期刊文献+

基于LIN总线的阀控式铅酸蓄电池管理系统设计 被引量:7

Design of valve regulated lead-acid battery management system based on LIN bus
下载PDF
导出
摘要 电池管理系统作为电动汽车重要的组成部件之一,被广泛地用于汽车电池组管理中,来确保电池的高性能、高可靠性和高稳定性。电池管理系统能够保护电池免受破坏,预测电池寿命以及在电池工作的情况下维护和保养电池。由于铅酸蓄电池充放电过程的复杂性和非线性,采用非线性最小二乘法回归得到电池的初始荷电状态。针对阀控式铅酸蓄电池,设计了基于本地互联网络的电池管理系统,在此基础上利用片上卡尔曼滤波算法对电池荷电状态进行在线修正。同时,介绍了电压采集模块,电流采集模块,温度采集模块,通信电路模块。验证试验结果表明,当电池荷电状态处于30%-70%范围内时,荷电状态平均相对误差为3%左右。 Battery management system (BMS), as one of important component in electric vehicle, is widely used in automotive battery management in order to ensure performance, high reliability and high stability. BMS can prevent battery from damage, predict battery state of health, and maintain battery in work condition. Due to the complex and nonlinear electrochemical process of lead-acid battery in charging and discharging, the initial battery state of charge (SOC) was obtained by non-linear least squares regression method (NLLSRM) in the paper. For valve regulated lead-acid battery (VRLA), a battery management system based on local interconnect network (LIN) was designed and on chip Kalman filter algorithm was employed to correct SOC on-line. At the same time, a detailed hardware circuit schemes of primary modules was introduced, including voltage sampling module, current sampling module, temperature sampling module, data transfer module. The validation experimental results show that the proposed lead-acid battery control unit is high credible and the SOC estimation average relative error is about 3% when the battery is 30%SOC to 70%SOC status.
出处 《电源技术》 CAS CSCD 北大核心 2011年第12期1562-1565,共4页 Chinese Journal of Power Sources
基金 重庆市科委自然科学基金计划资助项目(CSTC-2010BB2400 CSTC2010GGA063 CSTC2009BB2080)
关键词 铅酸蓄电池 荷电状态 LIN总线 非线性最小二乘法 卡尔曼滤波 lead-acid battery SOC LIN NLLSRM Kalman
  • 相关文献

参考文献4

  • 1SHUO T,MUNAN H,MINGGAO O.An experimental study and non- linear modeling of discharge I-V behavior of balve-regulated leadacid batteries[J]. IEEE Transactions on Energy Conversion, 2009, 24: 452-458.
  • 2林立南.一种新型电池组单体电池电压检测方法[J].传感器世界,2010,16(10):18-20. 被引量:11
  • 3乐浪,李革臣,朱磊,何银吉,李金录.卡尔曼滤波在电池检测中的应用[J].电源技术,2006,30(2):152-154. 被引量:3
  • 4VASEBI A, BATHAEE S M T, PARTOVIBAKHSH M. Predicting state of charge of lead-acid batteries for hybrid electric vehicles by extended Kalman filter [J]. Energy Conversion and Management, 2008, 49(1): 75-82.

二级参考文献8

共引文献12

同被引文献39

引证文献7

二级引证文献15

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部