Pure electric vehicle cooling system control method based on deep reinforcement learning

Abstract

The invention relates to a pure electric vehicle cooling system control method based on deep reinforcement learning, which comprises the following steps: first, obtaining the temperature of the powerbattery of the pure electric vehicle, the working current of the power battery, and the ambient temperature information; Construct DDPG algorithm model, carry on reinforcement learning training, get agroup of optimal PID control parameters of electronic pump. The PID control quantity is obtained by the PID input quantity, and the electronic pump is controlled based on the PID control quantity. The work of the electronic pump changes the flow rate of coolant in the power battery cooling system to achieve the purpose of cooling the power battery. At the same time, the information of the power battery is transmitted to the environment sensing module, and the first step is returned to circulate the whole process. The invention introduces the depth reinforcement learning into the PID control algorithm, the depth reinforcement learning can better interact with the environment, has the self-learning function, adapts to the dynamic characteristics of the uncertain system, and therefore can adapt to the complex and changeable characteristics of the pure electric vehicle running environment, and realizes on-line control under different actual scenes.

Description

technical field [0001] The invention relates to the technical field of thermal management of pure electric vehicles, in particular to a method for controlling the cooling system of a power battery of pure electric vehicles based on reinforcement learning. Background technique [0002] At present, most of the cooling electronic water pumps used in electric vehicles use switch-type control methods. This method is mainly to set a desired temperature value according to the target value, and then set the upper limit value of the control temperature according to the target value. If the temperature exceeds this range, the electronic water pump starts to cool down, otherwise it does not start, allowing the coolant to cool naturally in the cooling cycle. In addition, there are fuzzy control, expert system and integrated intelligent control. [0003] Among them, the main problem of the switch-type control method is that the electronic water pump will be turned on frequently in some ...

AI Technical Summary

Problems solved by technology

[0003] Among them, the main problem of the switch-type control method is that the electronic water pump will be turned on frequently in some specific environments, which seriously affects the service life of the electronic water pump; Ineffective consumption of power, the cost of operation will be greatly increased

Fuzzy control has a good control effect on systems that are difficult to establish an accurate model but can be controlled based on experience, but there are fuzzy rule designs, which rely too much on manual design and cannot be applied to systems with large delays

Expert systems can make better use of expert experience and knowledge, but there are deficiencies in that knowledge acquisition relies on manual work and weak reasoning ability

The integrated intelligent control algorithm is combined according to the advantages of different intelligent control algorithms, but it still cannot completely avoid the shortcomings of the combined intelligent control algorithm itself

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