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电动汽车电池热管理系统的机器学习建模与优化综述

郭洪飞 崔宇 张锐

计算机工程与应用2026,Vol.62Issue(16):1-20,20.
计算机工程与应用2026,Vol.62Issue(16):1-20,20.DOI:10.3778/j.issn.1002-8331.2509-0387

电动汽车电池热管理系统的机器学习建模与优化综述

Review on Machine Learning Modeling and Optimization of Battery Thermal Management Systems for Electric Vehicles

郭洪飞 1崔宇 1张锐2

作者信息

  • 1. 内蒙古工业大学 智能科学与技术学院,呼和浩特 010080
  • 2. 天津科技大学 电子信息与自动化学院,天津 300222
  • 折叠

摘要

Abstract

The battery thermal management system(BTMS)is a key subsystem that ensures the safe operation,energy efficiency,and longevity of traction batteries in electric vehicles.Traditional physics-based methods rely on fine-grained modeling and parameter tuning,and under complex operating conditions they often suffer from model mismatch,limited real-time performance,and high computational cost.With advances in sensing and computing,machine learning has been widely applied to thermal-state modeling,thermal anomaly detection,and cooling-control optimization,and has also driven the adoption of lightweight techniques,such as model compression,quantization,and distillation on in-vehicle embedded platforms.This paper systematically reviews related progress of machine learning in thermal state modeling and prediction:Supervised learning shows clear advantages in temperature prediction,unsupervised and semi-supervised learning per-form well in thermal anomaly detection,and reinforcement learning exhibits adaptive strengths in optimizing cooling-control strategies.By comparing trade-offs among accuracy,real-time capability,and computational demand,this paper emphasizes that physics-data integration and lightweight implementation are pivotal for engineering deployability.Over-all,machine learning complements traditional approaches,improves prediction and control performance,and provides guidance for the intelligent development and engineering application of BTMS.

关键词

电动汽车/电池热管理系统/机器学习/强化学习

Key words

electric vehicle/battery thermal management system/machine learning/reinforcement learning

分类

信息技术与安全科学

引用本文复制引用

郭洪飞,崔宇,张锐..电动汽车电池热管理系统的机器学习建模与优化综述[J].计算机工程与应用,2026,62(16):1-20,20.

基金项目

国家自然科学基金(52465061) (52465061)

内蒙古自治区自然科学基金重点项目(2024ZD26) (2024ZD26)

国家外国专家项目(S20240366) (S20240366)

内蒙古自治区重点研发和成果转化计划项目(2023YFJM0007) (2023YFJM0007)

准格尔旗重点研发计划项目(2024YF-01) (2024YF-01)

内蒙古自治区研究生教育教学改革项目(JG2024034C) (JG2024034C)

2025年重点研发和成果转化计划(社会公益领域)项目(2025YFSH0070). (社会公益领域)

计算机工程与应用

1002-8331

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