SYSTEMS AND METHODS FOR DETERMINING VEHICLE BATTERY HEALTH
First Claim
1. A method performed by one or more computing device, comprising:
- receiving, by the one or more computing devices, information corresponding to internal resistances of a battery of a vehicle;
receiving, by the one or more computing devices, information corresponding to at least one other operating condition, in addition to the internal resistances, corresponding to the battery;
receiving a model that was trained on internal resistance and other information, from a plurality of vehicles, to predict remaining battery life;
evaluating the model based on the internal resistances and the at least one other operating condition to produce a prediction regarding the remaining battery life; and
communicating, by the one or more computing devices, the prediction, regarding the remaining battery life, to the relevant party.
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Abstract
Techniques described herein may be used to provide a driver of a vehicle with an accurate assessment of the remaining life of the vehicle battery. An on-board device may collect information from one or more sensors or devices within the vehicle. The information may be processed to generate a data set that accurately describes the current status and operating conditions of the battery. The data set may be used to evaluate the health of the battery and make predictions regarding the future performance of the battery, which may be communicated to the driver of the vehicle. Machine-learning techniques may be implemented to improve upon methodologies to evaluate the health of the battery and make predictions regarding battery performance.
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Citations
20 Claims
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1. A method performed by one or more computing device, comprising:
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receiving, by the one or more computing devices, information corresponding to internal resistances of a battery of a vehicle; receiving, by the one or more computing devices, information corresponding to at least one other operating condition, in addition to the internal resistances, corresponding to the battery; receiving a model that was trained on internal resistance and other information, from a plurality of vehicles, to predict remaining battery life; evaluating the model based on the internal resistances and the at least one other operating condition to produce a prediction regarding the remaining battery life; and communicating, by the one or more computing devices, the prediction, regarding the remaining battery life, to the relevant party. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. One or more computing devices comprising circuitry to:
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receive information corresponding to internal resistances of a battery of a vehicle; receive information corresponding at least one other operating condition, in addition to the internal resistances, corresponding to the battery; receive a model that was trained on internal resistance and other information, from a plurality of vehicles, to predict remaining battery life; evaluate the model based on the internal resistances and the at least one other operating condition to produce a prediction regarding the remaining battery life; and communicate the prediction, regarding the remaining battery life, to the relevant party. - View Dependent Claims (9, 10, 11, 12, 13, 14)
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15. One or more computing devices, comprising:
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a non-transitory memory device storing a plurality of processor-executable instructions; and a processor configured to execute the processor-executable instructions, wherein executing the processor-executable instructions causes the processor to; receive measurements of internal resistances of batteries installed at a plurality of vehicles; receive measurements of other operating conditions, in addition to the internal resistances, relating to the plurality of vehicles; train a model, using machine learning techniques and based on the measurements of internal resistance and based on the measurements of the other operating conditions, to predict battery failure in the plurality of vehicles; and transmit the trained model, to the plurality of vehicles, for prediction of battery failure at the plurality of vehicles. - View Dependent Claims (16, 17, 18, 19, 20)
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Specification