate, the diffusion of the electroactive molecules from the bulk to the reaction sites, the transfer of cations through a perfluorosulfonic membrane and the ohmic losses. Furthermore, the electrochemical reactions accounted for include the reduction and the oxidation of water modeled with Tafel slopes. Thanks to this approach, we highlight the non-negligible role of oxygen evolution reaction in these conditions. The model is used as a tool to optimize operating conditions as well as to predict the most advantageous potential of electrolytes to enhance performances and limit side reactions. For example, under alkaline condition (pH = 14), the negolyte standard potential can be targeted to -0.8 V without competing with HER, however, the posolyte potential must be kept below 0.65 V to avoid competition with OER.
Embargoed file
Vignette du fichier
Fast Computing Flow Battery Modeling to Optimize the Choice of Electrolytes and Operating Conditions Sup Mat.pdf (192.5 Ko) Télécharger le fichier
Embargoed file
0 5 25
Year Month Jours
Avant la publication

Dates and versions

hal-03353804 , version 1 (24-09-2021)

Identifiers

Cite

Quentin Cacciuttolo, Martin Petit, David Pasquier. Fast Computing Flow Battery Modeling to Optimize the Choice of Electrolytes and Operating Conditions – Application to Aqueous Organic Electrolytes. Electrochimica Acta, 2021, 392, pp.138961. ⟨10.1016/j.electacta.2021.138961⟩. ⟨hal-03353804⟩

Collections

IFP
29 View
74 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More