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车用锂离子电池SOC估算算法的研究
引用本文:鲍可进,金玲.车用锂离子电池SOC估算算法的研究[J].计算机工程与科学,2012,34(12):169-173.
作者姓名:鲍可进  金玲
作者单位:江苏大学计算机科学与通信工程学院,江苏镇江,212013
摘    要:针对纯电动汽车的锂离子电池容量损失而导致估算电池电荷状态(SOC)精度降低的问题,本文分析了影响电池容量损失的因素,提出容量修正算法。通过改进电池模型,把电池容量作为状态变量,将电池容量修正算法运用于Kalman滤波算法估计SOC,解决了锂离子电池容量损耗使得误差累积的问题。实验证明,本文提出的基于容量修正的Kalman最优滤波算法提高了SOC估算的精度,并且对初始误差有很强的修正作用,可以保证纯电动汽车锂离子电池的稳定工作。

关 键 词:纯电动汽车  电池容量损耗  SOC估计  Kalman滤波算法

Study on SOC Estimation Algorithm of Lithium-ion Battery of Electric Vehicle
BAO Ke-jin , JIN Ling.Study on SOC Estimation Algorithm of Lithium-ion Battery of Electric Vehicle[J].Computer Engineering & Science,2012,34(12):169-173.
Authors:BAO Ke-jin  JIN Ling
Affiliation:(School of Computer Science and Telecommunication Engineering,Jiangsu University,Zhenjiang 212013,China)
Abstract:For the problem of SOC estimation accuracy reducing that is caused by the lithium-ion battery capacity losing in pure electric vehicle, the paper analyzes the influence factors of battery capacity losing and put forward a capacity correction algorithm. By improving battery model, the battery capacity is as state variables and the capacity correction algorithm is used in kalman filter to estimate the SOC. This solves the error accumulation problem that is caused by the lithium-ion battery capacity losing. The test proves that the based on the capacity fixed kalman optimal filter algorithm is of benefit to improving the accuracy of SOC estimation and performs well when initial error happens. The method can ensure the stability of lithium-ion of pure electric vehicle.
Keywords:pure electric vehicle  battery capacity losing  SOC estimation  Kalman filter algorithm
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