Research on Lithium-Ion Battery Electrode Particles Cracking Mechanism Considering Solid-Phase Diffusion-Induced Stress
Kong Chun1, Zhu Guorong1,2, Wei Xueliang3, Wang Jing1, Kang Jianqiang4,5, Wang Qian1
1. State Key Laboratory of Maritime Technology and Safety Wuhan University of Technology Wuhan 430070 China; 2. School of Automation Wuhan University of Technology Wuhan 430070 China; 3. College of Artificial Intelligence China University of Petroleum (Beijing) Beijing 102249 China; 4. Hubei Key Laboratory of Advanced Technology for Automotive Components Wuhan University of Technology Wuhan 430070 China; 5. Hubei Collaborative Innovation Center for Automotive Components Technology Wuhan University of Technology Wuhan 430070 China
Abstract：Loss of electrode active material in lithium-ion batteries is one of the main causes of lithium-ion battery degradation, and electrode particle rupture is in turn the main mechanism leading to electrode active material loss.However, it is difficult to directly observe the state of electrode particles during charge and discharge. Therefore, this paper proposes a fractional-order model with electrolyte considering stress (FOMeS) to observe the lithium-ion concentration and stress changes in electrode particles. Furthermore, the electrode particle cracking model is proposed based on FOMeS and the material properties of the electrode particles. The accuracy of the proposed model is indirectly verified through NCA (LiNi0.8Co0.15Al0.05O2) battery cycling aging experiments. Firstly, to achieve accurate internal state observation in lithium-ion batteries, a fractional-order model with electrolyte (FOMe) is proposed. FOMe is a simplified electrochemical lithium-ion batteries model based on single particle model, which simplifies solid-phase lithium-ion diffusion with fractional-order Padé approximation, and simplifies electrolyte-phase lithium-ion diffusion with two state-space systems. FOMe achieves accurate lithium-ion concentration prediction in solid phase and electrolyte phase with low computational complex. Secondly, the lithium-ion concentration distribution in electrode particles affects the solid-phase diffusion-induced stresses, and the strain of electrode particles affects the solid-phase lithium-ion concentration distribution. To establish the relationship between the stress, the strain and the lithium-ion concentration in electrode particles, a fractional-order model with electrolyte considering stress (FOMeS) is proposed. To verify the effectiveness of FOMeS, a NCA lithium-ion battery aging experiment is designed. The 1/30C constant current discharge voltage data is used to identify the thermodynamic parameters of NCA batteries in different aging stages with particle swarm optimization. The positive and negative electrodecapacitiesidentified from the experiment are highly consistent with the positive and negative electrode capacities predicted from FOMeS. The positive electrode capacity RMSE and MAPE of FOMeS are 0.073 9 A·h and 1.373 4%, respectively. The negative electrode capacity RMSE and MAPE of FOMeS are 0.260 2 A·h and 3.178 5%, respectively. The experiment result shows that FOMeS achieves accurate lithium-ion concentration and solid phase diffusion-induced stress prediction. Finally, to further investigate the effect of solid-phase diffusion-induced stress on the crack growth trend of electrode particles, the electrode particle cracking model is proposed. The proposed model combines the solid phase diffusion-induced stress based on FOMeS with the material properties of the electrode particles, the crack growth rate of the electrode particles can be calculated by the Paris equation. The stress and strain of electrode particles are simulated at 1C rate constant current charge and discharge. The simulation results show that the crack growth rate of electrode particles accelerates with the deepening of the crack length of electrode particles. For the NCA battery used in the experiment, the radius of negative electrode particles is larger than that of positive electrode particles, the solid-phase diffusion coefficient of negative electrode particles is smaller than that of positive electrode particles, and the Young's modulus of negative electrode particles is smaller than that of positive electrode particles. Therefore, the growth rate of crack propagation in negative electrode particles is faster than that in positive electrode particles. There are some conclusions can be made: (1) Compared with FOMe, FOMeS provides a more realistic response to the effect of electrode particle strain on lithium-ion concentration in electrode particles. (2) The aging battery experiments show that FOMeS accurately describes the stress trend of electrode particles and the loss of electrode capacity. (3) The electrode cracking model achieves the electrode particle crack growth simulation and predict the electrode particle crack growth trend.
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2025, Vol. 40 
