Abstract: A battery system is provided, including a processing module and a plurality of battery modules. Each of the plurality of battery modules includes a battery management system and an electrochemical cell pack controlled by the battery management system. The processing module is configured to control the electrochemical cell pack to alternately perform a discharging or charging operation. A sum of power of battery modules other than a first battery module in the plurality of battery modules is greater than power required by a target power-supplied object, and the first battery module is any one of the plurality of battery modules. A battery management system is configured to record a target time. The processing module or the battery management system is configured to determine a state of health of the electrochemical cell pack in the first battery module based on the target time.

Abstract: Uses of artificial intelligence in battery technology including a method that includes receiving a trained model, receiving sensor data from at least one sensor associated with a battery, and executing the trained model by a processor. Executing the trained model includes providing the sensor data as input to the trained model to generate a model output. The method also includes sending, from the processor to a charge controller coupled to the battery, a control signal that is based on the model output and automatically, by the charge controller, initiating or terminating charging of the battery based on the control signal.

Abstract: A battery diagnosing apparatus includes a measuring unit configured to measure voltage and temperature of a battery, an ohmic resistance determining unit configured to determine an ohmic resistance of the battery based on an impedance profile generated for the battery, and a control unit configured to calculate a voltage change amount by comparing the voltage of the battery measured by the measuring unit with a reference voltage, calculate a resistance change rate by comparing the ohmic resistance determined by the ohmic resistance determining unit with a reference resistance, judge an internal gas generation level of the battery by comparing magnitudes of the calculated resistance change rate and a criterion resistance change rate, and judge an internal gas generation cause of the battery by comparing magnitudes of the calculated voltage change amount and a criterion voltage change amount.

Abstract: A power supply is disclosed for an industrial control system or any system including a distributed power supply network. In embodiments, the power supply comprises: a battery module including a battery cell and a battery monitor configured to monitor the battery cell; and a self-hosted server operatively coupled with the battery module, the self-hosted server being configured to receive diagnostic information from the battery monitor and provide network access to the diagnostic information. In implementations, the diagnostics stored by the self-hosted server can be broadcast to or remotely accessed by enterprise control/monitoring systems, application control/monitoring systems, or other remote systems via a secured network (e.g., secured access cloud computing environment).

Abstract: A method for determining a predicted state of health of an electrical energy storage unit in a machine includes providing a data-based or hybrid state of health model, the data-based state of health model is trained, depending on operating variables of the electrical energy storage unit and/or operating features derived from the operating variables, to indicate a state of health and to indicate a model uncertainty of the indicated state of health, ascertaining a state of health characteristic and the associated model uncertainty of the energy storage unit based on the operating variables using the state of health model, and generating at least one random constructed state of health characteristic candidate that corresponds to constructed state of health characteristics within characteristic of confidence intervals, the characteristic of confidence intervals defined by the model uncertainties of the states of health of the ascertained state of health characteristic.

Abstract: Disclosed is an apparatus and method for controlling an operation of a secondary battery using a relative deterioration degree of an electrode. The method includes determining a SOC of the secondary battery whenever a pulse current flows through the secondary battery; determining an electrochemical reaction resistance from a voltage change amount measured during a preset initial time in each pulse current section and determining a lithium ion diffusion resistance from a voltage change amount measured during a remaining time except for the initial time; determining a deterioration-biased electrode by comparing a deterioration diagnosing resistance ratio, which is a relative ratio of the lithium ion diffusion resistance to the electrochemical reaction resistance, with a preset reference deterioration diagnosing resistance ratio; and adaptively adjusting an operation condition of a next charging/discharging cycle according to the type of the deterioration-biased electrode.

