An energy control method for hybrid power system based on fuzzy neural network

Abstract

The invention discloses an energy control method of a hybrid power system based on a fuzzy neural network. The power required by the motor drive system calculated according to the current vehicle state and the state of charge (SOC) information of the battery system are transmitted to the fuzzy neural network controller, and the output power of the power system is adjusted according to the rules trained by the fuzzy neural network controller. Make adjustments. The invention can control the output power of the fuel cell system, effectively manage the energy flow between the power systems, keep the SOC of the battery pack in a relatively stable state, and extend the power supply system on the premise of meeting the power requirements of the vehicle. The working life is improved, and the working efficiency of the power system is improved. At the same time, the system responds faster, has strong robustness, and can respond quickly to the driver's operations under different driving conditions.

Description

technical field [0001] The invention belongs to the field of hybrid power system control, and in particular relates to a power system control method in which a fuel cell and an energy storage battery are mixed. Background technique [0002] With the depletion of global fossil resources and the seriousness of environmental pollution, energy conservation and emission reduction has become an important direction for the development of various industries, especially the automobile industry. Domestic new energy vehicles such as electric vehicles and fuel cell vehicles are gradually emerging. However, due to current technical limitations, pure electric vehicles have short mileage and insufficient endurance; while pure fuel cell vehicles have high cost and slow dynamic response, which limits their further development. Therefore, some researchers have proposed that hybrid vehicles are one of the effective solutions to the energy crisis and global warming. The current hybrid fuel cel...

AI Technical Summary

Problems solved by technology

For hybrid electric vehicles, the commonly used rule-based control method is not effective in complex road conditions (a control method for plug-in hybrid electric vehicles based on fuzzy systems, patent No. CN101947955B), and the formulation of fuzzy control itself fuzzy rules It also has strong subjective factors. Considering that energy management is an important factor in determining the power distribution between the fuel cell system and the auxiliary energy storage device and improving the overall efficiency of the system, it is urgent to develop related control methods based on intelligent algorithms

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