The invention discloses a pure electric bus driving range estimation method integrated with battery aging characteristics, which comprises the following steps: step 1, data processing: acquiring electric bus operation data based on a sensing technology and cleaning the data; 2, representing battery performance based on a capacity increment analysis method; 3, recognizing the aging level of the battery through deviation quadratic sum system clustering; 4, establishing a driving range estimation model based on a self-attention mechanism; and 5, estimating the driving range of the pure electric bus based on the driving range estimation model. Compared with a traditional integrated machine learning method, the method has better performance in processing high-dimension and sequence data. The self-attention mechanism can capture the dependency relationship among different positions in the sequence, and compared with an integration method which usually needs to train a plurality of base learners step by step, the self-attention mechanism has the advantages that modern computing resources can be more fully utilized, so that the advantages of the self-attention mechanism in large-scale data processing are more obvious.
本发明公开了一种融入电池老化特征的纯电动公交车续驶里程估计方法,包括步骤1:数据处理,基于传感技术采集电动公交车运行数据并对数据进行数据清洗;步骤2:基于容量增量分析法表征电池性能;步骤3:通过离差平方和系统聚类识别电池老化水平;步骤4:基于自注意力机制建立续驶里程估计模型;步骤5:基于续驶里程估计模型进行纯电动公交车续驶里程估计。具有相比于传统的集成机器学习方法在处理高维度和序列数据时表现更佳。自注意力机制能够通过捕捉序列中不同位置之间的依赖关系,相较于集成方法通常需要逐步训练多个基学习器,自注意力更能充分利用现代计算资源,这使其在大规模数据处理中的优势更加明显的优点。
Method for estimating driving range of pure electric bus integrated with battery aging characteristics
一种融入电池老化特征的纯电动公交车续驶里程估计方法
28.02.2025
Patent
Elektronische Ressource
Chinesisch
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