Abstract: Provided is a battery residual value determination system capable of easily and accurately determining the residual value of a battery. The battery residual value determination system includes: a battery information reception unit that receives information on the voltage, the current, the temperature, and the period of time elapsed from the time of manufacture of a battery; a first residual value determination unit that determines a first residual value indicating the SOH of the battery; an attenuation function determination unit that determines an attenuation function which indicates a time-dependent change of the SOH specific to the battery and is used for correcting the first residual value of the battery; and a second residual value output unit that determines and outputs a second residual value obtained by correcting the first residual value by using the attenuation function according to the period of time elapsed from the time of manufacture of the battery.

Abstract: A method for generating an energy usage profile for a software program executed in a computing device includes generating a call trace of an executed system call, identifying a first power consumption and duration of a first power state due to the first system call using a model, identifying a second power consumption and duration of a second power state based on the model, and generating an energy usage profile for the software program. The energy usage profile includes energy consumption of the computing device for the system call based on the first power consumption level multiplied by the first duration and the second power consumption level multiplied by the second duration associated an identifier for the call trace.

Abstract: The disclosure is generally directed to systems and methods for battery life cycle prediction for a preowned electrified vehicle including receiving state of charge (SOC) and mileage data associated with the preowned electrified vehicle, providing one or more driving maneuvers to be performed by a driver, providing one or more instructions to the driver to operate power-driven accessories of the preowned electrified vehicle, collecting data representing battery usage by the driver by monitoring the driving maneuvers and the operation of power-driven accessories as performed by the driver, and responsive to the collected data representing battery usage and the SOC and mileage, providing a battery life prediction for the preowned electrified vehicle.

Abstract: A battery management apparatus according to the present disclosure includes a memory to store a charging sequence table that records a correspondence relationship between first to mth temperature ranges, first to mth SOC lists and first to mth current lists, a sensing unit to detect a voltage, a current and a temperature of a battery, and a control unit. Each of the SOC lists defines first to nth SOC ranges. The control unit determines a current SOC of the battery based on the detected voltage and the detected current. The control unit determines a temperature range of interest, a SOC list of interest and a current list of interest based on the detected temperature. The control unit determines a remaining charging time required to charge the battery to a target SOC based on the detected current, the current SOC, the SOC list of interest and the current list of interest.

Abstract: An estimation device includes: a derivation unit (31) configured to derive a derivation history based on a current, a voltage of a lead-acid battery and a temperature of the lead-acid battery; a specifying unit (31) configured to specify one or more physical quantities based on the derivation history, and one or more relationships selected from a first relationship between a first history and an amount of positive active material, a second relationship between a second history and a specific surface area of a positive electrode material, a third relationship between a third history and bulk density of the positive active material, a fourth relationship between a fourth history and positive active material particles in a cluster size, a fifth relationship between a fifth history and a cumulative amount of lead sulfate of a negative electrode material, a sixth relationship between a sixth history and a specific surface area of the negative electrode material, a seventh relationship between a seventh history and

Abstract: A battery condition monitoring apparatus includes a measurer configured to measure a charging current which is an internal current of a converter and is charged into a sub-battery, a charging voltage of the converter, and an ambient temperature of a vehicle, an impedance calculator configured to an impedance of the sub-battery on basis of a voltage and a current each measured by the measurer, and a determiner configured to determine a condition of the sub-battery by using the ambient temperature of the vehicle and the impedance of the sub-battery.

Abstract: An electric automobile incorporating a secondary battery has a disadvantage such as a difficulty in knowing the remaining capacity accurately and in predicting the time when the remaining capacity becomes zero because of deterioration of the secondary battery. The internal resistance is estimated with high accuracy even when the secondary battery deteriorates. Data used for learning or estimation is a data group (also referred to as data with regenerative charging) that is limited to data acquired within a certain time range around the end of regenerative charging. Such data within the limited range is extracted, used for learning, and subjected to the estimation. Thus, a value of the internal resistance can be output with high accuracy, specifically, with a mean error rate of 1% or less.

