North Carolina State University

Total Sa

Total Solar International

Totalenergies Onetech

Carlos Carrejo

Ning Lu

Mo-Yuen Chow

Gonzague Henri

Cong Sheng Huang

Gonzaque Henri

A method, system, and device for controlling energy storage devices are provided, the method including receiving a trained machine learning model from a centralized machine learning system, recording temporal data for a respective energy storage device, periodically transmitting the temporal data to the machine learning system, performing a mode prediction for controlling the energy storage device using the trained machine learning model and the temporal data, and sending a control signal to the energy storage device to operate in the predicted mode. The machine learning system aggregates the temporal data transmitted by each agent and uses the aggregated temporal data to update the machine learning model. By using aggregated temporal data, less data is needed from an individual energy storage device so that when a new energy storage device joins the machine learning system, the new energy storage device can benefit from increased performance with less computation.

Multi-agent shared machine learning approach for real-time battery operation mode prediction and control

A method and an apparatus for battery modelling. The method includes acquiring battery information from a sensor attached to a battery, the battery information including at least a terminal voltage and a load current; classifying, the battery information as effective data or ineffective data based on a phase of a battery cycle during which the battery information is acquired; identifying one or more parameters of the circuit model associated with the battery based on the effective data; and generating an estimation of a state of the battery using the circuit model having the one or more parameters identified using the effective data. Further, a circuit model is identified using effective data.

Apparatus, circuit model, and method for battery modelling

Growing community of inventors

Paris, France

Carlos Carrejo