The invention provides an ECMS strategy optimization method based on a working condition clustering result of navigation information, and the method comprises the steps: carrying out the offline simulation according to the data of a real vehicle, and obtaining the operation segment division of each segment of the data of the vehicle; training of a working condition identification neural network model is carried out on the operation segment; cleaning and repairing key road condition signals in the navigation information to obtain repairing data; on the basis of the restoration data, mileage window division is carried out, and correction about congestion and gradient is obtained; calculating working condition characteristic parameters of each time window under the actual navigation repair data by using the time windows divided based on the actual navigation repair data in the step 3 and the step 4; performing clustering division of working conditions according to the working condition characteristic parameters and a neural network model, and matching a corresponding optimal equivalent factor according to the database in the step 1; and correcting a navigation clustering working condition output result according to an optimal equivalent factor obtained by historical vehicle speed clustering. According to the method, the oil consumption is greatly reduced.
本发明提供了一种基于导航信息的工况聚类结果的ECMS策略优化方法,包括:根据实车跑车数据进行离线仿真,获得每段跑车数据的运行片段划分;对所述运行片段进行工况识别神经网络模型的训练;对导航信息中关键路况信号进行清洗以及修复,获得修复数据;在所述修复数据基础上进行里程窗口划分,获得关于拥堵和坡度的修正;利用所述步骤三和四的基于实际导航修复数据划分的时间窗口,计算出实际导航修复数据下各时间窗口的工况特征参数;根据工况特征参数和神经网络模型进行工况的聚类划分,并根据所述步骤一的数据库匹配对应最优的等效因子;根据历史车速聚类得到的最优等效因子对导航聚类工况输出结果进行修正。本发明方法大大降低了油耗。
ECMS strategy optimization method of working condition clustering result based on navigation information
一种基于导航信息的工况聚类结果的ECMS策略优化方法
2023-01-24
Patent
Electronic Resource
Chinese
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