干式荷电铅酸蓄电池健康状态的有效检测路径探究

Study on Effective Detection Path of Dry Charged Lead-acid Battery Health Status

干式荷电铅酸蓄电池的健康状态与其荷电状态、使用寿命、老化程度密切相关,荷电状态的评估指标为蓄电池的SOC,老化程度的评价指标为SOH,使用寿命的评价依据为电池的有效循环次数。检测SOC指标时需建立电池的等效电路模型,利用HPPC识别电池的欧姆内阻、极化电阻、极化电容3个关键参数,然后代入计算式求得开路电压,再根据SOC-OCV对照关系求得SOC。检测SOH指标时需在任意放电电流和标准放电电流间建立等效关系式,然后运用关系式换算,将SOC引入计算式中,建立SOC和SOH的逻辑关系。使用寿命预测中利用SVM核函数建立电池使用规律模型,从而预测电池的健康状态。

The health status of dry charged lead-acid battery is closely related to its state of charge,service life and aging degree.The evaluation index of SOC of the battery is the evaluation index of SOC,the evaluation index of aging degree is SOH,and the evaluation of service life is based on the number of effective cycles of the battery.When detecting SOC index,it is necessary to establish the equivalent circuit model of the battery.HPPC is used to identify the three key parameters of the battery,namely ohmic internal resistance,polarization resistance and polarization capacitance,and then the open-circuit voltage is obtained by substituting them into the calculation formula,and then the SOC is calculated according to the control relationship between SOC and OCV.When detecting SOH index,it is necessary to establish the equivalent relation between arbitrary discharge current and standard discharge current,and then use the relation conversion to introduce SOC into the calculation formula,and establish the logical relation between SOC and SOH.In service life prediction,the SVM kernel function is used to establish the battery service rule model,so as to predict the health state of the battery.