研究目的
To propose a model based on hysteretic characteristics of lithium-ion battery and use Cubature Kalman Filter (CKF) algorithm to estimate the SOC, which greatly reduces the model error and the algorithm error.
研究成果
The second-order RC hysteresis model can track the dynamic characteristics of lithium-ion battery more accurately even in the condition of the severe changes of current. CKF algorithm can accurately estimate the battery SOC even if model error is considerable, showing good robustness.
研究不足
The model and algorithm's performance under extreme conditions or different types of lithium-ion batteries is not explored.
1：Experimental Design and Method Selection:
The second-order RC hysteresis model is established through the test and analysis of lithium-ion battery hysteresis characteristics. The cubature Kalman filter algorithm is used to estimate the battery state of charge.
2：Sample Selection and Data Sources:
The LP2770102AC lithium-ion battery is chosen for testing. A Digatron MCT 30-05-40 cell cycler was used to test.
3：List of Experimental Equipment and Materials:
LP2770102AC lithium-ion battery, Digatron MCT 30-05-40 cell cycler.
4：Experimental Procedures and Operational Workflow:
The battery temperature is kept at 20 ± 2 °C. The battery voltage is assumed to keep stable value after standing for 1 hour in the charging and discharging test process.
5：Data Analysis Methods:
The recursive least squares method is used to estimate the parameters of the equivalent circuit model.
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