Adaptive state of energy evaluation for supercapacitor in emergency power system of more-electric aircraft

被引:17
作者
Wang, Bin [1 ]
Wang, Chaohui [1 ]
Wang, Zhiyu [1 ]
Ni, Siliang [2 ]
Yang, Yixin [1 ]
Tian, Pengyu [1 ]
机构
[1] Xi An Jiao Tong Univ, State Key Lab Mfg Syst Engn, Xian 710049, Shaanxi, Peoples R China
[2] Univ Canterbury, Coll Engn, Dept Mech Engn, Private Bag 4800, Christchurch 8140, New Zealand
基金
中国国家自然科学基金;
关键词
Supercapacitor; State of energy evaluation; Adaptive parameter estimation; Sliding mode observer; Emergency power system; More -electric aircraft; DOUBLE-LAYER CAPACITORS; MANAGEMENT STRATEGIES; CHARGE ESTIMATION; FUTURE; ARCHITECTURE; PARAMETERS; BATTERIES;
D O I
10.1016/j.energy.2022.125632
中图分类号
O414.1 [热力学];
学科分类号
摘要
This paper presents an adaptive state of energy (SOE) evaluation method for a supercapacitor in the emergency power system of a more-electric aircraft. The adaptive SOE evaluation is realized based on a dynamic first-order RC equivalent circuit and its self-adaptive updated parameters. First, a dynamic first-order RC equivalent circuit with three parameters (i.e., the charge/discharge resistance R0, the dynamic self-discharge resistance R1, and the dynamic capacity C1) and a state-space model are introduced for modeling the supercapacitor. Then, an adaptive sliding mode observer is designed for tracking the dynamic change of the three state-space model parameters (i. e., R0, (R0+R1)/R1C1, and 1/R1C1). With this design, the three parameters of the dynamic first-order RC equivalent circuit can be updated adaptively along with the derivation of the three state-space model parameters. Moreover, the adaptive sliding mode observer is redesigned with a sign function, which can enhance the convergence rate of the three self-adaptive updated parameters. Finally, the accurate SOE evaluation would be achieved based on the three self-adaptive updated parameters. Various simulations and experiments are con-ducted to validate the adaptive SOE evaluation method. It is shown that the adaptive SOE evaluation method can achieve 0.5% of the maximum relative error of the estimated SOE. Compared with the commonly used method, the adaptive SOE evaluation method has over 1% improvement for the SOE estimation accuracy.
引用
收藏
页数:10
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