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基于最小能耗的动力电池风冷控制策略 被引量:5

Air cooling strategy of power battery based on minimum energy consumption
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摘要 针对目前电动汽车动力电池风冷散热能耗高、散热滞后的问题,提出一种基于最小能耗的动力电池风冷控制策略,根据车载导航系统预报的工况信息预测动力电池的未来温升,在满足动力电池散热需求的前提下以风机能耗最少为目标,运用分段式动态规划算法确定风机在未来路段的开启时机与最优风速。以添加了坡度信息的ARB02、HWFET和UDDSHDV的组合工况为测试工况,对动力电池未来温升的精度进行了硬件在环试验,得出实际路况试验温度与预报工况试验温度的最大差值为0.3℃,最大偏差率为0.7%。与其他两种控制策略进行了Fluent仿真对比,结果表明基于最小能耗控制策略下动力电池的最高温度为39.87℃,最大温差为1.1℃;风机能耗是全程开启型控制策略的77.2%,是温度开关型控制策略的53.7%。该策略能有效控制动力电池的温度且风机能耗最小。 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.
作者 赵国柱 招晓荷 徐晓明 高茂庆 ZHAO Guozhu;ZHAO Xiaohe;XU Xiaoming;GAO Maoqing(College of Engineering, Nanjing Agricultural University, Nanjing 210031, Jiangsu, China;hool of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, Jiangsu, China)
出处 《储能科学与技术》 CAS CSCD 2019年第4期751-758,共8页 Energy Storage Science and Technology
基金 国家自然科学基金项目(51505196)
关键词 动力电池 风冷散热 车载导航系统 温度预测 最小能耗 power battery air cooling and heat dissipation vehicle navigation system temperature prediction minimum energy consumption
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