The invention discloses a fuel cell vehicle driving range prediction method based on historical real-time energy consumption, which comprises the following steps: carrying out standardization test on a fuel cell vehicle to obtain historical data, and collecting open road data to construct a speed history curve; processing the historical data to obtain model input data, and importing the model input data into the original CNN-LSTM energy consumption model for training to obtain an optimized CNN-LSTM energy consumption model; dividing speed history curve segments to obtain speed history segments, obtaining corresponding segment mileage through integration, and inputting the speed history segments into the optimized CNN-LSTM energy consumption model to obtain current segment energy consumption; calculating residual energy and historical unit energy consumption mileage according to the corresponding fragment mileage and the current fragment energy consumption; and a historical real-time strategy is adopted for the historical unit energy consumption mileage to obtain the optimized unit energy consumption mileage, the remaining energy and the optimized unit energy consumption mileage are multiplied to obtain a driving mileage prediction value, and fuel cell vehicle driving mileage prediction is achieved.
本发明公开了一种基于历史实时能耗的燃料电池汽车续驶里程预测方法,通过对燃料电池汽车进行标准化测试获得历史数据,采集开放道路数据构建速度历程曲线;对历史数据进行处理获得模型输入数据,将模型输入数据导入原始CNN‑LSTM能耗模型进行训练,获得优化CNN‑LSTM能耗模型;对速度历程曲线片段划分,获得速度历程片段,通过积分获得对应片段里程,将速度历程片段输入优化CNN‑LSTM能耗模型中获得当前片段能耗;根据对应片段里程、当前片段能耗计算剩余能量和历史单位能耗行驶里程;对历史单位能耗行驶里程采用历史实时策略获得优化单位能耗行驶里程,剩余能量和优化单位能耗行驶里程相乘获得续驶里程预测值,实现燃料电池汽车续驶里程预测。
Fuel cell vehicle driving range prediction method based on historical real-time energy consumption
基于历史实时能耗的燃料电池汽车续驶里程预测方法
2023-12-12
Patent
Electronic Resource
Chinese
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