Abstract:
A charging system includes a service office, a charging station, a charging plug, a plurality of cameras, and a controller. The charging station is in communication with the service office. The service office is remote from the charging station. The charging plug is coupled to the charging station. The charging plug is operable to charge a battery of an electric vehicle. The plurality of cameras is coupled to the charging station. The plurality of cameras is operable to generate a plurality of images of the charging plug from a plurality of directions. The controller is disposed in the charging station. The controller is operable to transmit the plurality of images to the service office. The service office is operable to determine a physical state of the charging plug based on the plurality of images received from the controller.
Abstract:
Methods and systems are provided for monitoring a fuel injector of an internal combustion engine. In one embodiment, a method includes: receiving a set of feature data, the feature data sensed from a fuel injector during a fuel injection event; processing, by a processor, the set of feature data with a machine learning model to generate a prediction of a fault status; and selectively generating, by the processor, a notification signal based on the prediction.
Abstract:
System and methods for estimating a relationship between a SOC and an OCV of a battery system included in a vehicle are presented. In certain embodiments, an initial relationship between an open circuit voltage (“OCV”) and a state of charge (“SOC”) of a cell of the battery system may be determined at a beginning of life of the cell. Changes in one or more stoichiometric points of a half-cell of the cell may be determined as the cell ages. Based on the determined stoichiometric point changes of the half-cell, an initial relationship between the OCV and the SOC of the cell may be adjusted to generate an updated relationship between the OCV and the SOC of the cell.
Abstract:
A system for use with a battery and sensors operable for measuring battery data includes an interactive user interface and a controller programmed with battery degradation monitoring logic for estimating a state of the battery. As part of a method, the controller identifies data bins for which measured state of charge range-based battery performance data is missing or dated/stale, and automatically prompts an operator to execute an assigned task corresponding to the identified data bins. The controller records the battery performance data for the identified data bins upon completion of the assigned task, estimates the state of the battery using the recorded battery performance data and the battery degradation monitoring logic, and executes a control action with respect to the system using the estimated state. A virtual or actual reward feature may be displayed in response to completion of the assigned task.
Abstract:
A number of illustrative variations may include a method, which may include using at least a segment of impedance-based battery power capability estimation data, and using real-time linear regression, which may be used as a method of estimating future behavior of a system based on current and previous data points, to provide a robust state of power predictor.
Abstract:
A system for optimizing life of a battery pack in a plug-in vehicle includes sensors for measuring battery performance data, including an open-circuit voltage, charging current, and/or temperature of the battery pack, a GPS receiver, a user interface, and a controller. The controller executes a method to monitor degradation of the battery pack using the performance data, and determines driving and charging histories for an operator of the vehicle using the measured battery performance data and a position signal from the GPS receiver. The histories identify the days, hours, and locations at which the operator has driven the vehicle and charged the battery pack. The controller identifies a state of charge data bin missing performance data or containing old performance data. The controller then controls a charging operation of the battery pack via a charging control signal, and records the measured battery performance data for the identified SOC data bin.
Abstract:
A system for optimizing life of a battery pack in a plug-in vehicle includes sensors for measuring battery performance data, including an open-circuit voltage, charging current, and/or temperature of the battery pack, a GPS receiver, a user interface, and a controller. The controller executes a method to monitor degradation of the battery pack using the performance data, and determines driving and charging histories for an operator of the vehicle using the measured battery performance data and a position signal from the GPS receiver. The histories identify the days, hours, and locations at which the operator has driven the vehicle and charged the battery pack. The controller identifies a state of charge data bin missing performance data or containing old performance data. The controller then controls a charging operation of the battery pack via a charging control signal, and records the measured battery performance data for the identified SOC data bin.
Abstract:
A number of variations include a method, which may include using at least a segment of voltage-based Battery State Estimation data, and using real-time linear regression, which may be a method of estimating future behavior of a system based on current and previous data points, to provide a robust and fast-adapting impedance response approximator. Linear regression may be performed by forming an RC circuit which is “equivalent” to electrochemical impedance spectroscopy data and processing the runtime values of that RC circuit using any number of known real-time linear regression algorithms including, but not limited, to a weighted recursive least squares (WRLS), Kalman filter or other means.
Abstract:
Methods are disclosed for modeling changes in capacity and the state of charge vs. open circuit voltage (SOC-OCV) curve for a battery cell as it ages. During battery pack charging, voltage and current data are gathered for a battery cell. In one method, using multiple data points taken during the plug-in charge event, data optimization is used to determine values for two parameters which define a scaling and a shifting of the SOC-OCV curve from its original shape at the cell's beginning of life to its shape in the cell's current condition. In a second method, only initial and final voltages and current throughput data are needed to determine the values of the two parameters. With the scaling and shifting parameters calculated, the cell's updated capacity and updated SOC-OCV curve can be determined. The methods can also be applied to data taken during a discharge event.
Abstract:
In an embodiment, a method is provided that includes obtaining sensor data for a vehicle having an energy storage system that is configured provide power for a home under certain conditions; obtaining home data as to a plurality of characteristics that pertain to power requirements for the home; and calculating, via a processor, a discharge time for the energy storage system based on the sensor data for the vehicle and the plurality of characteristics of the home.