A novel pseudo-open-circuit voltage modeling method for accurate state-of-charge estimation of LiFePO4 batteries

被引:39
作者
Zhang, Kaixuan [1 ]
Xiong, Rui [1 ,4 ]
Li, Qiang [2 ]
Chen, Cheng [1 ]
Tian, Jinpeng [1 ]
Shen, Weixiang [3 ]
机构
[1] Beijing Inst Technol, Sch Mech Engn, Joint Lab Adv Energy Storage & Applicat, Beijing 100081, Peoples R China
[2] Weichai Power Co Ltd, Weifang 261061, Shandong, Peoples R China
[3] Swinburne Univ Technol, Sch Sci Comp & Engn Technol, Hawthorn, Vic 3122, Australia
[4] Beijing Inst Technol, Sch Mech Engn, Joint Lab Adv Energy Storage & Applicat, 5 South Zhongguancun St, Beijing 100081, Peoples R China
基金
北京市自然科学基金;
关键词
LiFePO (4) battery; Flat voltage; State of charge; Pseudo-OCV; Closed -loop feedback; LITHIUM-ION BATTERY; ONLINE STATE; KALMAN FILTER; TIME; HYSTERESIS;
D O I
10.1016/j.apenergy.2023.121406
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
LiFePO4 batteries are widely used in electric vehicles and energy storage due to their high safety. However, their flat voltage characteristics in the middle state of charge (SOC) range make it difficult to correct SOC estimation errors with a feedback mechanism. This study proposes a pseudo-open circuit voltage (OCV) modeling method to improve the performance of a closed-loop feedback correction. First, the relationship between the derivative of OCV and SOC or the slope of OCV, SOC range, and estimation error is analyzed to select the SOC interval for OCV curve construction. Second, a pseudo-OCV curve is established. An optimization algorithm is developed to identify the parameters of the OCV model based on the selected SOC interval and OCV slope, which establishes a pseudo-OCV curve. Third, the pseudo-OCV is compared with the real OCV to adjust the selected interval and further determine the optimal construction interval, then the curves of the pseudo-OCV and real OCV are stitched together to obtain the optimal OCV curve for global SOC estimation. Finally, SOC estimation is carried out using the constructed full pseudo-OCV and compared with the reference SOC obtained from experiments. The results show that the SOC estimation error at the full SOC range is less than 3 %.
引用
收藏
页数:12
相关论文
共 37 条
[1]   A novel data-driven method for mining battery open-circuit voltage characterization [J].
Chen, Cheng ;
Xiong, Rui ;
Yang, Ruixin ;
Li, Hailong .
GREEN ENERGY AND INTELLIGENT TRANSPORTATION, 2022, 1 (01)
[2]   A Lithium-Ion Battery-in-the-Loop Approach to Test and Validate Multiscale Dual H Infinity Filters for State-of-Charge and Capacity Estimation [J].
Chen, Cheng ;
Xiong, Rui ;
Shen, Weixiang .
IEEE TRANSACTIONS ON POWER ELECTRONICS, 2018, 33 (01) :332-342
[3]   Adaptive model parameter identification for large capacity Li-ion batteries on separated time scales [J].
Dai, Haifeng ;
Xu, Tianjiao ;
Zhu, Letao ;
Wei, Xuezhe ;
Sun, Zechang .
APPLIED ENERGY, 2016, 184 :119-131
[4]   Online state of charge estimation and open circuit voltage hysteresis modeling of LiFePO4 battery using invariant imbedding method [J].
Dong, Guangzhong ;
Wei, Jingwen ;
Zhang, Chenbin ;
Chen, Zonghai .
APPLIED ENERGY, 2016, 162 :163-171
[5]   A reliable approach of differentiating discrete sampled-data for battery diagnosis [J].
Feng, Xuning ;
Merla, Yu ;
Weng, Caihao ;
Ouyang, Minggao ;
He, Xiangming ;
Liaw, Bor Yann ;
Santhanagopalan, Shriram ;
Li, Xuemin ;
Liu, Ping ;
Lu, Languang ;
Han, Xuebing ;
Ren, Dongsheng ;
Wang, Yu ;
Li, Ruihe ;
Jin, Changyong ;
Huang, Peng ;
Yi, Mengchao ;
Wang, Li ;
Zhao, Yan ;
Patel, Yatish ;
Offer, Gregory .
ETRANSPORTATION, 2020, 3
[6]   State of charge estimation of lithium-ion phosphate battery based on weighted multi-innovation cubature Kalman filter [J].
Fu, Shiyi ;
Liu, Wen ;
Luo, Weilin ;
Zhang, Zhifang ;
Zhang, Maohui ;
Wu, Lei ;
Luo, Chengdong ;
Lv, Taolin ;
Xie, Jingying .
JOURNAL OF ENERGY STORAGE, 2022, 50
[7]   A review on the key issues of the lithium ion battery degradation among the whole life cycle [J].
Han, Xuebing ;
Lu, Languang ;
Zheng, Yuejiu ;
Feng, Xuning ;
Li, Zhe ;
Li, Jianqiu ;
Ouyang, Minggao .
ETRANSPORTATION, 2019, 1
[8]   China's battery electric vehicles lead the world: achievements in technology system architecture and technological breakthroughs [J].
He, Hongwen ;
Sun, Fengchun ;
Wang, Zhenpo ;
Lin, Cheng ;
Zhang, Chengning ;
Xiong, Rui ;
Deng, Junjun ;
Zhu, Xiaoqing ;
Xie, Peng ;
Zhang, Shuo ;
Wei, Zhongbao ;
Cao, Wanke ;
Zhai, Li .
GREEN ENERGY AND INTELLIGENT TRANSPORTATION, 2022, 1 (01)
[9]   Charging time and loss optimization for LiNMC and LiFePO4 batteries based on equivalent circuit models [J].
Hu, Xiaosong ;
Li, Shengbo ;
Peng, Huei ;
Sun, Fengchun .
JOURNAL OF POWER SOURCES, 2013, 239 :449-457
[10]   A method for SOC estimation based on simplified mechanistic model for LiFePO4 battery [J].
Li, Junfu ;
Lai, Qingzhi ;
Wang, Lixin ;
Lyu, Chao ;
Wang, Han .
ENERGY, 2016, 114 :1266-1276