Abstract: A method and system for monitoring a charge capacity of a battery includes determining a predicted charge capacity and a first uncertainty parameter based upon the current, voltage, and temperature of the battery, wherein the predicted charge capacity is determined by executing a charge capacity degradation model. A measured charge capacity and an associated second uncertainty parameter of the battery are also determined, by executing a charge capacity update routine. A charge capacity estimate for the battery is determined based upon the predicted charge capacity and the measured charge capacity, and an updated uncertainty parameter for the charge capacity estimate is determined based upon the first and the second uncertainty parameters. An estimated covariance parameter, and a covariance ratio are determined based upon the updated uncertainty parameter and the estimated covariance parameter.

Abstract: A method for estimating a state of a battery pack using a controller having battery state estimator (BSE) logic includes receiving or delivering a constant baseline current via the battery pack. Current oscillations having time-variant frequency content are selectively injected into the baseline current via the controller in response to a predetermined condition. The baseline current and the current oscillations combine to form a final current. The method includes estimating a battery parameter via the BSE logic concurrently with the current oscillations to generate an estimated battery parameter, and estimating the present state of the battery pack via the controller using the estimated battery parameter. An electrical system includes a rotary electric machine that is electrically connected to and driven by the battery pack, and a controller configured to execute the method.

Abstract: An apparatus and method for tracking a battery cell is disclosed, for a device having one or more sensors and a controller with a processor and tangible, non-transitory memory. The method includes obtaining respective sensor data relative to an anode and a cathode. A predicted anode capacity and predicted cathode capacity are determined based on the respective sensor data. The predicted anode capacity and predicted cathode capacity each have a respective variance value. An updated set of variables and updated respective variance values are generated based in part on the predicted anode capacity, the predicted cathode capacity and a measured equilibrium voltage, via a Kalman filter module executed by the controller. The updated set of variables include an updated anode capacity and an updated cathode capacity. Operation of the device is controlled based in part on the updated set of variables and updated respective variance values.

Abstract: A method for battery capacity estimation is provided. The method includes monitoring a sensor, collecting a plurality of data points including a voltage-based state of charge value and an integrated current value, defining within the data points a first data set collected during a first time period and a second data set collected during a second time period, determining an integrated current error related to the second data set, comparing the integrated current error related to the second data set to a threshold integrated current error. When the error related to the second data set exceeds the threshold, the method further includes resetting the second data set based upon an integrated current value from the first time period. The method further includes combining the data sets to create a combined data set and determining a voltage slope capacity estimate as a change in integrated current versus voltage-based state of charge.

Abstract: A method for battery capacity estimation is provided. The method includes, within a computerized processor, monitoring a sensor operable to gather data regarding a battery, determining a voltage-based state of charge for the battery based upon the data from the sensor, determining a capacity degradation value for the battery based upon the data from the sensor, determining an integrated current value through Coulomb counting based upon the data from the sensor, determining a predicted battery state of charge for the battery based upon the capacity degradation value and the integrated current value, processing the voltage-based state of charge and the predicted battery state of charge using a Kalman filter to generate an updated overall battery capacity estimate, and using the updated overall battery capacity estimate to control management of the battery.

Abstract: A method and system for monitoring a charge capacity of a battery includes determining a predicted charge capacity and a first uncertainty parameter based upon the current, voltage, and temperature of the battery, wherein the predicted charge capacity is determined by executing a charge capacity degradation model. A measured charge capacity and an associated second uncertainty parameter of the battery are also determined, by executing a charge capacity update routine. A charge capacity estimate for the battery is determined based upon the predicted charge capacity and the measured charge capacity, and an updated uncertainty parameter for the charge capacity estimate is determined based upon the first and the second uncertainty parameters. An estimated covariance parameter, and a covariance ratio are determined based upon the updated uncertainty parameter and the estimated covariance parameter.

Abstract: A wiper system for use with a windshield includes a track guide, a wiper assembly, a drive mechanism and a wipe mechanism. The wiper assembly has a wiper arm attached at a first end thereof to a rotor rotatably disposed on a wiper carrier, wherein the wiper carrier is engaged with the track guide and is configured for translation therealong. The drive mechanism is connected with the wiper carrier and is configured for positioning the wiper carrier along the track guide. The wipe mechanism is connected with at least one of the rotor and the wiper carrier and is configured to cause the rotor to rotate, thereby causing the wiper arm to produce a wiping motion.

Abstract: An electrical system includes a battery pack, sensors, and a controller. The sensors configured output measured state signals indicative of an actual state of the battery back, including a respective actual voltage, current, and temperature of each of the multiple battery cells. The controller executes a method to generate, responsive to the measured state signals, an estimated state of the multiple battery cells using a respective open-circuit voltage and low-frequency transient voltage of each of the multiple battery cells. The controller estimates the low-frequency transient voltages using a porous electrode transient (PET) model as part of a model set, the PET model having open-circuit voltage elements representing uneven charge distribution within a cell electrode. State of charge (SOC) of the battery pack is estimated using the estimated voltages. An operating state of the electrical system is controlled in real-time responsive to the estimated SOC.

Abstract: An electrical system includes a battery, sensors, and a controller. The sensors output measured signals indicative of an actual state of the battery, including respective actual voltage, current, and temperature signals for each battery cell. The controller, in conducting a method, generates an estimated state of the battery, including a predicted voltage of the battery, doing so responsive to the signals using an open-circuit voltage and an output of an empirical model. An operating state of the electrical system is controlled using the estimated state. The empirical model includes low-pass/band-pass filters and a high-pass filter each with a different time-constant, the time-constants being spread over a time-constant range. Each low-pass/band-pass filter branches through a basis function(s) whose output(s) are multiplied by a respective resistance value to generate higher-frequency voltage transients. The controller sums the open-circuit voltage and voltage transients to derive the predicted voltage.