Abstract: A method for assessing a state of charge/discharge (SOC/SOD) for a secondary electrochemical cell, the cell having a first operational mode during which the cell is charged from a power supply connected to terminals of the cell, a second operational mode during which the cell is discharged into a load and a rest mode, the method comprising steps of measuring entropy and enthalpy for the electrochemical cell in the course of the first and second operational modes and during rest, and calculating a data representative of the state of charge/discharge (SOC/SOD).

Abstract: An appropriate upper limit current value is set in consideration of steep change in battery voltage in a high-current region caused by the ion concentration gradient in a diffusion layer formed around an interface between an electrode and an electrolyte. An upper limit current calculator 152 includes: a concentration gradient estimator 1523 that estimates a lithium ion concentration gradient in a diffusion layer formed around an interface between an electrode and an electrolyte of a battery, based on a current flowing in the battery, or on the current and a temperature; and an upper limit current determiner 1524 that determines an upper limit current value of the battery, based on the lithium ion concentration gradient. The upper limit current determiner 1524 determines the upper limit current value such that an overvoltage of the battery according to the lithium ion concentration gradient falls within a predetermined range.

Abstract: The present solution provides calibration for a battery model of an electric vehicle battery. One or more processors of an electric vehicle coupled with memory can identify, for the electric vehicle, a model configured to determine performance of a battery of the electric vehicle based on a function. The function can generate values for a parameter of the model across a range of states of charges and a range of temperatures. The one or more processors can generate, based on input from a sensor of the electric vehicle, a value of performance of the electric vehicle via the model. The one or more processors can provide an action for the electric vehicle based on the value of the performance.

Abstract: Remaining charge acquisition means of a battery installation system acquires remaining charge information on a remaining charge of each of a plurality of batteries which are installable in an unmanned aerial vehicle. Battery weight acquisition means acquires battery weight information on a weight of each battery. Location acquisition means acquires location information on a movement destination of the unmanned aerial vehicle. Selection means selects, based on the remaining charge information, the battery weight information, and the location information, from among the plurality of batteries, a battery having a remaining charge equal to or more than a battery consumption amount for moving to the movement destination. Processing execution means executes processing for installing the battery selected by the selection means in the unmanned aerial vehicle.

Abstract: A method of constructing a chart of correlations between a rapid discharge and a slow discharge in order to measure the wear of at least one electrochemical cell, including a measurement phase that includes a training sequence followed by a characterization sequence, and an aging phase. Each of the sequences includes charging-relaxing-discharging-relaxing under controlled conditions and is repeated with different conditions. The time of each discharge is measured. The aging phase includes an alternation of charges and discharges with no intermediate relaxation and is implemented before each repetition of the measurement phase, such that a real capacity is obtained for a plurality of pairs of imposed parameters.

Abstract: A battery state estimation apparatus calculates a measured DC resistance value of a DC resistance based on a current change amount and a voltage change amount, which are calculated in a predetermined period using measured current value and voltage value. The battery state estimation apparatus further calculates (i) a non-temperature dependent constant and (ii) a constant of a temperature dependent function based on (i) an estimated DC resistance value and (ii) the measured DC resistance value. The estimated DC resistance value is an estimated value of the measured DC resistance value; the estimated DC resistance value is represented as a sum of (i) the non-temperature dependent constant Ra, which indicates a temperature independent component of the DC resistance of the secondary battery, and (ii) the temperature dependent function Rb, which indicates a temperature dependent component of the DC resistance of the secondary battery.

Abstract: A battery resistance diagnosis device includes a current supply unit configured to supply a preset fixed current to a battery cell, a voltage measurement unit configured to measure an open circuit voltage of the battery cell while the fixed current is supplied, an external resistance calculation unit configured to calculate an external resistance value of the battery based on the fixed current and the open circuit voltage of the battery cell, and an abnormality diagnosis unit configured to diagnose a battery abnormality due to a voltage drop by comparing the calculated external resistance value with a preset external resistance value.

