不同开路电压松弛时间下基于等效电路解构的锂离子电池荷电状态估计（英文）

发布时间：2018-05-03 18:52

本文选题：锂离子电池 + 开路电压　；参考：《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》2017年04期

【摘要】：目的:开路电压是基于模型的电池荷电状态估计的必要参数,其测试耗时大、效率低。本文旨在测试各种电压松弛时间的荷电状态-开路电压关系,研究其对开路电压法和等效电路模型的荷电状态估计准确度的影响,提高开路电压测试效率。创新点:1.通过电路解构方法,将二阶阻容电路分解为简单路,运用二阶段递推最小二乘法辨识电路模型的参数;2.基于递推最小二乘法和卡尔曼滤波算法,建立电路参数辨识和荷电状态估计的的联合自适应算法,研究电池电压松弛时间对基于等效电路模型的荷电状态估计的影响。方法:1.通过电路解构技术和理论推导,构建辨识二阶阻容等效电路参数的二阶段递推最小二乘法辨识方法(图2和公式(4)~(9));2.将二阶段递推最小二乘法和扩展卡尔曼滤波器集成,建立适应工况变化的电池模型参数辨识和状态估计的联合算法(图3);3.通过电池测试,建立多温度和多电压松弛时间的荷电状态与开路电压的关系,驱动自适应联合算法,获得既保证荷电状态估计准确度,又缩短开路电压测试时间的电压松弛时间。结论:1.二阶段递推最小二乘法既能简化矩阵计算,又能够保证电路参数的辨识非负性;2.联合自适应算法能够适应工况变化辨识模型参数和估计荷电状态;3.联合自适应算法的结果表明,5 min的电压松弛时间既能保证荷电状态估计性能,又能极大地提高开路电压测试效率。
[Abstract]:Aim: open circuit voltage is a necessary parameter for battery charge state estimation based on model, which is time-consuming and inefficient. The purpose of this paper is to test the charge state open circuit voltage relation of various voltage relaxation times, to study its influence on the accuracy of charge state estimation of open circuit voltage method and equivalent circuit model, and to improve the efficiency of open circuit voltage measurement. The innovation point is 1: 1. The second order resistive and capacitive circuit is decomposed into a simple circuit by the method of circuit deconstruction, and the parameters of the circuit model are identified by using the two-stage recursive least square method. Based on recursive least square method and Kalman filter algorithm, a combined adaptive algorithm for circuit parameter identification and charge state estimation is established to study the effect of battery voltage relaxation time on charge state estimation based on equivalent circuit model. Method 1: 1. By means of circuit deconstruction technique and theoretical derivation, a two-stage recursive least square method for identifying the parameters of second-order resistive and capacitive equivalent circuits is constructed (Fig. 2 and formula 4). The two-stage recursive least square method and extended Kalman filter are integrated to establish a joint algorithm for parameter identification and state estimation of battery model with varying operating conditions (figure 3 / 3). Through battery test, the relationship between charge state and open circuit voltage of multi-temperature and multi-voltage relaxation time is established, and the self-adaptive joint algorithm is driven to obtain the accuracy of state estimation. It also shortens the voltage relaxation time of open circuit voltage test time. Conclusion 1. The two-stage recursive least square method can not only simplify the matrix calculation, but also guarantee the nonnegative identification of circuit parameters. The combined adaptive algorithm can be used to identify the parameters of the model and estimate the charged state. The results of the combined adaptive algorithm show that the voltage relaxation time of 5 min can not only guarantee the performance of state estimation, but also greatly improve the efficiency of open circuit voltage measurement.
【作者单位】： Collaborative
【基金】：Project supported by the National Natural Science Foundation of China(No.51677006)
【分类号】：TM912

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