电动飞行器用电池SOC估计算法多指标量化研究  

Multi-index quantitative research on SOC estimation of electric aircraft energy system

作　　者：张丹红 王榘[1,2] 呼文韬 孙国瑞 ZHANG Danhong;WANG Ju;HU Wentao;SUN Guorui(China Electronics Technology Energy Co.,Ltd.,Tianjin 300384,China;Tianjin Institute of Power Sources,Tianjin 300384,China)

机构地区：[1]中电科能源有限公司,天津300384 [2]中国电子科技集团公司第十八研究所,天津300384

出　　处：《电源技术》2023年第8期1033-1039,共7页Chinese Journal of Power Sources

摘　　要：电动飞行器用储能电池系统具有比能量高、老化速率快、电磁环境复杂等特点,存在荷电状态(SOC)估计不准、可用能量受限、算法鲁棒性降低等问题。提出一种SOC估计算法多指标量化分析方法,基于分析算法实时性、工况适应性、噪声鲁棒性、估算精准性四个性能6个指标,综合评估多个SOC估计算法在储能电池系统中的应用潜力。结果表明:SMO观测器具有较好的估计精度和实时性;EKF、UKF、HIF具有相似的估算精准性和算法收敛速度,HIF算法具有更强的抗噪声鲁棒性。The energy storage battery system for electric aircraft has the characteristics of high specific energy,fast aging rate,and complex electromagnetic environment.In this paper,a multi-index quantitative analysis method of SOC estimation accuracy was proposed.The algorithm’s real-time performance,operating condition adaptability,noise robustness,and estimation accuracy were used to comprehensively evaluate the application potential of multiple SOC estimation algorithms in energy storage battery systems.The results show that the SMO observer has better estimation accuracy and real-time performance.And the EKF,UKF and HIF have similar estimation accuracy and algorithm convergence speed.The HIF algorithm has stronger estimation accuracy and noise robustness.

关 键 词：电动飞行器 储能电池系统 多指标量化 荷电状态 

分 类 号：TM912[电气工程—电力电子与电力传动]