Abstract: A diagnostic device (100) includes: an acquisition unit (101) that acquires first charging information including a first detected value detected by an external charger (200) during charging of a battery mounted in a vehicle (10) and second charging information including a second detected value detected by the vehicle; and a deterioration estimation unit (105) that estimates a deterioration degree that indicates a degree of deterioration of the battery on the basis of the first charging information and the second charging information.

Abstract: An information handling system may include at least one processor, a physical storage resource, and a non-volatile memory other than the physical storage resource. The at least one processor may be configured to execute instructions for: storing learned profile data at the physical storage resource; in response to detection of a catastrophic event, copying the learned profile data from the physical storage resource to the non-volatile memory; and subsequent to a remediation event for the catastrophic event, restoring the learned profile data from the non-volatile memory.

Abstract: A secondary battery state estimation device includes: a state measurer configured to measure state variables including a terminal current and a terminal voltage of a secondary battery; an internal resistance calculator configured to calculate internal resistance of the secondary battery; an estimated open-circuit-voltage (OCV) calculator configured to calculate an estimated OCV; an estimated state-of-charge (SOC) calculator configured to calculate an estimated SOC, by using an SOC-OCV characteristic model; a differential estimated SOC calculator configured to calculate a differential estimated SOC; an integrated terminal current calculator configured to calculate an integrated terminal current; and a state-of-health (SOH) calculator configured to calculate an SOH. The SOH that the SOH calculator has calculated in a high SOC state where at least the estimated OCV is equal to or above a first threshold value is entered into an SOH estimation model used to estimate the SOH to update the SOH estimation model.

Abstract: A method for operating a system including a battery-operated machine having a battery, the method includes continuously providing operating variables of the battery, ascertaining operating features for a current evaluation period depending on characteristics of the provided operating variables, the operating features characterizing a use of the battery in the current evaluation period, ascertaining at least one stress-maximizing operating feature of the ascertained operating features that is associated with a stress factor for the battery using a state of health model, the stress factor having a greatest influence on aging of the battery, and signaling a measure in the battery-operated machine depending on the stress factor.

Abstract: A battery management apparatus according to an embodiment of the present disclosure includes a voltage measurer for measuring a voltage of a battery module and output a measured voltage value; a current measurer for measuring a charging current of the battery module and output a measured current value; and a controller for receiving the measured voltage value and the measured current value, estimating a state of charge (SOC) of the battery module based on the measured voltage value and the measured current value, calculating an accumulated change rate by adding up a change rate of the estimated SOC per unit time, and detecting whether the battery module has a defect by comparing the calculated accumulated change rate with a reference change rate.

Abstract: An apparatus for detecting a defect of a battery pack may disconnect a battery cell at which a defect is detected inside a battery pack to remove a risk factor that may occur from the corresponding battery cell. Risk factors that may cause explosions can be eliminated by discharging the battery cell at which a defect is detected. In addition, the recurrence of the risk factor can be prevented in advance by disconnecting the battery cell at which the defect is detected from the battery pack.

Abstract: A battery state notification apparatus for an electric vehicle includes a collision detector, an electric leakage detector, a surrounding condition detector, a vehicle exterior sounding device, and a battery state notification device. The collision detector detects a collision of the electric vehicle. The electric leakage detector detects a state of the electric leakage from the drive battery. The surrounding condition detector detects a surrounding condition including the presence of a person around the electric vehicle. The vehicle exterior sounding device outputs a sound to the outside of the electric vehicle. The battery state notification device causes the vehicle exterior sounding device to make notification about the state of electric leakage from the drive battery in a case where the collision detector detects the collision of the electric vehicle and where the surrounding condition detector detects the presence of the person around the electric vehicle.

Abstract: An apparatus for calculating battery power including a time setting unit that sets a target time for using a battery cell, a temperature sensor unit that measures temperature of the battery cell, a resistance calculation unit that calculates resistance of the battery cell, and a power calculation unit that calculates an optimum current value usable without exceeding threshold temperature of the battery cell during the target time, based on the temperature and resistance of the battery.

