The invention provides an energy management method and device based on working condition self-adaption, equipment and a storage medium, and the method comprises the steps: constructing a neural network recognition model through dividing three working conditions, and outputting a predicted recognition result; using conditions of an automobile power battery and a fuel battery and an automobile driving state are obtained, the equivalent hydrogen consumption amount of the whole automobile is selected to construct an optimization target model, and then off-line optimization is carried out on parameters of a fuzzy controller by using a genetic algorithm; according to the three divided working conditions, the obtained automobile battery energy data are used as parameters to be input into the updated fuzzy controller, and a fuzzy energy management strategy is obtained; according to the prediction recognition result output by the working condition recognition module, the fuzzy energy management strategy corresponding to the prediction recognition result is adaptively selected, and energy management is carried out through the current automobile working condition recognition result and the fuzzy energy management strategy, so that the energy of the whole automobile can be reasonably utilized, and the energy utilization rate of the whole automobile is effectively improved; the service life of the power battery is prolonged.
本发明提出基于工况自适应的能量管理方法、装置、设备及存储介质,通过划分三种工况,构建神经网络识别模型输出预测的识别结果;获取汽车动力电池和燃料电池的使用情况,以及汽车行驶状态,选定整车的等效氢气消耗量构建优化目标模型,再使用遗传算法对模糊控制器的参数进行离线寻优;根据划分的三种工况,将获取到的汽车电池能量数据作为参数输入到更新后的模糊控制器中,得到模糊能量管理策略;根据工况识别模块输出的预测识别结果,自适应选择与之对应的模糊能量管理策略,通过当前汽车工况识别结果以及所述模糊能量管理策略进行能量管理,从而能够对整车能量合理利用,有效提高整车的能量利用率,延长动力电池的使用寿命。
Energy management method, device and equipment based on working condition self-adaption and storage medium
基于工况自适应的能量管理方法、装置、设备及存储介质
2023-01-24
Patent
Elektronische Ressource
Chinesisch
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