Integrated Optimal Fast Charging and Active Thermal Management of Lithium-Ion Batteries in Extreme Ambient Temperatures

TL;DR

This paper develops an integrated control strategy combining optimal fast charging with active thermal management for Lithium-ion batteries, effectively balancing charging speed and battery health in extreme temperatures.

Contribution

It introduces a control-oriented thermal-NDC battery model and develops a model predictive control algorithm for simultaneous thermal management and fast charging.

Findings

The control strategy improves energy efficiency during charging.

The algorithms maintain battery health in extreme ambient temperatures.

Numerical experiments confirm effectiveness and robustness.

Abstract

This paper presents an integrated control strategy for optimal fast charging and active thermal management of Lithium-ion batteries in extreme ambient temperatures, striking a balance between charging speed and battery health. A control-oriented thermal-NDC (nonlinear double-capacitor) battery model is proposed to describe the electrical and thermal dynamics, incorporating the effects of both an active thermal source and ambient temperature. A state-feedback model predictive control algorithm is then developed for optimal fast charging and active thermal management. Numerical experiments validate the algorithm under extreme temperatures, showing that the proposed algorithm can energy-efficiently adjust the battery temperature, thereby balancing charging speed and battery health. Additionally, an output-feedback model predictive control algorithm with an extended Kalman filter is proposed for battery charging when states are partially measurable. Numerical experiments validate the effectiveness under extreme temperatures.