【摘要】 磷酸铁锂电池作为我国电动汽车用动力电池的主要形式,得到广泛的研究和应用。电池负荷状态(SOC)估计是锂离子电池智能管理系统(BMS)研究的难点和重点;锂离子电池在使用过程中,工况具有很大的不确定性,而SOC用到的电池参数模型和使用工况又有很大的关系,因此本文利用自适应原理,在电池的实际使用过程中,不断的去采集电池状态信息,修正电池模型参数,适应不同的工况,完善SOC估计的功能。本文的设计思路是通过自适应测量,修正开路电压-荷电状态(OCV)曲线、实际电池容量和电池内阻曲线,然后根据修正后的参数结合安时计算方法进行综合估算,以便在电池整个寿命过程中都能判断电池状态和进行负荷状态估计(SOC)。更多还原

【Abstract】 Lithium ion battery is the most common electrical energy storage devices in EVS. The battery management system (BMS) has been the topic of recent research in EV system, and one of the important parameters is the estimating the state of charge (SOC). Accurate estimation of SOC is difficult, because the operation condition of EV is in a wide rage. The model of battery will change as the operation and aging of the EV. This research designing a self-adaptive system to measurement the coefficients of battery follow the operation and aging. The amendment of open circuit voltage (OCV) and internal resistance will be achieved by the measurement. The amendment model and current integration technique are used to estimate the SOC.更多还原