The invention discloses a cluster electric vehicle power optimization management method based on machine learning. The method comprises the following steps: firstly, establishing a cluster electric vehicle power management model based on machine learning; acquiring and processing historical data, and substituting the historical data into a long short-term memory (LSTM) neural network for offline training; then, comparing results of the offline training performed in the step B, and installing an LSTM with an optimal training effect in the cluster electric vehicle management system; and finally,inputting online acquired data into the LSTM, generating a scheduling result online, and issuing a scheduling instruction. According to the method, mathematical calculation is carried out in the offline stage, approximately optimal scheduling signals can be quickly obtained only by matching the relationship between input and output through the trained LSTM network during online operation, the requirement for a CPU during online operation is reduced, and the method is suitable for online scheduling calculation of large-specification electric vehicles.
本发明公开了一种基于机器学习的集群电动汽车功率优化管理方法,先建立基于机器学习的集群电动汽车功率管理模型;再通过采集并处理历史数据,代入长短期记忆神经网络LSTM进行离线训练;之后,比较步骤B中所进行的离线训练的结果,在集群电动汽车管理系统中安装具有最佳训练效果的LSTM;最后,在线采集数据输入LSTM,在线生成调度结果,下达调度指令。本方法在离线阶段进行数学计算,在在线运行时只需要通过训练好的LSTM网络匹配输入和输出的关系,快速得到近似最优的调度信号,降低了对在线运行时CPU的要求,适合于大规电动汽车的在线调度计算。
Cluster electric vehicle power optimization management method based on machine learning
一种基于机器学习的集群电动汽车功率优化管理方法
2020-06-19
Patent
Electronic Resource
Chinese
IPC: | H02J CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER , Schaltungsanordnungen oder Systeme für die Abgabe oder Verteilung elektrischer Leistung / B60L PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES , Antrieb von elektrisch angetriebenen Fahrzeugen / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung |
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