The invention relates to battery state of charge control using machine learning. Control of battery state of charge using machine learning is provided. A system of an electric vehicle identifies data including a state of charge of a battery of the electric vehicle, a state of health of the battery of the electric vehicle, and a driving mode of the electric vehicle. The system establishes a schedule for controlling charging of the battery of the electric vehicle based on inputting the data into a local model configured on the electric vehicle and trained with machine learning. The system executes the schedule in response to a power source electrically coupled to the battery of the electric vehicle to control an amount of current supplied from the power source to the battery of the electric vehicle.
本公开涉及使用机器学习的电池荷电状态控制。提供了使用机器学习来控制电池荷电状态。一种电动汽车的系统识别包括该电动汽车的电池的荷电状态、该电动汽车的该电池的健康状态和该电动汽车的驾驶模式的数据。该系统基于将该数据输入到配置在该电动汽车上并且用机器学习训练的本地模型中,建立控制该电动汽车的该电池充电的时间表。该系统响应于电耦合到该电动汽车的该电池的电源来执行该时间表,以控制从该电源供应到该电动汽车的该电池的电流量。
Battery state of charge control using machine learning
使用机器学习的电池荷电状态控制
2023-10-31
Patent
Elektronische Ressource
Chinesisch
IPC: | B60L PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES , Antrieb von elektrisch angetriebenen Fahrzeugen |
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