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: An electrical system includes a battery, sensors, and a controller. The sensors output measured signals indicative of an actual state of the battery, including respective actual voltage, current, and temperature signals for each battery cell. The controller, in conducting a method, generates an estimated state of the battery, including a predicted voltage of the battery, doing so responsive to the signals using an open-circuit voltage and an output of an empirical model. An operating state of the electrical system is controlled using the estimated state. The empirical model includes low-pass/band-pass filters and a high-pass filter each with a different time-constant, the time-constants being spread over a time-constant range. Each low-pass/band-pass filter branches through a basis function(s) whose output(s) are multiplied by a respective resistance value to generate higher-frequency voltage transients. The controller sums the open-circuit voltage and voltage transients to derive the predicted voltage.

Abstract: An electrical system includes a battery pack, sensors, and a controller. The sensors configured output measured state signals indicative of an actual state of the battery back, including a respective actual voltage, current, and temperature of each of the multiple battery cells. The controller executes a method to generate, responsive to the measured state signals, an estimated state of the multiple battery cells using a respective open-circuit voltage and low-frequency transient voltage of each of the multiple battery cells. The controller estimates the low-frequency transient voltages using a porous electrode transient (PET) model as part of a model set, the PET model having open-circuit voltage elements representing uneven charge distribution within a cell electrode. State of charge (SOC) of the battery pack is estimated using the estimated voltages. An operating state of the electrical system is controlled in real-time responsive to the estimated SOC.

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 number of variations may include products and methods for estimating the state of an energy system. At least one sensor may monitor a voltage and a current of the energy storage system. An electronic controller may be communicatively coupled with the energy storage system and may receive input from the sensor. A circuit may be representative of the energy storage system and may be appropriately defined in the electronic controller. The circuit may estimate a state of the energy storage system from a reading of the voltage and the current.

Abstract: A number of variations may include a product comprising: an electrochemical device comprising an anode and a cathode, and at least one sensor comprising a plurality of strain sensing components and at least one temperature sensing component wherein each of the anode and the cathode comprises at least one strain sensing component comprising an optical fiber comprising at least one grating, wherein the at least one sensor is constructed and arranged to provide measurements that derive both state of charge and temperature of the anode and the cathode simultaneously.

Abstract: A number of variations may include a product comprising: at least one sensor comprising an optical fiber comprising a first end comprising a semiconductor material, a second end, and a longitudinal midsection comprising a grating, wherein the sensor is constructed and arranged to provide measurements that derive both state of charge and temperature of an electrochemical device simultaneously.

Abstract: During the charging of lithium-ion batteries, comprising graphite anode particles, the goal is to intercalate lithium into the anode materials as LiC6. But it is possible to conduct the charging process at a rate that lithium is undesirably plated, undetected, as lithium metal on the particles of graphite. During an open-circuit period of battery operation, immediately following such a charging period, the presence of lithium plating can be detected, using a computer-based monitoring system, by continually measuring the cell potential (Vcell) over a brief period of open-circuit time, fitting the open-circuit voltage data to a best cubic polynomial fit, and then determining dVcell/dt (mV/s) from the polynomial fit over a like period of time. It is found that the presence of a maximum or a minimum in the derivative curve (a local minimum) reliably correlates with plated lithium on the graphite particles of the anode.

Abstract: A discharge module is configured to determine a change in capacity of the battery between: (i) a measurement of a first open circuit voltage (OCV) of a battery of a vehicle; and (ii) a measurement of a second OCV of the battery. A lookup table is stored in memory and includes reference states of charge (SOCs) indexed by reference OCVs and reference capacities. A relationship module is configured to: from the lookup table, identify a first set of the reference SOCs associated with the first OCV and the reference capacities, respectively; from the lookup table, identify a second set of the reference SOCs associated with the second OCV and the reference capacities, respectively; determine changes in SOC associated with the reference capacities; determine changes in capacity; and determine an equation that relates changes in capacity to capacity based on the changes in capacity and the reference capacities, respectively.

Abstract: Disclosed are battery management systems with control logic for battery state estimation (BSE), methods for making/using/assembling a battery cell with a reference electrode, and electric drive vehicles equipped with a traction battery pack and BSE capabilities. In an example, a battery cell assembly includes a battery housing with an electrolyte composition stored within the battery housing. The electrolyte composition transports ions between working electrodes. A first working (anode) electrode is attached to the battery housing in electrochemical contact with the electrolyte composition. Likewise, a second working (cathode) electrode is attached to the battery housing in electrochemical contact with the electrolyte composition. A reference electrode is interposed between the first and second working electrodes, placed in electrochemical contact with the electrolyte composition.

Abstract: Systems and methods are disclosed for estimating a state of a battery system such as a current-limited state of power and/or a voltage-limited state of power using a battery system model incorporating a nonlinear resistance element. Parameters of elements included in a battery cell model associated with a nonlinear resistance of a battery cell may be directly parameterized and used in connection with state estimation methods. By accounting for the nonlinear effect, embodiments of the disclosed systems and methods may increase available battery power utilized in connection with battery system control and/or management decisions over a larger window of operating conditions.