专题论文

电动汽车锂离子电池管理系统的关键技术

  • 卢兰光 ,
  • 李建秋 ,
  • 华剑锋 ,
  • 欧阳明高
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  • 1. 清华大学汽车安全与节能国家重点实验室, 北京 100084;
    2. 北京科易动力科技有限公司, 北京 100096
卢兰光,博士,研究方向为新型动力系统,电子信箱:lulg@mail.tsinghua.edu.cn

收稿日期: 2016-02-03

  修回日期: 2016-02-20

  网络出版日期: 2016-04-14

基金资助

中美清洁能源联合研究中心清洁能源汽车项目(2014DFG71590)

A review on the key issues of the lithium-ion battery management

  • LU Languang ,
  • LI Jianqiu ,
  • HUA Jianfeng ,
  • OUYANG Minggao
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  • 1. StateKey Laboratory of Automotive Safety & Energy, Tsinghua University, Beijing 100084, China;
    2. Key Power Technology Co., Ltd., Beijing 100096, China

Received date: 2016-02-03

  Revised date: 2016-02-20

  Online published: 2016-04-14

摘要

锂离子电池具有能量密度高、功率密度高、寿命长、环保等特点,已经在电动汽车中获得应用。但电动汽车锂离子电池组的容量大、串并联节数多、安全工作区域有限,需要电池管理系统对其进行有效控制与管理,以充分保证电池的安全性、耐久性和动力性。电池管理系统由各种传感器、执行器、控制器等构成,其关键技术包括:传感器的精度及传感器之间的同步技术、电池单体及电池组的状态(荷电状态、健康状态、功能状态、能量状态、安全状态等)估计技术、电池组一致性辨识与均衡技术、安全充电和故障诊断技术。为了研发先进的电池管理系统,首先要对锂离子电池性能进行测试研究,确定影响其性能的主要因素及变化规律;然后采用基于机理、半经验或经验的建模方法建立电池系统模型,设计基于模型的电池系统状态估计及性能优化管理算法,并进行系统集成和应用开发,以保证在电池安全可靠运行的前提下发挥出最佳的动力性能。

本文引用格式

卢兰光 , 李建秋 , 华剑锋 , 欧阳明高 . 电动汽车锂离子电池管理系统的关键技术[J]. 科技导报, 2016 , 34(6) : 39 -51 . DOI: 10.3981/j.issn.1000-7857.2016.06.004

Abstract

Lithium ion battery is widely used in new energy vehicles, given its high energy/power density, extended longevity, and environment friendliness. However, composed of hundreds of lithium ion cells, the battery system is very complex and subject to many safety constraints. Therefore, safety, durability and power output capability of lithium ion batteries must be well managed on board. It is essential for a battery management system (BMS) to guarantee that the lithium ion battery works within safe status, thereby ensuring safety, durability and power output capability of the lithium ion battery system. A typical BMS is composed of sensors, actuators, controllers, etc. The key technologies of the BMS include: sensor and signal synchronization, state estimation of cell and battery pack (state of charge-SOC, state of health-SOH, state of function-SOF, state of energy-SOE, and state of safety-SOS), cell variation identification and balancing, safe charging control, fault diagnosis, etc. Advanced BMS design requires systematic research of battery mechanism and long-time technological accumulation. Basically, performance tests and researches are essential to the characteristics and mechanisms of safety, durability and power output capability of lithium ion battery. Based on deep understanding of the battery performance, semi-empirical and empirical models can be established for cell and battery systems. Furthermore, model-based state estimation and performance optimization algorithms can be developed in BMS integration and design, and the battery system can thus safely work at its optimal status.

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