Abstract: A method for determining an optimal state-of-charge (SOC) operating window for a battery for use in an electric vehicle includes learning a pattern of periodic charging of the battery for a plurality of time periods and a pattern of periodic usage of the battery for the plurality of time periods, determining a periodic energy requirement for the battery for the plurality of time periods based on the learned patterns using a statistical model, and setting a maximum SOC level and a minimum SOC level for the SOC operating window based on two or more of the periodic energy requirement, the learned patterns and a battery chemistry of the battery.

Abstract: A system for monitoring a battery of a vehicle includes a processor and a memory storing instructions which when executed by the processor configure the processor to receive first features including statistics of internal resistances of a plurality of cell groups in a battery pack of the battery, compute second features for the battery pack based on the first features, determine whether the battery pack is faulty based on one or more of the second features, and determine, in response to the battery pack being faulty, whether one or more of the cell groups is faulty based on one or more of the first features.

Abstract: A system for monitoring a battery of a vehicle includes a current measuring circuit to measure a current of the battery comprising a plurality of cell groups connected to each other. A voltage measuring circuit is to measure voltages of the cell groups. A controller is configured to define a plurality operating regions in a current profile of the battery during a drive cycle of the vehicle. The controller is configured to filter the current and the voltages measured in the operating regions and calculate internal resistances of the cell groups in the operating regions based on the filtered current and voltages. The controller is configured to generate statistical values based on the internal resistances of the cell groups and determine whether one or more of the cell groups is faulty based on differences between maximum and minimum values of one of the statistical values across the cell groups.

Abstract: A method for estimating remaining energy in a battery pack having series-connected cells/cell groups includes measuring battery parameters, including a battery voltage, current, and temperature. The controller estimates a static state of charge difference (?SOC) value and a current-dependent ?SOC value in real-time using the parameters, including calculating the static ?SOC value as a difference between an average SOC of the battery pack and an SOC of a weakest/lowest energy cell group. The current-dependent ?SOC value is a percentage SOC per unit of the current. The static ?SOC value and current-dependent ?SOC values are filtered via a multi-parameter state estimator block. Using the filtered state values, the controller executes a control action responsive to the estimated remaining energy, including displaying the remaining energy and/or a quantity derived from the remaining energy via a display device. A powertrain system includes the controller, electric machine, and battery pack.

Abstract: System and method of controlling operation of a device having a rechargeable energy storage pack with a plurality of cells, based on propulsion loss assessment. A controller is configured to obtain a state of charge data and an open circuit voltage of the rechargeable energy storage pack. The controller is configured to obtain a state of charge disparity factor (dSOC) from a selected dataset. The state of charge disparity factor (dSOC) is defined as a difference between a minimum value of the state of charge and an average value of the state of charge of the plurality of cells. The controller is configured to control operation of the device based in part on the state of charge disparity factor (dSOC) and a plurality of parameters (Pi), including raising one or more of a plurality of flags each transmitting respective information to a user.

Abstract: A method for diagnosing battery pack faults includes connecting a diagnostic service tool (DST) to the battery pack and measuring battery parameters using one or more electrical sensors, including a voltage of each cell/cell group. The method includes calculating, via the DST using the battery parameters, a section-average state of charge (SOC) of each battery section and identifying, from among the cells/cell groups of each respective section, a particular one of the cells or cell groups having a lowest cell SOC. For each respective battery section, a ?SOC value is calculated as a difference between the section-average and lowest cell SOC, including comparing the ?SOC value for each section to a calibrated threshold. A repair action is executed or initiated with respect to the battery pack, via the DST, responsive to the ?SOC value for one or more sections exceeding the calibrated threshold.

Abstract: A method for estimating remaining energy in a battery pack having series-connected cells/cell groups includes measuring battery parameters, including a battery voltage, current, and temperature. The controller estimates a static state of charge difference ( ?SOC) value and a current-dependent ?SOC value in real-time using the parameters, including calculating the static ?SOC value as a difference between an average SOC of the battery pack and an SOC of a weakest/lowest energy cell group. The current-dependent ?SOC value is a percentage SOC per unit of the current. The static ?SOC value and current-dependent ?SOC values are filtered via a multi-parameter state estimator block. Using the filtered state values, the controller executes a control action responsive to the estimated remaining energy, including displaying the remaining energy and/or a quantity derived from the remaining energy via a display device. A powertrain system includes the controller, electric machine, and battery pack.

