Electrochemical estimation and control for lithium-ion battery health-aware fast charging
Journal article, 2018

Fast charging strategies have gained an increasing interest toward the convenience of battery applications but may unduly degrade or damage the batteries. To harness these competing objectives, including safety, lifetime, and charging time, this paper proposes a health-aware fast charging strategy synthesized from electrochemical system modeling and advanced control theory. The battery charging problem is formulated in a linear time-varying model predictive control algorithm. In this algorithm, a control-oriented electrochemical-thermal model is developed to predict the system dynamics. Constraints are explicitly imposed on physically meaningful state variables to protect the battery from hazardous operations. A moving horizon estimation algorithm is employed to monitor battery internal state information. Illustrative results demonstrate that the proposed charging strategy is able to largely reduce the charging time from its benchmarks while ensuring the satisfaction of health-related constraints.

Electrochemical model

lithium-ion (Li-ion) battery

fast charging

state estimation

moving horizon estimation (MHE)

model predictive control (MPC)

Author

Changfu Zou

Chalmers, Electrical Engineering, Systems and control, Automatic Control

Xiaosong Hu

Chongqing University

Zhongbao Wei

Nanyang Technological University

Torsten Wik

Chalmers, Electrical Engineering, Systems and control, Automatic Control

Bo Egardt

Chalmers, Electrical Engineering, Systems and control, Automatic Control

IEEE Transactions on Industrial Electronics

0278-0046 (ISSN)

Vol. 65 8 6635-6645

Subject Categories

Robotics

Control Engineering

Other Electrical Engineering, Electronic Engineering, Information Engineering

DOI

10.1109/TIE.2017.2772154

More information

Latest update

5/2/2018 1