| Citation: | ZHANG Zhiwen, DU Wenjie, LIANG Junfei, et al. Layered control of hybrid power loader based on fuel cell[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(11): 2165-2176. doi: 10.13700/j.bh.1001-5965.2021.0099(in Chinese)
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It is of great significance to study new energy technologies for loaders, which have high energy consumption and poor emissions. Combined with the operating characteristics of the loader, this paper proposes a power supply system driven by fuel cell and super capacitor. Our research focused on adaptive energy management strategy resulting from dynamic model and real-time data of fuel cell and supercapacitor system under complex working conditions. Firstly, we designed a composite power supply topology and power transmission scheme. Then, a multi-state model of the system was established under complex working conditions of the loader. And, based on the Haar wavelet theory, the power of the vehicle system was split. Subsequently, a fuzzy logic energy management strategy was proposed to dynamically balance the low-frequency components of the demand power. Lastly, the particle swarm optimization algorithm was used to optimize the control system. The simulation results showed that the power change was greatly slowed down because of the optimal threshold three-layer Haar wavelet on the load power, which effectively improved the life of the fuel cell system. The fuel cell power curve output by the fuzzy logic controller also changed smoothly. Meanwhile, the SOC value of the super capacitor was within the set area. Therefore, the overall efficiency of the composite power system was improved. After optimizing the controller by the particle swarm algorithm, the average output power of the fuel cell decreased by about 5% year-on-year, and the SOC value of the super capacitor reaches a dynamic equilibrium state of about 0.6, which improves the dynamic response and stability of the loader.
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