Automated multi-dimensional dynamic planning algorithm for solving energy management problems in fuel cell electric vehicles

1. The AuDP algorithm does not require any hyperparameter adjustment and can meet various constraints.
You can compute the optimal control results under different gas purge time constraints by adjusting the variable [OFF2ON] below.

2. The battery model integrates the SOP algorithm recommended by the battery supplier and includes a simple battery thermal model.
However, we currently do not have permission to disclose the SOP data, so parts of the code involving battery data have been encapsulated.
The open-source code is sufficient to demonstrate most of the details of AuDP.
In the future, we will seek publicly available SOP data and open-source all the code.


3. It is recommended to read the AuDP files in the following order:
+AuDP_Function/AuDP.m
+AuDP_Function/AuDP_Single_Step.m
+AuDP_Function/Mode_Masking.m
+AuDP_Function/Start_Mode.m
+AuDP_Function/Work_Mode.m
+AuDP_Function/Close_Mode.m
+AuDP_Function/EV_Mode.m
+AuDP_Function/SOC_Masking.m
+AuDP_Function/Data_Merge.m
+AuDP_Function/Result_Display.m

4. Running [main.m] to get the result of the calculation.
You can also directly read the data in [+Data_Storage] to view the calculation results,
and use [+AuDP_Function/Result_Display] to visualize the data.

5. This code was developed using Matlab 2022b, so it is recommended to run it in Matlab 2022b to avoid potential errors.
On a laptop configured with a 12th Gen Intel(R) Core(TM) i9-12900HX 2.30 GHz CPU, 32.0 GB RAM, and RTX3080Ti,
the runtime of this code is approximately 185–195 seconds.
Note that different Matlab versions and laptop configurations may result in varying computation times, which is normal.

1. AuDP算法无需调整任何超参数，即可满足多种约束条件。您可以通过调整以下变量[OFF2ON]，在不同气体吹扫时间约束下计算最优控制结果。

2. 电池模型集成了电池供应商推荐的SOP算法，并包含了一个简单的电池热模型。然而，由于目前尚未获得披露SOP数据的许可，因此涉及电池数据的部分代码已被封装。开源代码足以展示AuDP的大部分细节。未来，我们将寻求公开可用的SOP数据，并将所有代码开源。

3. 建议按以下顺序阅读AuDP文件：
+AuDP_Function/AuDP.m
+AuDP_Function/AuDP_Single_Step.m
+AuDP_Function/Mode_Masking.m
+AuDP_Function/Start_Mode.m
+AuDP_Function/Work_Mode.m
+AuDP_Function/Close_Mode.m
+AuDP_Function/EV_Mode.m
+AuDP_Function/SOC_Masking.m
+AuDP_Function/Data_Merge.m
+AuDP_Function/Result_Display.m

4. 运行[main.m]以获取计算结果。您还可以直接读取[+Data_Storage]中的数据以查看计算结果，并使用[+AuDP_Function/Result_Display]可视化数据。

5. 本代码是在Matlab 2022b环境中开发的，因此建议在Matlab 2022b中运行以避免潜在的错误。在配置了第12代Intel(R) Core(TM) i9-12900HX 2.30 GHz CPU、32.0 GB RAM和RTX3080Ti的笔记本电脑上，本代码的运行时间约为185-195秒。请注意，不同的Matlab版本和笔记本电脑配置可能导致计算时间不同，这是正常的。