Lifetime Prediction of Rechargeable Lithium-Ion Battery Using Multi-Physics and Multiscale Model

Prediction of the state of health (SOH) of lithium-ion batteries (LIBs) is attracting intensive attention in the everincreasing deployment of consumer electronics and electrical transportation. We develop an electrochemicalthermal-aging coupled model to forecast the lifetime of lithium-ion battery at room and elevated temperatures, in which Arrhenius empirical equation is adopted to describe the bidirectional dependence between electrochemical performance, thermal behavior and aging characteristics. Considering the internal behaviors (ions transport, inter/deintercalation reaction, side reactions) and external performance (voltage, temperature, capacity), our model predicts electrochemical performance and SOH at 25 and 45 degrees C. The simulated results well coincide with measured data of LIBs with LiNi0.6Co0.1Mn0.3O2 cathode and graphite anode. Parameters including capacity loss, surface film thickness, porosity, area resistance and heat generation are employed and analyzed. Aging reactions lead to the increase of battery resistance and decrease of porosity, which decelerate the lithiumion transport process and battery degrade performance. Additional resistance results in the temperature rise that in turn accelerates the ion diffusion and side reactions, which reflects the complex electrical, thermal and aging interplay. This modeling methodology provides effective strategy for the design and optimization of lithium-ion batteries.