Joint structural and electrochemical modeling: Impact of porosity on lithium-ion battery performance

Abstract

Future increases of energy density of lithium-ion batteries require a systematic optimization of electrode structure and the related production process. Such optimization is facilitated by electrochemical models which predict cell performance with good accuracy. In this work, classic relations of structure to model parameters in the classical Doyle-Newman electrode model are replaced to improve the prediction accuracy of the model regarding electrode structure effects. Therefor, a 3D micro structure model is used to derive effective electrode property relations for ionic and electric conductivity, which are then used in the computationally efficient P2D framework of the Doyle-Newman model. Simulations show clearly the transition from an electron transport limited to an ion transport limited electrode performance with increasing compression ratio. Integrating the derived algebraic structure-model parameter relations into the electrochemical model allows a higher accuracy in predicting the optimal porosity of the experimental data compared to the classical P2D model.