首页|期刊导航|中国电机工程学报|一种基于GRU的氢燃料重卡汽车工况下锂离子电池温度预测模型

一种基于GRU的氢燃料重卡汽车工况下锂离子电池温度预测模型OA北大核心CSTPCD

A GRU Based Temperature Prediction Model of Lithium-ion Battery for Hydrogen Fuel Heavy Truck Under Operating Conditions

中文摘要英文摘要

针对目前氢燃料重卡在行驶过程中,动力电池工况复杂、外表面温度变化难以预测、滞后时间长等问题,以氢燃料重卡锂离子动力电池外表面温度为研究对象,提出一种类交叉熵损失函数和自适应矩估计(adaptive moment estimation,Adam)优化的改进型门控循环单元神经网络(gate recurrent unit,GRU),建立锂离子动力电池表面温度预测模型.该模型利用GRU神经网络的特殊门机制和全局处理能力,得到锂离子电池表面温度和电池充放电…查看全部>>

Addressing the complexities of power battery conditions,unpredictable surface temperature changes,and significant time lags encountered during the operation of heavy hydrogen fuel cards,this study focuses on the outside surface temperature of lithium-ion power batteries as the primary research target.To this end,an enhanced gate recurrent unit(GRU)neural network is proposed,optimized through the integration of a cross-entropy loss function and adaptive momen…查看全部>>

闫志远;孙桓五;刘世闯;赵立禹

太原理工大学机械与运载工程学院,山西省 太原市 030024

交通运输

氢燃料重卡锂离子电池温度预测模型门控循环单元神经网络深度学习

hydrogen fuel heavy trucklithium-ion batteriestemperature prediction modelgated recurrent neural networkdeep learning

《中国电机工程学报》 2024 (006)

2330-2339,后插21 / 11

山西省科技重大专项项目(20181102009).Major Special Project of Science and Technology in Shanxi Province(20181102009).

10.13334/j.0258-8013.pcsee.221789

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