Abstract: A battery diagnostic device includes an acquisition unit that acquires a temperature and an internal resistance of a battery; a determination unit that determines a diagnostic temperature that is a temperature used for a diagnosis of the battery, based on the temperature acquired by the acquisition unit; an estimation unit that estimates the internal resistance of the battery at the diagnostic temperature based on the temperature and the internal resistance acquired by the acquisition unit and the diagnostic temperature determined by the determination unit; and a diagnosis unit that diagnoses the battery based on the internal resistance estimated by the estimation unit.

Abstract: A battery management apparatus for providing more specific information about degradation of a battery cell and changing a control condition according to a degradation pattern of the battery cell. Since not only the degradation degree of the battery cell but also the degradation pattern of the battery cell is estimated, the present state of the battery cell may be more accurately estimated.

Abstract: A computing system can facilitate cooperation between a utility and a fleet of vehicles. The system can receive a charging requirement from a vehicle. The charging requirement can be based on an available power output capacity of a battery pack of the vehicle. The system can receive solar ramp data from a utility. The solar ramp data can be based on an anticipated power output of a solar energy source. The system can determine a charge plan based on the charging requirement and the solar ramp data and specify a timing of charging or discharging the vehicle. The system can transmit the charge plan to the vehicle. The system can receive load data from the vehicle based on supply or consumption of power by the vehicle and the charge plan.

Abstract: A method for brand identification of an electric vehicle to a charging station includes connecting a plug of the charging station to a socket of the electric vehicle, receiving a control pilot signal at the socket from the charging station, terminating the control pilot signal in a variable resistance in the electric vehicle, and toggling the variable resistance in a vehicle pattern that transitions between two charging state resistances. The charging station detects the vehicle pattern and maps the vehicle pattern to a vehicle brand of the electric vehicle. The method includes receiving electrical current to recharge the electric vehicle at the socket.

Abstract: A method of controlling a fuel battery system of the present disclosure is a method of controlling a fuel battery system, including a measurement process in which a power generation voltage at a predetermined current density of a fuel battery cell is measured, a first calculation process in which a poisoning rate of an electrode catalyst at the power generation voltage measured in the measurement process is calculated from a predetermined relationship between the power generation voltage at the predetermined current density and the poisoning rate of the electrode catalyst of the fuel battery cell, and a second calculation process in which a generation rate of hydrogen peroxide at the poisoning rate of the electrode catalyst calculated in the first calculation process is calculated from a predetermined relationship between the poisoning rate of the electrode catalyst and the generation rate of hydrogen peroxide of the fuel battery cell.

Abstract: In a method of estimating an internal degradation state of a degraded cell, a measurement system calculates a target capacity characteristic curve by differentiating current capacity by voltage on a target charge curve of a target battery. Further, the method obtains changes of parameters of different types based on a fitting operation that fits the curve and a reference capacity characteristic curve calculated from reference data. In the fitting operation, whichever of low current capacity regions and high current capacity regions of the curve and the curve have a stronger correlation are fit first and whichever of them have a weaker correlation are fit later.

Abstract: A battery diagnosis apparatus according to the present disclosure includes a voltage measurer for measuring a cell voltage of each of first to nth battery cells and a processor, wherein n is a natural number of 2 or greater. The processor determines an average cell voltage of each battery cell for a first rest period from a first time point to a second time point, based on the cell voltage of each battery cell measured a first number of times for the first rest period, determines an average cell voltage of each battery cell for a second rest period and diagnoses a fault of each battery cell based on the average cell voltage of each battery cell for the first rest period and the average cell voltage of each battery cell for the second rest period.

Abstract: According to an aspect, a battery system for controlling a charging current includes a temperature sensor configured to measure a temperature of a first battery, a state-of-charge (SoC) calculation engine configured to calculate an SoC value of the first battery, and a charge current controller configured to determine an adjusted current according to a charge profile based on the temperature and the SoC value, where the charge current controller is configured to transmit current data that indicates the adjusted current to a device.

