The hybrid power system formed by batteries and supercapacitors can meet the demands of electric loaders for endurance and instantaneous power. Appropriate parameter matching can optimize the operational performance of the hybrid power system. However, multiple optimization objectives and complex constraints present technical challenges for parameter matching. To address this, this paper proposes a multi-objective optimization parameter matching method for a hybrid power system based on the Non-dominated Sorting Genetic Algorithm II (NSGA-II) algorithm. First, mathematical models for the battery, supercapacitor, and DC-DC converter are established. Next, based on the performance requirements of electric loaders, objective functions and constraints for hybrid power parameter matching are defined, and an optimization model for parameter matching is developed. Finally, the optimal parameters for the hybrid power system are determined using the NSGA-II algorithm. Experimental results indicate that, compared to a single battery energy storage system, the operational energy consumption of electric loaders equipped with a hybrid power system is reduced by 3.32% and battery capacity degradation is decreased by 10.61%, with only a slight increase in costs.

For the variable speed variable displacement power unit (VSVDPU), achieving power matching between the permanent magnet synchronous motor (PMSM) and the variable displacement plunger pump (VDPP) is the key to reducing system energy consumption. The control method of adjusting the speed of the PMSM and the displacement of the VDPP is the mainstay of current research and application of the VSVDPU. However, the dynamic properties of the PMSM and VDPP have not been balanced, which affects the control effect of the VSVDPU. This paper proposes a control method of variable speed and variable displacement with low energy consumption and high dynamics. The main idea is based on the efficiency model and dynamic response model of the PMSM and VDPP, and the factors that affect the efficiency and dynamic characteristics of the VSVDPU are analyzed. Guided by the multi-objective optimization algorithm, the optimal combination of speed and displacement under specific working conditions is derived. Simulation and experiment results show that the proposed control method is feasible to improve the efficiency and dynamic characteristics of the VSVDPU.