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中文摘要：
对蓄电池的荷电状态（state of charge,SOC）进行预测是蓄电池能量管理的前提。考虑蓄电池充放电电流、内部工作温度和充放电循环次数等因素的影响,结合卡尔曼滤波,提出了蓄电池SOC预测的改进能量-卡尔曼滤波算法。在蓄电池三阶动态模型的基础上,详细阐述了算法的计算步骤,并与传统的SOC预测方法进行了对比研究。仿真结果表明,改进的能量-卡尔曼预测算法可以有效跟踪蓄电池SOC的变化,其精度优于传统的预测方法。
英文摘要：
It is elementary to predict State of Charge（SOC） of battery for battery energy management.Considering the battery charge-discharge current,the internal temperature and the number of charge-discharge cycles and combining the Kalman Filtering,an improved energy-Kalman method was proposed,which integrated with Kalman filtering.Based on the three-order battery model,the paper described in detail the calculation steps of this new prediction method and compared with the traditional prediction methods.The results of simulation indicate that this method can effectively track the change of SOC and the algorithm is superior to the traditional methods in accuracy.
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