Abstract: Disclosed is an estimation method for the safety state of a battery pack based on deep learning and consistency detection, including: acquiring battery parameters of each single battery in the battery pack in a charging process to be identified; calculating multiple groups of feature data according to the battery parameters; constituting a first matrix by the multiple groups of feature data, and calculating a covariance matrix of the first matrix; inputting the covariance matrix into a first trained fully connected layer, so as to extract principal components of the first matrix and obtain a second matrix; multiplying the first matrix and the second matrix to obtain a third matrix; and inputting the third matrix into a series-connected and trained multi-head self-attention layer and classification layer, to identify whether single battery consistency safety hazards exist in the charging process. This embodiment improves the accuracy of identification.

Abstract: A battery cell error determining apparatus including: a magnetic field measurement unit configured to measure a magnetic field generated by a current flowing in a battery cell, and a control unit configured to calculate a capacity of the battery cell by using a current calculated by the magnetic field measured by the magnetic field measurement unit. The control unit determines an error of the battery cell by using the capacity of the battery cell.

Abstract: A method for predicting a life includes the following. Obtain multiple cycle numbers of a battery and multiple capacity data corresponding to the cycle numbers. Obtain multiple sets of first fitting data by fitting the cycle numbers and the capacity data with a bi-exponential empirical model. Obtain multiple sets of second fitting data by fitting the cycle numbers and the capacity data with a box-cox transformation method. Determine a first capacity error according to the multiple sets of first fitting data and the multiple capacity data. Determine a second capacity error according to the multiple sets of second fitting data and the capacity data. Generate a battery-life prediction model according to the first capacity error, the second capacity error, the multiple sets of first fitting data, and the multiple sets of second fitting data. Determine an RUL of the battery according to a predetermined battery-capacity-value and the battery-life prediction model.

Abstract: A battery pack in accordance with an embodiment may include a battery management system (BMS) controlling the battery pack, the BMS includes an internal resistance value calculation module calculating an internal resistance value for each battery cell directly after the battery pack is charged or discharged for a predetermined time, a maximum internal resistance valued battery cell detection module detecting a battery cell having a biggest internal resistance value of the calculated internal resistance values, and a defective battery cell determination module determining a defective battery cell on the basis of a detected number of time each battery cell has the biggest internal resistance value.

Abstract: In one or more embodiments, one or more systems, one or more methods, and/or one or more processes may determine a historical discharge rate (dh) from multiple discharge rates a battery of an information handling system (IHS) while the IHS operates on electrical power provided by the battery; receive a current discharge rate (dc) of the battery; determine a full charge capacity correction factor value (Cfcc) associated with the battery; determine a weighting factor (?); determine a difference between a full charge capacity value (FCC) and Cfcc; determine ?·dh; determine (1??)·dc; determine a sum of dh·? and dc·?; determine a quotient value of FCC?Cfcc and ?·dh+(1??)·dc; scale the quotient value based at least on a relative state of charge of the battery to determine an estimated time remaining for the IHS to operate on the electrical power provided by the battery; and display the estimated time remaining.

Abstract: An apparatus for monitoring health of one or more cells in a battery includes a health monitoring system configured to measure voltage on one or more cells when a waveform is injected into the one or more cells. The waveform is measured at an end of a pulse for each current.

Abstract: Energy storage cell qualification and related systems, methods, and devices are disclosed. A method of qualifying rechargeable battery cells includes taking measurements on the rechargeable battery cells, determining specific capacity distributions of the rechargeable battery cells as a function of a number of discharge cycles based on the measurements, determining one or more specific capacity thresholds to separate the specific capacity distributions of the rechargeable battery cells into two or more classifications, and qualifying the rechargeable battery cells into the two or more classifications based, at least in part, on the specific capacity distributions and the one or more specific capacity thresholds. A method of implementing rechargeable battery cells into product manufacturing and qualifying the rechargeable battery cells, and deploying those of the rechargeable battery cells qualified into a first classification of the two or more classifications into the product.

