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电动汽车动力电池剩余电量在线测量 被引量:13

The Estimation of the State of Charge of Storage Battery Based on the Kalman Filtering Theory for Electric Vehicle
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摘要 为了精确可靠估算以蓄电池为动力的电动汽车所用电池的剩余电量,在讨论目前一些蓄电池剩余电量估算方法的基础上,以聚合物锂离子电池组为研究对象,将电池荷电状态作为系统的状态,建立了单变量的锂电池组的状态空间模型,采用了开路电压法和卡尔曼滤波递推算法相结合的方法。经试验这种方法能够获得蓄电池组精确和可靠的荷电状态预测值。 To estimate residual capacity of traction battery in electric vehicle accurately and reliably,the paper chooses a lithium-ion polymer battery pack as a research object,takes the SOC(State of charge) as the state of the system,and builds the battery's state space model with single state,and then develops a method combining open circuit voltage method and Kalman filtering recursive algorithm method,based on some methods of residual capacity estimation of battery often used at present. The experiments proved that accurate and reliable battery SOC estimation of battery could be obtained by adopting the new method.
出处 《电子测量与仪器学报》 CSCD 2008年第S2期182-185,共4页 Journal of Electronic Measurement and Instrumentation
基金 国家自然科学基金项目 60871088
关键词 聚合物锂离子电池组 卡尔曼滤波 电动汽车 荷电状态 Lithium-Ion Polymer Battery Kalman Filter Electric Vehicle State-of-charge
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参考文献9

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二级参考文献2

  • 1刘君华.离散时间控制系统[M].西安:西安交通大学出版社,1990.. 被引量:1
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