Internal temperature estimation of lithium-ion battery based on improved electro-thermal coupling model and ANFIS

Abstract

Accurate estimation of the internal temperature of lithium-ion batteries plays an important role in the development of a suitable battery thermal management system, safeguarding the healthy and safe operation of batteries, and improving battery performance. In order to accurately estimate the internal temperature of the battery, this paper proposes a method for estimating the internal temperature of lithium-ion batteries based on an improved electro-thermal coupling model and an Adaptive Network-based Fuzzy Inference System (ANFIS). First, a parameterization method of the electrical model is proposed, and an electrical model whose parameters are affected by temperature and SOC is established. Second, to overcome the complex nonlinear modeling problem of lithium-ion batteries, the ANFIS thermal model is established. Then, an improved electro-thermal coupling model for lithium-ion batteries is established by combining the proposed electrical model and the ANFIS thermal model to improve the accuracy of estimating the internal temperature of the battery. Finally, the effectiveness of the proposed method is verified by simulation and experiment.