Energy Storage Science and Technology ›› 2023, Vol. 12 ›› Issue (9): 2904-2916.doi: 10.19799/j.cnki.2095-4239.2023.0342

• Energy Storage Test: Methods and Evaluation • Previous Articles     Next Articles

State of charge estimation for lithium batteries based on an improved electrochemical model at a wide temperature environment

Jiangwei SHEN1(), Canbiao ZHOU1, Xing SHU1, Zheng CHEN1(), Yonggang LIU2   

  1. 1.Faculty of Transportation Engineering Kunming University of Science and Technology, Kunming 650000, Yunnan, China
    2.College of Mechanical Engineering Chongqing University, Chongqing 400030, China
  • Received:2023-05-16 Revised:2023-06-07 Online:2023-09-05 Published:2023-09-16
  • Contact: Zheng CHEN E-mail:shenjiangwei6@kust.edu.cn;chen@kust.edu.cn

Abstract:

In order to improve the practicability of the electrochemical model and its applicability at complex temperature environments and solve the problem of difficulty in quickly and accurately estimating the internal state of lithium-ion batteries, a state-of-charge estimation method based on an improved electrochemical model is designed. First, the order reduction of the solid-liquid phase equation of the electrochemical model is solved using the finite difference method and Galerkin method to explain the real-time state of lithium-ion concentration in the battery. Simultaneously, the equivalent circuit model is integrated further, and two RC network structures are used to characterize the internal polarization process of the battery. The temperature-dependent characteristics are included to form a low-order ordinary differential system suitable for the state of charge estimation, realizing effective simplification and order reduction of the electrochemical model and saving the calculation cost. Then, to address the model uncertainty caused by model simplification and reduce noise interference, a square root volume Kalman filter was introduced to design a lithium battery state of charge estimation algorithm at full operating temperature. The results showed that the proposed state of charge estimation method based on the improved electrochemical model could accurately estimate the state of charge under different temperatures and complex working conditions, with a maximum error of less than 1.6% under diverse temperature settings.

Key words: lithium ion battery, electrochemical mode, ambient temperature, state of charge, square root cubature kalman filte

CLC Number: