zhan-sheng guo's blog
Data-Driven State of Health Estimation for Lithium-Ion Batteries Based on Universal Feature Selection
A simple yet effective health indicator (HI)-based data-driven model forecasting the state of health (SOH) of lithium-ion batteries (LIBs) and thus enabling their efficient management is developed. Five HIs with high physical significance and predictive power extracted from voltage, current, and temperature profiles are used as model inputs. The generalizability and robustness of the proposed ridge regression–based linear regularization model are assessed using three NASA datasets containing information on the behavior of batteries over a wide range of temperatures and discharge rates.
Elastoplastic model for chemo-mechanical behavior of porous electrodes using image-based microstructure
The microstructure of electrodes is intrinsically complex and thus should be determined prior to the analysis of the chemo-mechanical performance during charge/discharge cycles. In this study, a microstructurally resolved, fully coupled chemo-mechanical model was developed to investigate the structure–property relationship of electrodes in the framework of elastoplastic finite deformation.
Analytical Model and Experimental Verification of the Interfacial Peeling Strength of Electrodes
Background
The interfacial peeling strength of lithium-ion battery electrodes is a very important mechanical property that significantly affects the electrochemical performance of battery cells.
Objective
To characterize the interfacial peeling strength of an electrode, an analytical model based on the energy balance principle is established by considering the state of charge (SOC), the energy release rate, the tensile stiffness, and the peeling angle.
Simulation of crack behavior of secondary particles in Li-ion battery electrodes during lithiation/de-lithiation cycles
The loss of connectivity in particle-based LiMO2 (M = Ni, Co, Al, and/or Mn) electrodes due to mechanical failure
and fracture at the interface between primary particles is one of the major causes of capacity fading in Li-ion
batteries (LIBs) after certain electrochemical cycles. In this study, a model of a secondary particle composed
of randomly distributed primary particles is established using a fractal algorithm. The finite element method
with cohesive crack modeling is employed to simulate the intraparticle fracture within the secondary particle.