Mr. Tong Zhang Profile

Tong Zhang

at Tongji Univ

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Proceedings Article | 19 October 2023 Paper

Research on energy management strategy of fuel cell hybrid power system based on minimum principle

Kai Li, Jiaxing Cehn, Tong Zhang

Proceedings Volume 12709, 127095R (2023) https://doi.org/10.1117/12.2684888

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As the power output of fuel cell system cannot respond quickly to dynamic power loading, it is necessary to combine other power sources. The battery is chosen as an auxiliary energy source to store the energy recovered from braking, and a super capacitor is also used because of its high power density. In order to distribute the power flow among the above three-power hybrid system, based on Pontryagin's minimum principle, this paper formulates an energy management strategy, focusing on the relationship between co-state and state of charge. The results show that although the relationship between the co-state and the state of charge for each auxiliary power source is monotonic, the co-states of different auxiliary power sources have coupling effect.

Proceedings Article | 10 November 2020 Paper

An online capacity estimation method for LiFePO4 battery module with incremental capacity curve processed by tracking differentiator under noises

Ling Liu, Tong Zhang, Yanhui Zhou, Xiongwu Zhong, Yongbo Xie, Wenming Wang, Jiejun Yang

Proceedings Volume 11584, 115841Y (2020) https://doi.org/10.1117/12.2581790

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Incremental capacity (IC) analysis is an effective and widely used approach to evaluate the lithium-ion battery remaining capacity. A limitation for IC based capacity estimation is that it requires a consistent constant charging current for each test and demands a large amount of data to be stored, which hinder its use in practical conditions. To address the issues, this paper proposes an online capacity estimation method for battery module with incremental capacity curves processed by tracking differentiator. Specifically, the IC features, such as peak voltage, peak amplitude, are analyzed for the battery module empirically and theoretically. The analytic linear relationship between the IC features and capacity are formulated. As a basis, the calculation of dQ/dV is converted to the derivative of terminal voltage, which is obtained by a designed tracking differentiator. For the iteratively derived IC curve, a realtime peak detection algorithm is proposed to detect the second peak voltage without the requirement to store any historical data. The proposed method is not sensitive to noise and applicable to common charging conditions. Experimental results with cycle data for a commercial 206Ah battery module reveals the superiority of the proposed method.

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