Co-Estimation of State of Charge and State of Health for Lithium-Ion Batteries Based on Fractional-Order Calculus
Journal article, 2018

Lithium-ion batteries have emerged as the state-of-The-Art energy storage for portable electronics, electrified vehicles, and smart grids. An enabling Battery Management System holds the key for efficient and reliable system operation, in which State-of-Charge (SOC) estimation and State-of-Health (SOH) monitoring are of particular importance. In this paper, an SOC and SOH co-estimation scheme is proposed based on the fractional-order calculus. First, a fractional-order equivalent circuit model is established and parameterized using a Hybrid Genetic Algorithm/Particle Swarm Optimization method. This model is capable of predicting the voltage response with a root-mean-squared error less than 10 mV under various driving-cycle-based tests. Comparative studies show that it improves the modeling accuracy appreciably from its second-and third-order counterparts. Then, a dual fractional-order extended Kalman filter is put forward to realize simultaneous SOC and SOH estimation. Extensive experimental results show that the maximum steady-state errors of SOC and SOH estimation can be achieved within 1%, in the presence of initial deviation, noise, and disturbance. The resilience of the co-estimation scheme against battery aging is also verified through experimentation.

state of charge


fractional-order calculus

state of health

estimator design


Xiaosong Hu

Chongqing University

Hao Yuan

Tongji University

Changfu Zou

Chalmers, Electrical Engineering, Systems and control, Automatic Control

Zhe Li

Tsinghua University

Lei Zhang

Beijing Institute of Technology

IEEE Transactions on Vehicular Technology

0018-9545 (ISSN)

Vol. 67 11 10319-10329 8437167

Subject Categories

Probability Theory and Statistics

Control Engineering

Signal Processing



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