5279 results about "State of charge" patented technology

A spinal cord stimulation (SCS) system includes multiple electrodes, multiple, independently programmable, stimulation channels within an implantable pulse generator (IPG) which channels can provide concurrent, but unique stimulation fields, permitting virtual electrodes to be realized. The SCS system includes a replenishable power source (e.g., rechargeable battery), that may be recharged using transcutaneous power transmissions between antenna coil pairs. An external charger unit, having its own rechargeable battery can be used to charge the IPG replenishable power source. A real-time clock can provide an auto-run schedule for daily stimulation. An included bi-directional telemetry link in the system informs the patient or clinician the status of the system, including the state of charge of the IPG battery. Other processing circuitry in the IPG allows electrode impedance measurements to be made. Further circuitry in the external battery charger can provide alignment detection for the coil pairs.

An expert system manages a power grid wherein charging stations are connected to the power grid, with electric vehicles connected to the charging stations, whereby the expert system selectively backfills power from connected electric vehicles to the power grid through a grid tie inverter (if present) within the charging stations. In more traditional usage, the expert system allows for electric vehicle charging, coupled with user preferences as to charge time, charge cost, and charging station capabilities, without exceeding the power grid capacity at any point. A robust yet accurate state of charge (SOC) calculation method is also presented, whereby initially an open circuit voltage (OCV) based on sampled battery voltages and currents is calculated, and then the SOC is obtained based on a mapping between a previously measured reference OCV (ROCV) and SOC. The OCV-SOC calculation method accommodates likely any battery type with any current profile.

A shared vehicle system includes a central facility, at least one vehicle distribution port facility and a plurality or fleet of vehicles, each having a vehicle subsystem. In general, the central station and port facility and the vehicle subsystems communicate in a manner to allow a user to enter information at a port facility. That information is then communicated to the central facility, where the information is processed to select a vehicle from the fleet to allocate to the user at the port facility. Selection of a vehicle for allocation to a user may be based on selecting an available or soon to be available vehicle according to various algorithms that take into account the vehicles state of charge. The central station also communicates with the port facility and the vehicle subsystem to notify the user of the selected vehicle, to provide secure user access to the selected vehicle, to monitor the location and operating status of vehicles in the fleet, to monitor the state of charge of electric vehicles and to provide other functions. The vehicles communicate with the central station to notify the central station of the PIN number of the individual attempting to use the vehicle, and of vehicle parameters such as state of charge and location of the vehicle.

The portable solar energy system stores electrical energy generated by a solar panel, which is made of an array of photovoltaic cells, in a dc storage battery, and upon demand converts the dc voltage of the battery to an ac output suitable for supplying conventional electrical appliances. The battery is a sealed lead-acid type and may be an Absorbed Glass Mat (AGM) battery. The system includes an energy storage and converting unit, which houses the battery and a dc-to-ac inverter. The inverter converts the stored energy of the battery, supplied at a low dc voltage, into the ac voltage and current required for supplying conventional appliances. A charge controller manages the flow of current from the solar panel to optimize the state of charge of the battery and to maximize the useful life of the battery. Additional circuitry monitors the discharge level of the battery to limit deep discharging.

A regulator voltage control includes measuring a current of a battery, determining a state of charge (SOC) of the battery based on the current, and determining a nominal optimum charging voltage as a function of the SOC of the battery. The nominal optimum charging voltage is converted to a % duty cycle, and a generator is operated relative to the % duty cycle for charging the battery. The nominal optimum charging voltage is reduced when either a battery charge current is below a predetermined value, or a current drawing accessory is turned on.

Methods and systems for energy management are disclosed. An example system includes a first port connected to an energy storage device for bidirectional flow of energy, a second port connected to an energy source device for unidirectional flow of energy, a third port connected to a utility grid for bidirectional flow of energy, and a unified control system with control logic configured to simultaneously control energy flow between the first, second, and third ports based on at least two factors from the group consisting of: a state of charge of the energy storage device, a state of the energy source device, and a state of the utility grid. Other embodiments are described and claimed.

A system is provided to instruct a plug-in hybrid electric vehicle how optimally to use electric propulsion from a rechargeable energy storage device to reach an electric recharging station, while maintaining as high a state of charge (SOC) as desired along the route prior to arriving at the recharging station at a minimum SOC. The system can include the step of calculating a straight-line distance and / or actual distance between an orientation point and the determined instant present location to determine when to initiate optimally a charge depleting phase. The system can limit extended driving on a deeply discharged rechargeable energy storage device and reduce the number of deep discharge cycles for the rechargeable energy storage device, thereby improving the effective lifetime of the rechargeable energy storage device. This “Just-in-Time strategy can be initiated automatically without operator input to accommodate the unsophisticated operator and without needing a navigation system / GPS input.

