服役工况下车用超级电容器模组寿命预估方法研究

Research on Life Prediction Method of Vehicle Supercapacitors Module Under Service Conditions

超级电容器具有充放电速度快、功率密度高等优点,在新能源汽车动力系统等方面有广泛的应用前景。但由于车用超级电容器的老化过程与工况及行驶条件等因素密切相关,在复杂的耦合因素影响下,实际寿命可能会与实验室测得的标称寿命不一致。该文提出一种基于实际服役工况下公交车的监控数据预估超级电容器模组寿命的方法。首先,针对监控数据采样频率和精度较低的问题,采用限定记忆最小二乘法对服役工况数据进行参数辨识得到容值及内阻,发现其具有时序性、季节性的特点。其次,基于容值和内阻的变化规律,提出基于Prophet算法的寿命预估方法。最后,通过前向链法验证,结果表明误差符合预期。Prophet算法可引入背景化知识调整预测结果,对季节性和周期性明显的时序数据预测具有优势。

Supercapacitors have the advantages of fast charging and discharging speed and high power density,and they have broad application prospects in the power system of new energy vehicles.However,the aging process of vehicle supercapacitors is closely related to service conditions and driving conditions,the actual life may be inconsistent with the nominal life measured in the laboratory under the influence of complex coupling factors.This paper proposed a method to estimate the life of supercapacitor modules based on the monitoring data of buses under service conditions.First,because of the low sampling frequency and accuracy of monitoring data,the limited memory least square method was used to perform parameter identification on the service conditions data to obtain the capacitance value and internal resistance as life characteristics parameters.It was found that it had the characteristics of time series and seasonality.Secondly,based on the change of capacitance and internal resistance,a life prediction method based on Prophet algorithm was proposed.Finally,the results are verified by the Rolling Origin Evaluation,which shows the error is in line with expectations.Prophet can introduce background knowledge to adjust the forecast results and has advantages in forecasting seasonal and periodic time series data.