Abstract:
This paper designed a composite power supply system to solve the problems of insufficient endurance of electric tractors, high energy consumption due to high randomness of power system discharge and imperfect capacity configuration, the study designed a composite power supply system based on battery and supercapacitor power supply. Aiming at the problem of poor dynamic load adaptability, a three-stage load power segmentation rule was designed, and the functional relationship between the power division parameter and the load statistics was established. Aiming at the phenomenon of poor discharging effect of the energy storage system due to changes in the working conditions of the electric tractor under the traditional fixed-threshold strategy, a fuzzy logic-based adaptive adjustment strategy for the discharging threshold was proposed on the basis of double closed-loop control. In addition, considering the differences between storage batteries and supercapacitors in terms of power density, energy density and price, a hybrid energy storage system capacity configuration method that considered the optimal energy saving rate and comprehensive economic effect was proposed. The capacity configuration objective function containing the whole life cycle cost of the energy storage device and the system power consumption cost was constructed, the energy saving rate results of the no-threshold control strategy and the threshold control strategy in this paper were analyzed separately, the genetic algorithm was used to find the optimal solution for the capacity configuration objective function, and the impact of the energy saving rate constraints on the capacity configuration results was analyzed. In addition, the proposed discharge threshold adaptive adjustment strategy was simulated and analyzed, and the simulation test was completed on the laboratory 10 kW load power supply simulation system to verify. The results showed that the energy saving rate using the fuzzy logic adaptive threshold control strategy in this paper was improved by 3.09% and the hourly power consumption was reduced by nearly 9.5% compared with the traditional energy management strategy without threshold, at the same time, the output voltage of the power supply system was 527 V when the power fluctuated greatly and the output voltage of the power supply system was 520 V when the power fluctuates was smooth, which improved the output voltage stability of the energy storage system. Implementation of the designed energy management strategy for composite power supply system using genetic algorithm can achieve better real-time energy management with lower computational cost.