【摘要】 目的提出一种基于健康因子的SOH估计方法,以准确估计锂离子电池的健康状态。方法选取锂离子电池恒流充电过程中两恒定压差下的时间间隔作为健康因子,基于健康因子估计电池的健康状态。采用高斯过程回归模型进行电池健康状态估计,通过共轭参数法优化超参数。健康因子作为模型输入,输出相应的电池健康状态,并选取NASA不同实验条件下6个电池的实验数据验证该算法。结果所选6个电池估计结果的MAPE与RMSE值均低于0.02。结论选取的健康因子可以较好地表征电池的健康状态,验证了基于健康因子的SOH估计方法的可行性。该方法可以对不同温度、放电倍率、放电深度下的电池进行准确的SOH估计,具有较强的适用性。更多还原

【Abstract】 Objective To put forward a kind of SOH estimation method based on the health factors, to accurately estimate the health status of lithium ion batteries. Methods The time interval between two constant voltages during the constant current charging process was selected as the health indicator to estimate SOH. The Gaussian process regression method was used to estimate SOH. The hyper-parameter was optimized by the conjugate gradient method. The health indicator was taken as the input of the model to output the corresponding SOH. The experimental data of six batteries under different experimental conditions from NASA was selected to verify the method. Results The MAPE and RMSE values of the estimated results of the 6 batteries selected were all below 0.02. Conclusions The health indicator selected can better characterize the SOH of the battery. It verifies the feasibility of the SOH estimation method based on health indicator. The method can accurately estimate the SOH of batteries under different temperatures, discharge rates and depths of discharge, and has strong applicability.更多还原