Charging pattern optimization for lithium-ion batteries with an electrothermal-aging model
Artikel i vetenskaplig tidskrift, 2018

This paper applies advanced battery modeling and multiobjective constrained nonlinear optimization techniques to derive suitable charging patterns for lithium-ion batteries. Three important yet competing charging objectives, including battery health, charging time, and energy conversion efficiency, are taken into account simultaneously. These optimization objectives are first subject to a high-fidelity battery model that is synthesized from recently developed individual electrical, thermal, and aging models. The coupling relationship and multiple timescales among different model dynamics are identified. Furthermore, constraints are imposed explicitly on the current, voltage, state-of-charge, and temperature. Such a complex charging problem is solved by using an ensemble multiobjective biogeography-based optimization approach. As a result, two charging patterns, namely the constant current-constant voltage (CC-CV) and multistage CC-CV, are optimized to balance various combinations of charging objectives. Different tradeoffs and sensitive elements are compared and analyzed based on the Pareto frontiers. Illustrative results demonstrate that the proposed strategy can effectively offer feasible health-conscious charging with desirable tradeoffs among charging speed and energy conversion efficiency under different demand priorities.

lithium-ion (Li-ion) batteries

electric vehicles (EVs)

Battery charging optimization

fast charging

electrothermal-aging model

Författare

Kailong Liu

The University of Warwick

Changfu Zou

Chalmers, Elektroteknik, System- och reglerteknik, Reglerteknik

Kang Li

University of Leeds

Torsten Wik

Chalmers, Elektroteknik, System- och reglerteknik, Reglerteknik

IEEE Transactions on Industrial Informatics

1551-3203 (ISSN)

Vol. 14 12 5463-5474 8444057

Ämneskategorier

Beräkningsmatematik

Annan fysik

Annan elektroteknik och elektronik

DOI

10.1109/TII.2018.2866493

Mer information

Senast uppdaterat

2019-01-10