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A Disturbance Rejection Control Strategy of a Single Converter Hybrid Electrical System Integrating Battery Degradation

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  • Yue Zhou

    (FEMTO-ST Institute, FCLAB, Université Bourgogne Franche-Comté, UTBM, CNRS, Rue Ernest Thierry Mieg, F-90000 Belfort, France)

  • Hussein Obeid

    (FEMTO-ST Institute, FCLAB, Université Bourgogne Franche-Comté, UTBM, CNRS, Rue Ernest Thierry Mieg, F-90000 Belfort, France)

  • Salah Laghrouche

    (FEMTO-ST Institute, FCLAB, Université Bourgogne Franche-Comté, UTBM, CNRS, Rue Ernest Thierry Mieg, F-90000 Belfort, France)

  • Mickael Hilairet

    (FEMTO-ST Institute, FCLAB, Université Bourgogne Franche-Comté, UTBM, CNRS, Rue Ernest Thierry Mieg, F-90000 Belfort, France)

  • Abdesslem Djerdir

    (FEMTO-ST Institute, FCLAB, Université Bourgogne Franche-Comté, UTBM, CNRS, Rue Ernest Thierry Mieg, F-90000 Belfort, France)

Abstract

In order to improve the durability and economy of a hybrid power system composed of a battery and supercapacitors, a control strategy that can reduce fluctuations of the battery current is regarded as a significant tool to deal with this issue. This paper puts forwards a disturbance rejection control strategy for a hybrid power system taking into account the degradation of the battery. First, the degradation estimation of the battery is done by the model-driven method based on the degradation model and Cubature Kalman Filter (CKF). Considering the transient and sinusoidal disturbance from the load in such a hybrid system, it is indispensable to smooth the behavior of the battery current in order to ensure the lifespan of the battery. Moreover, the constraints for the hybrid system should be considered for safety purposes. In order to deal with these demands, a cascaded voltage control loop based on a super twisting controller and proportional integral controller with an anti-windup scheme is designed for regulating the DC bus voltage in an inner voltage loop and supercapacitors’ voltage in an outer voltage loop, respectively. The specific feature of the proposed control method is that it operates like a low-pass filter so as to reduce the oscillations on the DC bus.

Suggested Citation

  • Yue Zhou & Hussein Obeid & Salah Laghrouche & Mickael Hilairet & Abdesslem Djerdir, 2020. "A Disturbance Rejection Control Strategy of a Single Converter Hybrid Electrical System Integrating Battery Degradation," Energies, MDPI, vol. 13(11), pages 1-19, June.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:11:p:2781-:d:365754
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    References listed on IDEAS

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    1. Henry Miniguano & Andrés Barrado & Cristina Fernández & Pablo Zumel & Antonio Lázaro, 2019. "A General Parameter Identification Procedure Used for the Comparative Study of Supercapacitors Models," Energies, MDPI, vol. 12(9), pages 1-20, May.
    2. Luping Chen & Liangjun Xu & Yilin Zhou, 2018. "Novel Approach for Lithium-Ion Battery On-Line Remaining Useful Life Prediction Based on Permutation Entropy," Energies, MDPI, vol. 11(4), pages 1-15, April.
    3. Mpho J. Lencwe & Shyama P. Chowdhury & Thomas O. Olwal, 2018. "A Multi-Stage Approach to a Hybrid Lead Acid Battery and Supercapacitor System for Transport Vehicles," Energies, MDPI, vol. 11(11), pages 1-16, October.
    4. Muhammad Umair Ali & Muhammad Ahmad Kamran & Pandiyan Sathish Kumar & Himanshu & Sarvar Hussain Nengroo & Muhammad Adil Khan & Altaf Hussain & Hee-Je Kim, 2018. "An Online Data-Driven Model Identification and Adaptive State of Charge Estimation Approach for Lithium-ion-Batteries Using the Lagrange Multiplier Method," Energies, MDPI, vol. 11(11), pages 1-19, October.
    5. Hannan, M.A. & Lipu, M.S.H. & Hussain, A. & Mohamed, A., 2017. "A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 834-854.
    6. Peng, Jiankun & Luo, Jiayi & He, Hongwen & Lu, Bing, 2019. "An improved state of charge estimation method based on cubature Kalman filter for lithium-ion batteries," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    7. Haibo Zhang & Xiaoming Liu & Honghai Ji & Zhongsheng Hou & Lingling Fan, 2019. "Multi-Agent-Based Data-Driven Distributed Adaptive Cooperative Control in Urban Traffic Signal Timing," Energies, MDPI, vol. 12(7), pages 1-19, April.
    8. Tommaso Campi & Silvano Cruciani & Francesca Maradei & Mauro Feliziani, 2019. "Magnetic Field during Wireless Charging in an Electric Vehicle According to Standard SAE J2954," Energies, MDPI, vol. 12(9), pages 1-24, May.
    9. Yu Wang & Zhongping Yang & Feng Li, 2018. "Optimization of Energy Management Strategy and Sizing in Hybrid Storage System for Tram," Energies, MDPI, vol. 11(4), pages 1-17, March.
    10. Muhammad Umair Ali & Amad Zafar & Sarvar Hussain Nengroo & Sadam Hussain & Gwan-Soo Park & Hee-Je Kim, 2019. "Online Remaining Useful Life Prediction for Lithium-Ion Batteries Using Partial Discharge Data Features," Energies, MDPI, vol. 12(22), pages 1-14, November.
    11. Cong Zhang & Dai Wang & Bin Wang & Fan Tong, 2020. "Battery Degradation Minimization-Oriented Hybrid Energy Storage System for Electric Vehicles," Energies, MDPI, vol. 13(1), pages 1-21, January.
    12. Matteo Moncecchi & Claudio Brivio & Stefano Mandelli & Marco Merlo, 2020. "Battery Energy Storage Systems in Microgrids: Modeling and Design Criteria," Energies, MDPI, vol. 13(8), pages 1-18, April.
    13. Liu, Liansheng & Kong, Fanxin & Liu, Xue & Peng, Yu & Wang, Qinglong, 2015. "A review on electric vehicles interacting with renewable energy in smart grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 648-661.
    14. Xiaopeng Tang & Ke Yao & Boyang Liu & Wengui Hu & Furong Gao, 2018. "Long-Term Battery Voltage, Power, and Surface Temperature Prediction Using a Model-Based Extreme Learning Machine," Energies, MDPI, vol. 11(1), pages 1-16, January.
    15. Jinhyeong Park & Munsu Lee & Gunwoo Kim & Seongyun Park & Jonghoon Kim, 2020. "Integrated Approach Based on Dual Extended Kalman Filter and Multivariate Autoregressive Model for Predicting Battery Capacity Using Health Indicator and SOC/SOH," Energies, MDPI, vol. 13(9), pages 1-20, April.
    16. Mahmoudzadeh Andwari, Amin & Pesiridis, Apostolos & Rajoo, Srithar & Martinez-Botas, Ricardo & Esfahanian, Vahid, 2017. "A review of Battery Electric Vehicle technology and readiness levels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 414-430.
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