L2-Gain Adaptive Robust Control for Hybrid Energy Storage System in Electric Vehicles

Authors

Xizheng Zhang, Zhangyu Lu, Xiaofang Yuan, Yaonan Wang, Xuejun Shen

Abstract

The underlying voltage/current tracking control is a key issue for a hybrid energy storage system (HESS) in electric vehicles. This article presents an innovative passivity-based L2-gain adaptive robust control (L2-ARC) method for a fully active battery/super-capacitor HESS. First, by exploiting and analyzing the internal structural properties, the port-controlled Hamiltonian model with dissipation for HESS is derived and then, the interconnection and damping assignment-passive based controller (IDA-PBC) is designed to realize the underlying control, where the rule-based energy management strategy is adopted to generate the current references. To overcome the adverse influence of external disturbances and parameter perturbations under complex driving conditions, by combining the L2 gain disturbance attenuation technique with the IDA-PBC method, the L2-ARC method is developed to guarantee fast response, high performance, and robust stability. Moreover, an adaptive mechanism is adopted to estimate the electrical parameters. The performance of L2-ARC is thoroughly investigated and compared through comprehensive case studies with traditional PID, IDA-PBC, and sliding mode controllers. Finally, a control prototype is implemented to validate L2-ARC.

Citation

• Journal: IEEE Transactions on Power Electronics
• Year: 2021
• Volume: 36
• Issue: 6
• Pages: 7319–7332
• Publisher: Institute of Electrical and Electronics Engineers (IEEE)
• DOI: 10.1109/tpel.2020.3041653

BibTeX

@article{Zhang_2021,
  title={{L2-Gain Adaptive Robust Control for Hybrid Energy Storage System in Electric Vehicles}},
  volume={36},
  ISSN={1941-0107},
  DOI={10.1109/tpel.2020.3041653},
  number={6},
  journal={IEEE Transactions on Power Electronics},
  publisher={Institute of Electrical and Electronics Engineers (IEEE)},
  author={Zhang, Xizheng and Lu, Zhangyu and Yuan, Xiaofang and Wang, Yaonan and Shen, Xuejun},
  year={2021},
  pages={7319--7332}
}

Download the bib file

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