| 引用本文: | 柳应全,鲁军勇,龙鑫林,等.储能用蓄电池模型参数的动态辨识.[J].国防科技大学学报,2019,41(5):87-92.[点击复制] |
| LIU Yingquan,LU Junyong,LONG Xinlin,et al.Dynamic identification of model parameters for energy storage batteries[J].Journal of National University of Defense Technology,2019,41(5):87-92[点击复制] |
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| 储能用蓄电池模型参数的动态辨识 |
| 柳应全, 鲁军勇, 龙鑫林, 魏静波, 周仁, 吴羿廷 |
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(海军工程大学 舰船综合电力技术国防科技重点实验室， 湖北 武汉 430033)
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| 摘要: |
| 为观测锂离子电池的参数，通过建立多元线性回归模型对内电路参数进行辨识，并提出通过间接观测蓄电池平衡电动势来辨识荷电状态的方法。该方法基于改进的Thevenin电池模型，以等效电容量来表征锂电池的容量特性。在循环周期内可通过测量放电前后开路电压变化量和电荷变化量来辨识等效电容；等效电容又可以在短时间内动态估算平衡电动势以作为辨识荷电状态的主要变量。通过一个循环周期内的脉冲放电实验验证了所采用的改进电池模型和辨识方法的有效性和准确性。 |
| 关键词: 线性回归 电池管理 荷电状态估算 参数辨识 平衡电动势 等效电容 |
| DOI：10.11887/j.cn.201905013 |
| 投稿日期：2018-04-25 |
| 基金项目:国家自然科学基金资助项目（51522706，51607187）；国家部委基金资助项目（613262） |
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| Dynamic identification of model parameters for energy storage batteries |
| LIU Yingquan, LU Junyong, LONG Xinlin, WEI Jingbo, ZHOU Ren, WU Yiting |
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(National Key Laboratory of Science and Technology on Vessel Integrated Power System, Naval University of Engineering, Wuhan 430033, China)
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| Abstract: |
| As the important indices for reflecting the comprehensive performance of the battery, the parameters of lithium-ion are unavailable by direct observation. Through identifying internal circuit parameters by establishing multiple linear regression model, a new method for the state of charge estimation of lithium-ion batteries by indirectly observing the batteries balance electromotive force was proposed. The equivalent capacitance was introduced to represent capacity character of lithium-ion batteries in this new method, which was based on an improved Thevenin battery model. Through measuring changes of open-circuit voltage and charge before and after the discharge process in a cycle period, the equivalent capacitance can be recognized in a long time scale. As the main variable for estimating state of charge, the balance electromotive force can be dynamically estimated through the equivalent capacitance in a short time scale. Finally, a pulse discharging experiment of a cycle period verified the effectiveness and accuracy of the improved battery model and the proposed dynamic identification method. |
| Keywords: linear regress battery management state of charge estimation parameter identification balance electromotive force equivalent capacitance |
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