A fractional order model of auxiliary power batteries suitable for hydrogen fuel cell hybrid systems heavy-duty trucks

被引:3
作者
Liu, Shichuang [1 ]
Sun, Huanwu [1 ,2 ]
Yu, Haotong [1 ]
Miao, Jian [1 ]
Zheng, Cao [1 ]
Zhang, Xiuwei [1 ]
机构
[1] Taiyuan Univ Technol, Coll Mech & Transport Engn, Taiyuan 030024, Peoples R China
[2] Natl Expt Teaching Demonstrat Ctr Coal Resources E, Taiyuan 030024, Peoples R China
关键词
Hydrogen fuel cell system; Heavy-duty trucks; Auxiliary power battery; Fractional -order model; SOC; PARAMETER-IDENTIFICATION; CIRCUIT; STATE;
D O I
10.1016/j.ijhydene.2024.03.095
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Aiming at the problem that the existing battery fractional order model is not suitable for the auxiliary power battery of hydrogen fuel cell heavy-duty trucks, considering the characteristics of multiple influencing factors and nonlinearity in actual driving processes, a fractional order model of auxiliary power batteries is proposed based on the hydrogen fuel cell heavy-duty trucks model and the batteries' fractional order model. Then, to solve the charge state estimation error increases due to the high frequency and large rate charging and discharging, H infinity filter is introduced into the adaptive unscented Kalman filter to optimize the charge state estimation in the model. Additionally, the model's parameters are identified using the evolutionary algorithm and the recursive least squares technique based on the forgetting factor. Finally, the model is verified by dynamic conditions. The results show that compared with the auxiliary power batteries' fractional order model, the optimized model reduces the MAE by 0.08% and the RMSE by 0.22% when estimating voltage, and reduces the MAE by 0.25% and the RMSE by 2.66% when estimating SOC. Therefore, the optimized fractional order model of auxiliary power battery has higher accuracy and applicability.
引用
收藏
页码:346 / 358
页数:13
相关论文
共 38 条
[1]   Time-domain fitting of battery electrochemical impedance models [J].
Alavi, S. M. M. ;
Birkl, C. R. ;
Howey, D. A. .
JOURNAL OF POWER SOURCES, 2015, 288 :345-352
[2]   Hydrogen fuel cell heavy-duty trucks: Review of main research topics [J].
Camacho, Maria de las Nieves ;
Jurburg, Daniel ;
Tanco, Martin .
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2022, 47 (68) :29505-29525
[3]   A novel combined estimation method of online full-parameter identification and adaptive unscented particle filter for Li-ion batteries SOC based on fractional-order modeling [J].
Chen, Lei ;
Wang, Shunli ;
Jiang, Hong ;
Fernandez, Carlos ;
Xiong, Xin .
INTERNATIONAL JOURNAL OF ENERGY RESEARCH, 2021, 45 (10) :15481-15494
[4]   Model-based fault diagnosis approach on external short circuit of lithium-ion battery used in electric vehicles [J].
Chen, Zeyu ;
Xiong, Rui ;
Tian, Jinpeng ;
Shang, Xiong ;
Lu, Jiahuan .
APPLIED ENERGY, 2016, 184 :365-374
[5]   Experimental validation for Li-ion battery modeling using Extended Kalman Filters [J].
Claude, F. ;
Becherif, M. ;
Ramadan, H. S. .
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2017, 42 (40) :25509-25517
[6]   Nonlinear Frequency Response Analysis (NFRA) of Lithium-Ion Batteries [J].
Harting, Nina ;
Wolff, Nicolas ;
Roeder, Fridolin ;
Krewer, Ulrike .
ELECTROCHIMICA ACTA, 2017, 248 :133-139
[7]   Clean commercial transportation: Medium and heavy duty fuel cell electric trucks [J].
Kast, James ;
Vijayagopal, Ram ;
Gangloff, John J., Jr. ;
Marcinkoski, Jason .
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2017, 42 (07) :4508-4517
[8]   State estimation of lithium polymer battery based on Kalman filter [J].
Li, Jiabo ;
Ye, Min ;
Gao, Kangping ;
Jiao, Shengjie ;
Xu, Xinxin .
IONICS, 2021, 27 (09) :3909-3918
[9]   A Novel Online Parameter Identification Algorithm for Fractional-Order Equivalent Circuit Model of Lithium-Ion Batteries [J].
Li, Lan ;
Zhu, Huarong ;
Zhou, Anjian ;
Hu, Minghui ;
Fu, Chunyun ;
Qin, Datong .
INTERNATIONAL JOURNAL OF ELECTROCHEMICAL SCIENCE, 2020, 15 (07) :6863-6879
[10]   Electrochemical study on lithium iron phosphate/hard carbon lithium-ion batteries [J].
Liao, Xiangfei ;
Yu, Ji ;
Gao, Lijun .
JOURNAL OF SOLID STATE ELECTROCHEMISTRY, 2012, 16 (02) :423-428