An approach to forecasting battery health as a dynamic time-series problem as opposed to a static prediction problem is presented. Systems and methods disclosed herein forecast a trajectory to failure by predicting a path to failure as opposed to only predicting when the battery may fail. A machine-learning model is implemented that extracts unique features taken from time-series data, such as time snippets of charging data. The raw time-series data may include current voltage and temperature with complex transformations and without capturing a full cycle, which permits wider applicability to instances of varying depth of discharge (DoD).
System and method for forecasting battery state with imperfect data
2024-11-26
Patent
Electronic Resource
English
IPC: | G07C TIME OR ATTENDANCE REGISTERS , Zeit- oder Anwesenheitskontrollgeräte / B60L PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES , Antrieb von elektrisch angetriebenen Fahrzeugen / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / H01M Verfahren oder Mittel, z.B. Batterien, für die direkte Umwandlung von chemischer in elektrische Energie , PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY |
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