SOC Estimation for Electrical Vehicle lithium Batteries base on Simplified-spherical Un-scented Kalman Filtering
DOI:
https://doi.org/10.54060/JIEEE/003.01.001Keywords:
Electrical Vehicle, State of Charge estimation, Extended Kalman Filter, Unscented Kalman Filter, Urban Driving CycleAbstract
In order to develop electric vehicles, it is vital to be able to accurately estimate the state charge (SOC) of a lithium battery. To address the problem that the Extended Kalman Filter (EKF) algorithm leads to the Taylor expansion truncation of the higher-order sys-tem. In this paper, a system of state-space equations is established based on the sec-ond-order equivalent circuit model, and a simplified-sphere sample approach is used to improve the Unscented Kalman Filter (UKF) algorithm. The SOC estimation performance of the three algorithms is tested under constant current discharge, pulse dis-charge con-ditions, and UDC conditions, respectively. The simulation results show that Simpli-fied-spherical Unscented Kalman Filtering (SUKF) has smaller errors between SOC esti-mation and theoretical reference values than EKF and UKF. The SUKF is less computa-tionally intensive than UKF and has better timeliness in the onboard battery manage-ment system.
Downloads
References
W. Qiu and Z. Qiu, "Design for symmetrical management of storage battery expert system based on single battery," 2006 International Conference on Mechatronics and Automation, 2006, pp. 1141-1146, doi: 10.1109/ICMA.2006.257786.
S. Maitreya, H. Jain and P. Paliwal, "Scalable and De-centralized Battery Management System for Parallel Operation of Multiple Battery Packs," 2021 Innovations in Energy Management and Renewable Resources(52042), 2021, pp. 1-7, doi: 10.1109/IEMRE52042.2021.9386861.
X. Li, R. Ma, L. Wang, S. Wang and D. Hui, "Energy Management Strategy for Hybrid Energy Storage Systems with Echelon-use Power Battery," 2020 IEEE International Conference on Applied Superconductivity and Electromagnetic Devices (ASEMD), 2020, pp. 1-2, doi: 10.1109/ASEMD49065.2020.9276135.
M. T. Lawder et al., "Battery Energy Storage System (BESS) and Battery Management System (BMS) for Grid-Scale Applications," in Proceedings of the IEEE, vol. 102, no. 6, pp. 1014-1030, 2014. doi: 10.1109/JPROC.2014.2317451.
F. Helling, S. Götz and T. Weyh, "A battery modular multilevel management system (BM3) for electric vehicles and stationary energy storage systems," 2014 16th European Conference on Power Electronics and Applications, 2014, pp. 1-10, doi: 10.1109/EPE.2014.6910821.
D. N. T. How, M. A. Hannan, M. S. Hossain Lipu and P. J. Ker, "State of Charge Estimation for Lithium-Ion Batteries Using Model-Based and Data-Driven Methods: A Review," in IEEE Access, vol. 7, pp. 136116-136136, 2019, doi: 10.1109/ACCESS.2019.2942213.
R. Xiong, J. Cao, Q. Yu, H. He and F. Sun, "Critical Review on the Battery State of Charge Estimation Methods for Electric Vehicles," in IEEE Access, vol. 6, pp. 1832-1843, 2018, doi: 10.1109/ACCESS.2017.2780258.
E. Aslan and Y. Yasa, "A Review on The Battery State of Charge Estimation Methods For Electric Vehicle Battery Management Systems," 2019 11th International Conference on Electrical and Electronics Engineering (ELECO), 2019, pp. 281-285, doi: 10.23919/ELECO47770.2019.8990463.
M. Naguib, P. Kollmeyer and A. Emadi, "Lithium-Ion Battery Pack Robust State of Charge Estimation, Cell Inconsistency, and Balancing: Review," in IEEE Access, vol. 9, pp. 50570-50582, 2021, doi: 10.1109/ACCESS.2021.3068776.
S. Shete, P. Jog, R. K. Kumawat and D. K. Palwalia, "Battery Management System for SOC Estimation of Lithium-Ion Battery in Electric Vehicle: A Review," 2021 6th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE), 2021, pp. 1-4, doi: 10.1109/ICRAIE52900.2021.9703752.
Y. Zhang, X. Cheng, Y. Fang and Y. Yin, "On SOC estimation of lithium-ion battery packs based EKF," Proceedings of the 32nd Chinese Control Conference, 2013, pp. 7668-7673.
L. Bo, Y. Xueqing and Z. Lin, "Li-ion battery SOC estimation based on EKF algorithm," 2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER), 2015, pp. 1584-1588, doi: 10.1109/CYBER.2015.7288182.
S. Gang, Z. Wei, H. Zhonghua and L. Shanshan, "Estimation of battery SOC based on improved EKF algorithm," 2016 IEEE Information Technology, Networking, Electronic and Automation Control Conference, 2016, pp. 151-154, doi: 10.1109/ITNEC.2016.7560338.
W. Zhang and W. Du, "SoC estimation based on adaptive EKF with colored noise," 2017 Chinese Automation Congress (CAC), 2017, pp. 1373-1377, doi: 10.1109/CAC.2017.8242981.
H. Du, G. Liu, J. Zhang, G. Tian and S. Wang, "SOC Estimation of Lithium-ion Batteries Based on Adaptive UKF," 2021 IEEE 4th International Conference on Renewable Energy and Power Engineering (REPE), 2021, pp. 137-140, doi: 10.1109/REPE52765.2021.9617029.