Abstract: In order to estimate states of health of batteries storing electrical energy significantly indicated by battery capacity and battery internal resistance, by which the estimation of states of health of batteries, deteriorated over time usage, is automated and carried out without a need of any specific test such as a capacity test and the usage of data out of normal operation, it is proposed to collect data from normal operation of a battery storing electrical energy relating to battery-internal physical properties such as a terminal direct current IDC, a terminal direct voltage UDV and a battery cell temperature T due to battery measurements and the determination or estimation, based on this data and a battery model, of a model parameter by solving an optimization-/model parameter estimation-problem and minimizing a difference between the battery model and the battery measurements.

Abstract: A determination apparatus (10) includes: a criteria value acquisition unit (11) that acquires a criteria value which is a performance value of a storage battery at a criteria time; a target value acquisition unit (12) that acquires a target value which is the performance value of the storage battery at a determination time; a usage method data acquisition unit (13) that acquires usage method data indicating a usage method of the storage battery from the criteria time to the determination time; a predicted range computing unit (14) that computes a predicted range of the performance value at the determination time on the basis of the criteria value, the usage method data, and a time elapsed from the criteria time to the determination time; and a determination unit (15) that determines that the storage battery is not to be compensated if the target value is within the predicted.

Abstract: A method for operating a central processing unit which is communicatively connected to a plurality of devices having electrical energy stores, includes determining a data-based state of health model which is trained to assign a state of health to an operating feature point which characterizes operation of a corresponding electrical energy store of the electrical energy stores of the plurality of devices and results from a plurality of operating features, determining operating feature points for the electrical energy stores of the plurality of devices, and selecting at least one of the operating feature points based on state uncertainties of the states of health of all operating feature points of the corresponding electrical energy store, such that the at least one operating feature point has a highest relevance for improving the state uncertainties of the operating feature points determined.

Abstract: In some embodiments, a battery management system is provided. The battery management system comprises a connector for electrically coupling a battery to the battery management system, at least one sensor configured to detect a battery state, a programmable chip configured to control at least one of charging and discharging of the battery, and a controller device. The controller device is configured to receive at least one battery state from the at least one sensor; provide the at least one battery state as input to a tanks-in-series model that represents the battery; and provide at least one output of the tanks-in-series model to the programmable chip for controlling at least one of charging and discharging of the battery.

Abstract: Software-configurable battery monitoring and management systems and methods provide flexibility in selecting the location where the highest voltage in a block of cells is sensed so as to support control boards to connect to any number of cells. In certain embodiments, battery management is accomplished by measuring cell voltages in a block of cells in a battery stack, determining whether the battery stack comprises a bus bar, determining a sum of the individual cell voltages, and comparing the voltage at the top of a battery stack, including any bus bar, to the sum of the individual cell voltages to obtain a comparison result that may be used to perform a diagnostic procedure.

Abstract: A charging apparatus for a vehicle where a terminal (1, FIG. 2) is connected to at least one kerbside power/data unit (9) to provide a power (4) and a data connection (5) to the power/data unit (9), the power/data unit (9) being connected to a nearby vehicle (17) to provide power to charge the vehicle (17) and receive data from the vehicle (17). The fact that the kerbside power/data unit (9) can charge a vehicle (17) using power supplied from a terminal (1, FIG. 2) and can transmit data from the vehicle (17) to the terminal (1, FIG. 2) provides the power and data requirements for connected autonomous vehicles at a kerbside location.

Abstract: A prediction method of battery health includes: obtaining an environment temperature, and a discharge capacity and an operating parameter of a battery; determining an estimated operating parameter in a preset temperature at the discharge capacity according to the environment temperature, the discharge capacity and the operating parameter; determining an estimated capacity of the battery according to the estimated operating parameter; and determining a health level of the battery according to the estimated capacity of the battery and a reference capacity, at the discharge capacity of the battery.