In one aspect of the present invention, a vehicle comprises: a consumable fuel powered engine, a battery and an electric motor powered by the battery. The battery is rechargeable both from an external electric power source (such as an electric power grid) and from the consumable fuel powered engine. A computer receives data as inputs and providing outputs, wherein the input data includes an expected state of the electric power source at a time when the vehicle is expected to be coupled to the electric power source. The outputs include control signals to control the state of charge of the battery during the time the vehicle is expected to be coupled to the electric power source.

A method of providing power to an electronic device in an energy-efficient manner includes transitioning between power states corresponding to charging and discharging a battery. The state of charge of the battery is detected. Upon detecting a high threshold state of charge, an external power source such as an AC-to-DC adapter is disabled, and the battery to provides primary power to the electronic device. Upon a low threshold state of charge, the AC-to-DC adapter is controlled to provide a high current output to charge the battery and provide primary power to the electronic device. The power states, when cycled over time based on the state of the battery, provide for an energy-efficient method of powering the electronic device.

A hybrid vehicular powertrain includes an electrical energy storage device. State-of-life for the electrical energy storage device is predictively determined based on electrical current, state-of-charge, and temperature of the electrical energy storage device during active and quiescent periods of operation.

An energy storage system determined to be at an operating point indicative of incipient threat to its condition is permitted to continue power flow for a duration that is a function of the state of charge before a diagnosis of a critical state of charge condition is rendered. If the state of charge returns to an acceptable region before the duration expires, no diagnosis of a critical state of charge condition is rendered. Generally, the duration increases as the state of charge trends toward the region of acceptable state of charge and decreases as the state of charge trends away from the region of acceptable state of charge.

A vehicle includes a charging unit receiving electric power from an external power source and externally charging a power storage unit. When a connector unit is coupled to the vehicle and a state ready for charging by the external power source is attained, a controller predicts degradation ratio of the power storage unit at the time point of completion of external charging based on degradation characteristic of the power storage unit in connection with SOC and battery temperature obtained in advance, and sets target state of charge of each power storage unit based on the battery temperatures so that the predicted degradation ratio does not exceed tolerable degradation ratio at the time point of completion of external charging. Then, the controller controls corresponding converters such that SOCs of power storage units attain the target states of charge.

Sate-of-life for an electrical energy storage device is predictively determined based on electrical current, state-of-charge, and temperature of the electrical energy storage device during active and quiescent periods of operation.

Systems and computer-implemented methods are used for analyzing battery information. The battery information may be acquired from both passive data acquisition and active data acquisition. Active data may be used for feature extraction and parameter identification responsive to the input data relative to an electrical equivalent circuit model to develop geometric-based parameters and optimization-based parameters. These parameters can be combined with a decision fusion algorithm to develop internal battery parameters. Analysis processes including particle filter analysis, neural network analysis, and auto regressive moving average analysis can be used to analyze the internal battery parameters and develop battery health metrics. Additional decision fusion algorithms can be used to combine the internal battery parameters and the battery health metrics to develop state-of-health estimations, state-of-charge estimations, remaining-useful-life predictions, and end-of-life predictions for the battery.

A battery cell converter (BCC) unit including one or more energy-storing battery cells coupled to one or more DC / DC converters is disclosed. A management unit can monitor and control the charging and discharging of each battery cells; including monitoring of voltages & State-of-Charge of each cell as well as controlling the switching of the DC / DC converters. The combined power and cell switching algorithms optimizes the charging and discharging process of the battery cells. A compound battery cell converter system comprising a series stack of BCCs to achieve high effective converter output voltage is also disclosed. The new proposed Battery Cell Converter architecture will enable improvements in battery pack usage efficiencies, will increase battery pack useable time per charge, will extend battery pack life-time and will lower battery pack manufacturing cost.

Systems and methods for health management of rechargeable batteries are disclosed. In one embodiment, a rechargeable battery system includes a rechargeable battery, and a battery health management unit operatively coupled to the rechargeable battery and including a state of health module configured to estimate a battery health by receiving battery-related data and predicting one or more failure modes. The state of health module may further include a prognostic failure mode component configured to combine at least one flight data variable with at least one model-based prognostic. In alternate embodiments, the battery health management unit may further include a state of life module and a state of charge module.

Methods and systems are provided for controlling a power transfer rate in to and / or out of a vehicle energy storage device to affect a current state of charge of the energy storage device. The vehicle may be on a mission comprising a plurality of future power transfer opportunities. In one example, the method comprises adjusting the power transfer rate based on an estimated duration of a future power transfer opportunity. Further, the method may include, if the estimated duration of the future power transfer opportunity is different from a predetermined threshold, changing the power transfer rate at the future power transfer opportunity. The method allows the operating life of the energy storage device to be extended.

Systems and methods for accurately determining the state of charge and the relative age of lithium sulfur batteries are provided. The cell resistance and taper input charge of a particular type of lithium sulfur battery are respectively measured to determine the state of charge and age of the battery.

