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.