科技创新与应用2025，Vol.15Issue(12)：84-88,5.DOI:10.19981/j.CN23-1581/G3.2025.12.019
基于数据驱动的港口电动集卡续航能力预测模型研究
黄梓畅 1张小锐 2于泳 2韩德胜 2孙会路 1雷路1
作者信息
- 1. 北京经纬恒润科技股份有限公司,北京 100015
- 2. 唐山港口实业集团有限公司,河北 唐山 063611
- 折叠
摘要
Abstract
To address the problem of big errors in calculating the range of electric container trucks in ports,this paper finds that it is mainly because the driving cycle of passenger cars are not applicable to the special working conditions of electric container trucks in ports.In this paper,a generative adversarial network-based approach is used to obtain representative driving cycle,and a dynamics-based energy consumption model is used to achieve a more accurate range estimation.The method divides the data into different subsets of short trips by dividing the short trips,counting the short trip features,and performing operations such as dimensionality reduction and clustering on the features.The subsets are used to train adversarial generative networks to obtain representative driving cycle in ports,and the whole vehicle energy consumption model is established based on kinetic analysis to achieve the estimation of range.Through the comparison and validation with the range of actual port electric container trucks,the error rate of the range predicted by this method is only 4.6％,which fully demonstrates the high accuracy of this method in predicting the range of port electric container trucks.关键词
循环工况/对抗式生成网络/能耗模型/续航里程/电动集卡Key words
driving cycle/generative adversarial network/energy consumption model/range/electric container truck分类
交通运输引用本文复制引用
黄梓畅,张小锐,于泳,韩德胜,孙会路,雷路..基于数据驱动的港口电动集卡续航能力预测模型研究[J].科技创新与应用,2025,15(12):84-88,5.