A system and method for determining and balancing state of charge among plural series connected electrical energy storage units is provided. State of change of a selected storage unit in a string of storage units is determined by (i) applying a non-dissipative load to the selected storage unit, resulting in an energy transfer between the selected storage unit and the string of electrical energy storage units through the non-dissipative load and (ii) determining the state of charge of the selected unit from voltage and current data of the selected storage unit resulting from the energy transfer. When the state of charge of the selected unit is different than a target state of charge, energy can be transferred between the selected unit and the string of storage units, such that the state of charge of the selected unit converges toward the target state of charge.

The invention discloses a method for estimating battery health of an electric automobile, which relates to methods for estimating battery health according to voltage characteristics of a battery charging end. The method solves the defect that battery parameters, such as impedance, internal resistance and the like, need to be calculated while estimating battery health in the prior art. The method is used for estimating battery health. The method comprises the following steps of: emptying a new battery to be detected, and fully charging the new battery to be detected, and in the fully charging process, recording a voltage-time curve and a charge capacity-time curve of charging of the new battery to be detected; calculating actually usable capacity Qnew of the new battery to be detected; setting a threshold of V / dQ; calculating the charged capacity of the new battery to be detected from the time when the threshold of dV / dQ is realized to the time when the battery is fully charged during the charging process; building a relation curve of the open-circuit voltage and SOC (State Of Charge) of the new battery to be detected; estimating a SOCocv, then, calculating theoretically usable capacity Qtest-full of the attenuated battery; and obtaining the health of the battery to be detected according to the attenuated theoretically usable capacity QoId and the actually usable capacity Qnew of the battery.

The invention provides a combined estimation method for lithium ion battery state of charge, state of health and state of function. The combined estimation method comprises the steps that the state of he---alth of a battery is estimated online: open circuit voltage and internal resistance are identified online by adopting a recursive least square method with a forgetting factor, the state of charge is indirectly acquired according to a pre-established OCV-SOC corresponding relation, and then the size of battery capacity is estimated according to cumulative charge and discharge electric charge between two SOC points; the state of charge of the battery is estimated online: the state of charge of the battery is estimated by adopting the Kalman filter algorithm based on a two-order RC equivalent circuit model, and the battery capacity parameter in the Kalman filter algorithm is updated according to the estimation result of battery capacity; and the state of function of the battery is estimated online: the maximum chargeable and dischargeable current is calculated based on the voltage limit and the current limit of the battery according to internal resistance obtained by online identification, and then the maximum chargeable and dischargeable function can be obtained through further calculation.

The invention discloses an SOC (State of Charge) and SOH (State of Health) prediction method of an electric vehicle-mounted lithium iron phosphate battery, which comprises the following steps of: (a) improving a Thevenin cell equivalent model; (b) determining the state equation and the output equation of a system; (c) identifying battery model parameters; (d) using a Kalman filter algorithm to iterate the state variables of the system, so that the predictive value of SOC is closer to the actual value; and (e) using a dual-channel Kalman filter algorithm to carry out the online predication of an internal resistance and capacity of the lithium iron phosphate battery, and simultaneously predicating the SOH of the battery according to the changes in the internal resistance and the capacity value of the battery in the current state and the initial state. With the method, the predication precision of SOH of the battery is effectively improved, the decline in battery performance can be determined more accurately, and the internal resistance and capacity information of the battery is combined to provide a basis for making the battery management strategy and maintaining and replacing the battery.

A fuel cell system employing a floating base load hybrid strategy for reducing fast voltage transients of a FCPM. A power request signal is applied to an average power calculation processor that calculates the average power requested over a predetermined previous period of time. A weighting function processor provides a weighting function based on the state of charge of an EESS. The power available from the FCPM and the EESS is applied to a power comparison processor. The available power is compared to the power request to provide a difference value between what is currently being provided and what is desired. The difference value is compared to power limit values of the EESS. The output value of this comparison is added to a filtered value to generate a signal for the change in the output power of the fuel cell stack based on the power request.

A system and method for controlling a vehicle-based source of uninterruptable power is disclosed. The vehicle-based UPS includes an energy storage system located on-board a vehicle and configured to generate DC power transferable to an external load, and an DC-AC inverter connected to the on-board energy storage system to receive the DC power therefrom and invert the DC power to an AC power useable by the external load. The vehicle-based UPS also includes a charging device located on-board the vehicle and connected to the on-board energy storage system to provide recharging power thereto and a control system. The control system is configured to determine one of a state-of-charge (SOC) and a voltage of the energy storage system and selectively operate the charging device to provide the recharging power to the energy storage system to maintain the SOC or voltage of the energy storage system within a pre-determined range.

A control method for operating internal combustion engine electric hybrid vehicles with smaller battery packs, particularly in configurations where an electric motor (E / M) or electric motor / generator (E / MG), a battery, and associated controls are inserted between the engine and a continuously variable or automatic transmission. The interaction between the combustion engine and battery operated electric motor is controlled by taking energy into the batteries only if it is more efficient than throttling the engine and operating the engine at a lower efficiency. Additionally, the batteries are charged to a certain state or the batteries are maintained at a particular state of charge. A goal of the invention is to obtain the best possible fuel economy while maintaining good driveability.