Air cooling strategy of power battery based on minimum energy consumption

doi:10.12028/j.issn.2095-4239.2019.0022

Abstract

Abstract: To solve the problems of high energy consumption and lag in heat dissipation of power batteries of electric vehicles, a control strategy of air cooling for power batteries based on minimum energy consumption is proposed. The strategy predicts the future temperature rise of power battery according to the working conditions which is predicted by vehicle navigation system. On the premise of meeting the heat dissipation requirement of power battery, the optimal objective is to minimize the energy consumption of fan, the sectional dynamic programming algorithm is applied to determining the starting time and optimal wind speed of fan in the future section. Taking the combined working conditions of ARB02, HWFET and UDDSHDV with slope information as test conditions, the hardwarein-the-loop test for the accuracy of predicting the future temperature rise of power battery is carried out. The maximum difference between the real-time road condition test temperature and the test temperature in predicting working conditions is 0.3℃, the maximum deviation rate is 0.7%. Fluent simulation results are compared with the other two control strategies, The results show that under the control strategy, the temperature of power battery is always within 40℃, and the maximum temperature difference of battery pack is 1.1℃; the energy consumption of fan is 77.2% of that of the control strategy of fan opening in the whole process, and 53.7% of that of fan based on temperature control strategy. The strategy can effectively control the temperature of power battery and minimize the energy consumption of fan.

Key words: power battery, air cooling and heat dissipation, vehicle navigation system, temperature prediction, minimum energy consumption

CLC Number:

U469.72+2

ZHAO Guozhu, ZHAO Xiaohe, XU Xiaoming, GAO Maoqing. Air cooling strategy of power battery based on minimum energy consumption[J]. Energy Storage Science and Technology, 2019, 8(4): 751-758.

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