Abstract: System and method of controlling operation of a device having a rechargeable energy storage pack with a plurality of cells, based on propulsion loss assessment. A controller is configured to obtain a state of charge data and an open circuit voltage of the rechargeable energy storage pack. The controller is configured to obtain a state of charge disparity factor (dSOC) from a selected dataset. The state of charge disparity factor (dSOC) is defined as a difference between a minimum value of the state of charge and an average value of the state of charge of the plurality of cells. The controller is configured to control operation of the device based in part on the state of charge disparity factor (dSOC) and a plurality of parameters (Pi), including raising one or more of a plurality of flags each transmitting respective information to a user.

Abstract: Methods for fast-charging battery packs having at least one lithium battery cell with an anode, a cathode, and a reference electrode (RE) comprise charging the battery in a first phase by maximizing charging current, subsequently charging the battery in a second phase by decreasing the charging current in response to an anode potential (AP) determined by a RE to maintain the AP at or above an AP threshold, and subsequently charging the battery in a third phase by decreasing the charging current in response to the cathode potential (CP) determined by the RE such that the CP is maximized without exceeding the cathode potential threshold. A controller can determine anode potential or cathode potential in real time using a cell potential signal and a cathode RE signal or an anode RE signal, respectively. The AP threshold is the AP above which substantially no lithium plating occurs.

Abstract: Methods for fast-charging battery packs having at least one lithium battery cell with an anode, a cathode, and a reference electrode (RE) comprise charging the battery in a first phase by maximizing charging current, subsequently charging the battery in a second phase by decreasing the charging current in response to an anode potential (AP) determined by a RE to maintain the AP at or above an AP threshold, and subsequently charging the battery in a third phase by decreasing the charging current in response to the cathode potential (CP) determined by the RE such that the CP is maximized without exceeding the cathode potential threshold. A controller can determine anode potential or cathode potential in real time using a cell potential signal and a cathode RE signal or an anode RE signal, respectively. The AP threshold is the AP above which substantially no lithium plating occurs.

Abstract: A charging system and method that may be used to automatically apply customized charging settings to a plug-in electric vehicle, where application of the settings is based on the vehicle's location. According to an exemplary embodiment, a user may establish and save a separate charging profile with certain customized charging settings for each geographic location where they plan to charge their plug-in electric vehicle. Whenever the plug-in electric vehicle enters a new geographic area, the charging method may automatically apply the charging profile that corresponds to that area. Thus, the user does not have to manually change or manipulate the charging settings every time they charge the plug-in electric vehicle in a new location.

Abstract: System and methods for estimating a temperature of a battery are presented. In some embodiments, a method of estimating a temperature of a battery system may utilize measured battery system temperature data and measured ambient temperature data. Based on the measured temperature data, an average estimated temperature of the battery system may be determined using, at least in part, an extended Kalman filter and an energy balance process model associated with the battery system.

Abstract: System and methods for estimating a temperature of a battery are presented. In some embodiments, a method of estimating a temperature of a battery system may utilize measured battery system temperature data and measured ambient temperature data. Based on the measured temperature data, an average estimated temperature of the battery system may be determined using, at least in part, an extended Kalman filter and an energy balance process model associated with the battery system.

Abstract: A charging system and method that may be used to automatically apply customized charging settings to a plug-in electric vehicle, where application of the settings is based on the vehicle's location. According to an exemplary embodiment, a user may establish and save a separate charging profile with certain customized charging settings for each geographic location where they plan to charge their plug-in electric vehicle. Whenever the plug-in electric vehicle enters a new geographic area, the charging method may automatically apply the charging profile that corresponds to that area. Thus, the user does not have to manually change or manipulate the charging settings every time they charge the plug-in electric vehicle in a new location.