Improved electric-thermal-aging multi-physics domain coupling modeling and identification decoupling of complex kinetic processes based on timescale quantification in lithium-ion batteries

Abstract

Unraveling the kinetic behavior inside the battery is essential to break through the limitations of mechanistic studies and to optimize the control of the integrated management system. Given this fact that the battery system is multi-domain coupled and highly nonlinear, an improved lumped parameter multi-physical domain coupling model is first developed to capture the electrical, thermal and aging characteristics of the battery in this paper. On this basis, an adaptive multi-timescale decoupled identification and estimation strategy is proposed based on the quantified timescale innovation, which realizes the online monitoring of the battery state and the accurate identification of the model parameters. The specific idea is that the decoupled identification of kinetic parameters inside the cell, the terminal voltage prediction and the real-time monitoring of the internal temperature with the online estimation of the available capacity are distinguished under different timescales. Meanwhile, the response time characteristic of the different kinetics is extracted and analyzed as a distinction between the coupled internal electrochemical processes. In this idea, four functionally different sub-observers are developed independently. Significantly, adaptive time-scale driven methods designed based on the fundamental timescale of the system, the amount of variation of the state of charge, and the amount of transfer charge are used separately for the observer implementation at different timescales. In addition, the coupling of the fast and slow kinetic parameter discriminators is achieved by diffusion voltage, and the internal temperature observer as well as the available capacity observer are coupled to each other based on the estimation results. Experimental results for two long-time operating conditions at 5, 25 and 45 °C show that the proposed strategy has fast convergence and reliable accuracy in monitoring the battery state characteristics. Compared with the traditional fixed timescale algorithm, the proposed multi-physics domain coupling modeling strategy based on independent timescale driven design is more competitive in practical embedded applications.