A real-time feedback and adaptive control strategy for battery thermal management system

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Impact Factor:9.4

DOI number:10.1016/j.energy.2025.137148

Journal:Energy

Key Words:Electric vehicles; Battery thermal management; Thermal safety; AMPC

Abstract:The control of a battery thermal management system (BTMS) is critical for ensuring thermal safety, energy efficiency, and prolonged service life of electric vehicles. To explore the coordination optimization between battery thermal safety and comprehensive energy consumption, this paper proposes a real-time feedback and adaptive control strategy based on Adaptive Model Predictive Control (AMPC). First, a computational fluid dynamics (CFD) model of the battery pack is established and verified under dynamic operating conditions and temperature variations. In the proposed real-time AMPC framework, accurate feedback of the battery temperature distribution is provided by real-time multiphysics simulations. The thermal parameters of the battery are adaptively updated online to precisely predict battery thermal states. A cost function consisting of the battery temperature, battery aging cost, and cooling cost is minimized to obtain the optimal flow velocity of the liquid cooling system. The results show that the proposed method reduces cooling energy consumption by 26.9%,limits temperature fluctuations to between 0.031 and 0.040 K, and reduces battery aging rate by up to 22%.

Note:中科院1区Top

Co-author:Haonan Tian,Muyao Wu,Yangrui Qiu,Heng Li

First Author:Xinrui Fang

Indexed by:Journal paper

Correspondence Author:Li Wang

Document Code:137148

Discipline:Engineering

Document Type:J

Volume:333

ISSN No.:0360-5442

Translation or Not:no

Date of Publication:2025-06-29

Included Journals:SCI、EI

Links to published journals:https://www.sciencedirect.com/science/article/pii/S0360544225027902