An Estimation Method of Rechargeable Electric Quantity for Aging Battery Based on Joint Estimation of State and Model Parameters
Sun Jinlei1, Tang Chuanyu1, Li Lei1, Zhu Jinda2, Zhu Chunbo3
1. School of Automation Nanjing University of Science and Technology Nanjing 210094 China; 2. State Grid Electric Power Research Institute Nanjing 211106 China; 3. School of Electrical Engineering & Automation Harbin Institute of Technology Harbin 150001 China
Abstract：Battery energy storage system has been widely used in power systems. In order to ensure the operation effect of the battery energy storage system, it is important to accurately estimate the battery state. The rechargeable electric quantity of the battery determines the ability of energy storage to a certain extent. However, it is difficult to accurately reflect the actual rechargeable electric quantity of the battery only using external characteristic parameters, such as voltage, current and temperature. The problem of the rechargeable electric quantity estimation of batteries in different health states has been difficult to solve, especially in different aging states. In this paper, the concept of rechargeable electric quantity is proposed, the relationship between the rechargeable electric quantity and the open circuit voltage (OCV) is constructed, and the rechargeable electric quantity affected by DC internal resistance is analyzed based on the Thevenin equivalent circuit model. Besides, a joint estimation method of battery states and model parameters is proposed based on dual adaptive dual extended Kalman filter (ADEKF), which realizes the rechargeable electric quantity estimation of the battery in any aging state. Taking three batteries with different aging states as the research object, the battery state and model parameter estimation results are verified in the federal urban driving schedule (FUDS) operating condition, and the estimation results of the rechargeable electric quantity loss are verified at 0.5C constant current charging. The experimental results show that for the new cell, the estimation error of the rechargeable electric quantity is less than 1%, and the error affected by DC internal resistance is 0.031A·h. For the aged cell, the estimation error of the rechargeable electric quantity is 2.7%, and the error affected by DC internal resistance is 0.074A·h. The comparison of the state estimation of three batteries with different aging states at 0.5C constant current charging condition further verifies the effectiveness of the proposed method for electric quantity estimation.
孙金磊, 唐传雨, 李磊, 朱金大, 朱春波. 基于状态与模型参数联合估计的老化电充入电量估计方法[J]. 电工技术学报, 2022, 37(22): 5886-5898.
Sun Jinlei, Tang Chuanyu, Li Lei, Zhu Jinda, Zhu Chunbo. An Estimation Method of Rechargeable Electric Quantity for Aging Battery Based on Joint Estimation of State and Model Parameters. Transactions of China Electrotechnical Society, 2022, 37(22): 5886-5898.
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