X. Zhang, J. Wu and G. Kang, "SOC estimation of Lithium battery by UKF algorithm based on dynamic parameter model," 2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), 2016, pp. 945-950, doi: 10.1109/URAI.2016.7734116.
M. Shehab El Din, A. A. Hussein and M. F. Abdel-Hafez, "Improved Battery SOC Estimation Accuracy Using a Modified UKF With an Adaptive Cell Model Under Real EV Operating Conditions," in IEEE Transactions on Transportation Electrification, vol. 4, no. 2, pp. 408-417, June 2018, doi: 10.1109/TTE.2018.2802043.
Y. Liu, Z. He, M. Gao, Y. Li and G. Liu, "Dual estimation of lithium-ion battery internal resistance and SOC based on the UKF," 2012 5th International Congress on Image and Signal Processing, 2012, pp. 1639-1643, doi: 10.1109/CISP.2012.6469649.
D. Mitra and S. Mukhopadhyay, "UKF Based Estimation of SOC and Core Temperature of a Lithium Ion Cell Using an Electrical Cell Model," 2018 15th IEEE India Council International Conference (INDICON), 2018, pp. 1-6, doi: 10.1109/INDICON45594.2018.8987074.
Q. Zheng, J. Yang, Q. Luo and K. Shi, "Estimation of state of charge of lithium battery based on BCRLS-UKF algorithm," 2021 IEEE International Conference on Computer Science, Electronic Information Engineering and Intelligent Control Technology (CEI), 2021, pp. 22-26, doi: 10.1109/CEI52496.2021.9574593.
S. Zhang, H. Sun and C. Lyu, "A method of SOC estimation for power Li-ion batteries based on equivalent circuit model and extended Kalman filter," 2018 13th IEEE Conference on Industrial Electronics and Applications (ICIEA), 2018, pp. 2683-2687, doi: 10.1109/ICIEA.2018.8398164.
Y. Song, M. Park, M. Seo and S. W. Kim, "Improved SOC estimation of lithium-ion batteries with novel SOC-OCV curve estimation method using equivalent circuit model," 2019 4th International Conference on Smart and Sustainable Technologies (SpliTech), 2019, pp. 1-6, doi: 10.23919/SpliTech.2019.8783149.
J. Wehbe and N. Karami, "Battery equivalent circuits and brief summary of components value determination of lithium ion: A review," 2015 Third International Conference on Technological Advances in Electrical, Electronics and Computer Engineering (TAEECE), 2015, pp. 45-49, doi: 10.1109/TAEECE.2015.7113598.
S. Zhang, H. Sun and C. Lyu, "A method of SOC estimation for power Li-ion batteries based on equivalent circuit model and extended Kalman filter," 2018 13th IEEE Conference on Industrial Electronics and Applications (ICIEA), 2018, pp. 2683-2687, doi: 10.1109/ICIEA.2018.8398164.
C. Kamrueng, S. Kittiratsatcha and S. Polmai, "A Number of RC Pairs Consideration of Electrical Equivalent Circuit Model of Li-ion Battery," 2020 6th International Conference on Engineering, Applied Sciences and Technology (ICEAST), 2020, pp. 1-4, doi: 10.1109/ICEAST50382.2020.9165523.
M. J. Malatji and S. P. D. Chowdhury, "Comparative study on Improvement in Battery Management System of Hybrid Batteries," 2019 IEEE PES/IAS PowerAfrica, 2019, pp. 307-312, doi: 10.1109/PowerAfrica.2019.8928868.
X. Sui, S. He, D. -I. Stroe, X. Huang, J. Meng and R. Teodorescu, "A review of sliding mode observers based on equivalent circuit model for battery SoC estimation," 2019 IEEE 28th International Symposium on Industrial Electronics (ISIE), 2019, pp. 1965-1970, doi: 10.1109/ISIE.2019.8781412.
Z. Chang et al., "Review of SOC estimation methods for lithium battery based on EKF," 2021 IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC), 2021, pp. 1319-1326, doi: 10.1109/IMCEC51613.2021.9482085.
F. Si, Z. Li, X. Long, F. Jiang and W. Hua, "Research on Estimation of Battery State of Electric Vehicle Battery Management System," 2020 IEEE 5th Information Technology and Mechatronics Engineering Conference (ITOEC), 2020, pp. 465-469, doi: 10.1109/ITOEC49072.2020.9141648.
C. Wang, X. Fan, L. Gao and X. Zhang, "Estimation of SOC of Battery Based on RVM-EKF Algorithm," 2018 11th International Symposium on Computational Intelligence and Design (ISCID), 2018, pp. 173-176, doi: 10.1109/ISCID.2018.10141.
X. Zhang and R. Zhang, "Estimation of Lithium Battery SOC Based on Fuzzy Unscented Kalman Filter Algorithm," 2021 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia), 2021, pp. 200-204, doi: 10.1109/ICPSAsia52756.2021.9621532.
M. Liu, N. Cui, S. Liu, C. Wang, C. Zhang and S. Gong, "Adaptive strong tracking unscented Kalman filter based SOC estimation for lithium-ion battery," 2017 Chinese Automation Congress (CAC), 2017, pp. 1437-1441, doi: 10.1109/CAC.2017.8242993.
J. Hu, S. Wu, Y. Wang, F. Lu and D. Liu, "Lithium Battery SOC Estimation Based on Improved Unscented Kalman Filter," 2020 15th IEEE Conference on Industrial Electronics and Applications (ICIEA), 2020, pp. 511-515, doi: 10.1109/ICIEA48937.2020.9248230.
Downloads
Published
How to Cite
CITATION COUNT
Issue
Section
