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Research on Power Optimization for Energy System of Hydrogen Fuel Cell Wheel-Driven Electric Tractor


Hydrogen fuel cell tractors are emerging as a new power source for tractors. Currently, there is no mature energy management control method available. Existing methods mostly rely on engineers’ experience to determine the output power of the fuel cell and the power battery, resulting in relatively low energy utilization efficiency of the energy system. To address the aforementioned problems, a power optimization method for the energy system of hydrogen fuel cell wheel-driven electric tractor was proposed. A dynamic model of tractor ploughing conditions was established based on the system dynamics theory. From this, based on the equivalent hydrogen consumption theory, the charging and discharging of the power battery were equivalent to the fuel consumption of the hydrogen fuel cell, forming an equivalent hydrogen consumption model for the tractor. Using the state of charge (SOC) of the power battery as a constraint, and with the minimum equivalent hydrogen consumption as the objective function, an instantaneously optimized power allocation method based on load demand in the energy system is proposed by using a traversal algorithm. The optimization method was simulated and tested based on the MATLAB simulation platform, and the results showed under ploughing conditions, compared with the rule-based control strategy, the proposed energy system power optimization method optimized the power output of hydrogen fuel cells and power batteries, allowing the energy system to work in a high-efficiency range, reducing the equivalent hydrogen consumption of the tractor by 7.79%, and solving the energy system power distribution problem.

Funding source: This research was funded by the National Key R&D Program of China [2022YFD2001203, 2022YFD2001201B], Henan University of Science and Technology Innovation Team Support Program [24IRTSTHN029], Zhongyuan Science and Technology Innovation Leading Talent Support Program Project [244200510043].
Related subjects: Applications & Pathways

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