Electric automobile compound energy management method based on rule and Q-learning reinforcement learning

Abstract

The invention discloses an electric automobile compound energy management method based on a rule and Q-learning reinforcement learning. By the adoption of the method, energy management is conducted according to the power requirement of a vehicle at every moment and the SOCs of a lithium battery and a super capacitor. In an energy management strategy based on Q-learning reinforcement learning, an energy management controller takes actions through observation of the system state, calculates the corresponding award value of each action and makes updates in real time, an energy management strategywith the minimum system loss power is obtained through utilization of the award values through Q-learning reinforcement learning algorithm simulative training, finally, real-time power distribution is conducted through the energy management strategy obtained through learning, and meanwhile, the award values are continuously updated to adapt to the current driving condition. By the adoption of themethod, on the basis that the required power is met, the electric quantity of the lithium battery can be kept, the service life of the lithium battery is prolonged, meanwhile, system energy loss is reduced, and the efficiency of a hybrid power system is improved.

Description

Technical field [0001] The invention relates to an electric vehicle energy management method based on rules and Q-learning enhanced learning. Background technique [0002] The current high dependence of automobiles on non-renewable fuels has aroused people's attention to the sustainable development of the global environment. The problems of air pollution and resource consumption caused by traditional cars have greatly promoted the development of electric cars. For the energy storage system of electric vehicles, not only enough energy is needed to travel long distances, but also enough power is needed to accelerate, brake, and climb hills. Lithium batteries can meet the requirements of high power density and high energy density due to their light weight, high energy storage, high power, and no pollution. However, the use of lithium batteries alone may cause the battery pack to overheat and shorten its life. The super capacitor has the advantages of long life and high instantaneo...

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to solve the energy distribution problem of the electric vehicle hybrid power system. This paper proposes a compound energy management method based on rules and nonlinear predictive control. According to the power demand of the vehicle at each moment, the lithium battery and super Capacitor SOC status for energy management

Images