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SYSTEMS, METHODS, AND STORAGE MEDIA FOR ADAPTING MACHINE LEARNING MODELS FOR OPTIMIZING PERFORMANCE OF A BATTERY PACK

机译:用于适应机器学习模型以优化电池组性能的系统,方法和存储介质

摘要

Systems, methods, and storage media for optimizing performance of a vehicle battery pack are disclosed. A method includes receiving data pertaining to cells within a battery pack installed in each vehicle of a fleet of vehicles, the data received from at least one of each vehicle, providing the data to a machine learning server, and directing the machine learning server to generate a predictive model. The predictive model is based on machine learning of the data. The method further includes providing the predictive model to each vehicle, the predictive model providing instructions for adjusting configuration parameters for each of the cells in the battery pack such that the battery pack is optimized for a particular use, and directing each vehicle to optimize performance of the vehicle battery pack based on the predictive model.
机译:公开了用于优化车辆电池组的性能的系统,方法和存储介质。一种方法包括:接收与安装在一组车队的每辆车中的电池组内的单元有关的数据;从每辆车中至少一个接收的数据;将数据提供给机器学习服务器;以及指导机器学习服务器生成预测模型。预测模型基于数据的机器学习。该方法进一步包括向每个车辆提供预测模型,该预测模型提供用于调整电池组中的每个电池单元的配置参数的指令,从而针对特定用途优化电池组,并指导每个车辆以优化其性能。基于预测模型的车辆电池组。

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