Parameter Matching of Battery–Supercapacitor Hybrid Power System for Electric Loader

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.