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首页> 外文期刊>Journal of Mechatronics, Electrical Power, and Vehicular Technology >Comparative Study Between Internal Ohmic Resistance and Capacity for Battery State of Health Estimation
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Comparative Study Between Internal Ohmic Resistance and Capacity for Battery State of Health Estimation

机译:内部欧姆电阻与电池健康状态估计能力的比较研究

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In order to avoid battery failure, a battery management system (BMS) is necessary. Battery state of charge (SOC) and state of health (SOH) are part of information provided by a BMS. This research analyzes methods to estimate SOH based lithium polymer battery on change of its internal resistance and its capacity. Recursive least square (RLS) algorithm was used to estimate internal ohmic resistance while coloumb counting was used to predict the change in the battery capacity. For the estimation algorithm, the battery terminal voltage and current are set as the input variables. Some tests including static capacity test, pulse test, pulse variation test and before charge-discharge test have been conducted to obtain the required data. After comparing the two methods, the obtained results show that SOH estimation based on coloumb counting provides better accuracy than SOH estimation based on internal ohmic resistance. However, the SOH estimation based on internal ohmic resistance is faster and more reliable for real application.
机译:为了避免电池故障,必须使用电池管理系统(BMS)。电池充电状态(SOC)和健康状态(SOH)是BMS提供的信息的一部分。本研究分析了基于SOH的锂聚合物电池内阻和容量变化的估算方法。递归最小二乘(RLS)算法用于估计内部欧姆电阻,而库仑计数用于预测电池容量的变化。对于估计算法,将电池端子电压和电流设置为输入变量。已经进行了一些测试,包括静态电容测试,脉冲测试,脉冲变化测试以及充放电测试之前,以获得所需的数据。比较这两种方法后,获得的结果表明,基于库仑计数的SOH估计比基于内部欧姆电阻的SOH估计具有更好的准确性。但是,基于内部欧姆电阻的SOH估算对于实际应用来说更快,更可靠。

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