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State of Health Estimation for Lithium-ion Batteries Based on Random Forest

Sun Mengmeng;Xia Xuelei;Faculty of Transportation Engineering, Kunming University of Science and Technology;  
As the power source, lithium-ion battery is one of the key parts of electrical vehicles(EVs). Accurate estimation of state of health(SOH) for lithium-ion batteries to ensure safety and obtain high service life. In this paper, considering actual usage of lithium-ion battery in EVs, a novel SOH estimation method is proposed based on the current-voltage charging current curve. Then, a random forest(RF) model is built to achieve online SOH estimation. In addition, the BP neural network is applied for comparison of the SOH estimation precision. The results show that RF can achieve more accurate estimation of SOH, compared with the BP neural network model.
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