Lg Chem, Ltd

Utah State University

University of Colorado

Other

Ford Global Technolgoies, LLC

Alliance for Sustainable Energy, LLC

Compact Power Inc.

American Electric Vehicles, Inc.

American Electric Vehicles, Ind.

Gregory L Plett

Dragan Maksimovic

Regan Andrew Zane

Michael Scott Trimboli

Richard Dyche Anderson

Daniel Jes Costinett

Kandler Alan Smith

Michael Evzelman

Khurram K Afridi

A heterogeneous energy storage device and a method for controlling a heterogeneous energy storage device are provided. In one implementation, a heterogeneous energy storage device is provided. The heterogeneous energy storage device includes a first energy storage device, a second energy storage device and a capacitive device. The first energy storage device has a first energy capacity and a first power to energy ratio (P/E). The second energy storage device has a second total energy capacity and a second P/E ratio different from the first P/E ratio. The capacitive device is coupled in series with the first energy storage device, wherein the second energy storage device is coupled in parallel with the series combination of the capacitive device and the first energy storage device. In another implementation, a method of controlling a heterogeneous energy storage device including a first energy storage device and a second energy storage device is provided. In this implementation, the method includes: providing a capacitive device in series with the first energy storage; coupling the second energy storage device in parallel with the series combination of capacitive device and the first energy storage device, wherein the capacitive device provides DC decoupling between the first energy storage device and the second energy storage device.

Heterogeneous energy storage system and method of controlling a heterogeneous energy storage system

An apparatus for model predictive control ('MPC') is disclosed. A method and system also perform the functions of the apparatus. The apparatus includes a measurement module that receives battery status information from one or more sensors receiving information from a battery cell, and a Kalman filter module that uses a Kalman filter and the battery status information to provide a state estimate vector. The apparatus includes a battery model module that inputs the state estimate vector and battery status information into a battery model and calculates a battery model output, the battery model representing the battery cell, and an MPC optimization module that inputs one or more battery model outputs and an error signal in a model predictive control algorithm to calculate an optimal response. The optimal response includes a modification of the error signal.

Model predictive control and optimization for battery charging and discharging

An apparatus includes a battery state module that determines a battery state of each of a plurality of battery cells forming a battery unit. A battery state includes a health of the battery cell. A battery state of a battery cell differs from a battery state of other battery cells of the battery unit. Each battery cell is connected to a shared bus through a bypass converter that provides power from the battery cell to the shared bus. A charge/discharge modification module determines, based on battery state, an amount to vary a charging characteristic for each battery cell compared to a reference charging characteristic. Each charging characteristic varies as a function of a reference state. A charge/discharge module adjusts charging/discharging of a battery cell of the battery unit based on the charging characteristic of the battery cell.

Autonomous battery control and optimization

For battery control, an apparatus includes a shared bus and a plurality of isolated direct current (DC) to DC bypass converters. Each bypass converter is associated with one battery unit. Inputs of each bypass converter are in parallel electrical communication with the associated battery unit. Outputs of each bypass converter are in parallel electrical communication with the shared bus. Each bypass converter estimates a battery state for each battery unit and controls the battery state to a reference state.

Battery control

A system and method for maximizing a battery pack total energy metric indicative of a total energy of a battery pack is provided. The method includes receiving battery cell charge capacity estimates for all cells in the battery pack, composing battery pack configurations comprising subsets of the totality of battery cells, evaluating a battery pack energy metric for every battery pack configuration that is composed, selecting the battery pack configuration that has the maximum battery pack energy metric, and storing values indicative of the selected battery pack configuration in a memory.

System and method for maximizing a battery pack total energy metric

A system, a method, and an article of manufacture for determining an estimated battery cell module state indicative of a state of a battery cell module of a battery pack are provided. The method includes measuring at least one of a battery cell module voltage, a battery cell module current, and a battery cell module temperature. The method further includes determining the estimated battery cell module state of the battery cell module at a predetermined time based on an estimated battery pack state and at least one of the battery cell module voltage, the battery cell module current, and the battery cell module temperature. The method further includes storing a vector corresponding to the estimated battery cell module state in a memory.

System, method, and article of manufacture for determining an estimated battery cell module state

A system and method for equalizing a battery pack during a battery pack charging process in accordance with an exemplary embodiment is provided. The method includes receiving total capacity estimates for all battery cells in the battery pack, and receiving state-of-charge estimates for all battery cells in the battery pack. The method further includes computing an equalization metric for all battery cells in the battery pack. The method further includes determining an equalization action for all battery cells in the battery pack, and initiating that equalization action. The method further includes executing a battery pack charging step.

System and method for equalizing a battery pack during a battery pack charging process

A system and a method for computing an estimated state of charge and an estimated cell resistance of an electrochemical cell are provided. The method includes predicting a first cell resistance value indicating a present resistance of the electrochemical cell utilizing a first nonlinear cell model. The method further includes predicting a first state of charge value indicating a present state of charge of the electrochemical cell utilizing a second nonlinear cell model. The method further includes measuring a voltage and, a current associated with the electrochemical cell to obtain a voltage value and a current value, respectively. The method further includes estimating a second state of charge value indicating the present state of charge of the electrochemical cell utilizing the second nonlinear cell model based on the first state of charge value, the first cell resistance value, the voltage value, and the current value. The method further includes estimating a second cell resistance value indicating the present resistance of the electrochemical cell utilizing the first nonlinear cell model based on the first cell resistance value, the first state of charge value, the voltage value, and the current value.

State and parameter estimation for an electrochemical cell

A system and method for determining an estimated battery cell total capacity indicative of a total capacity of a battery cell is provided. The method includes receiving a first battery cell state-of-charge estimate at a first time and receiving a second battery cell state-of-charge estimate at a second time subsequent to the first time, measuring an integrated battery cell current value indicative of the integrated battery cell current between the first time and the second time, updating at least one recursive parameter based on the first battery cell state-of-charge estimate, the second battery cell state-of-charge estimate, and the integrated battery cell current value, determining the estimated battery cell total capacity based on at least one recursive parameter, and storing a value corresponding to the estimated battery cell total capacity in a memory.

System and method for recursively estimating battery cell total capacity

A system, a method, and an article of manufacture for determining an estimated combined battery state-parameter vector are provided. The method determines the estimated combined battery state-parameter vector based on a plurality of predicted the combined battery state-parameter vectors, a plurality of predicted battery output vectors, and a battery output vector.

System, method, and article of manufacture for determining an estimated combined battery state-parameter vector

The present invention relates to a method and an apparatus for estimating discharge and charge power of battery applications, including battery packs used in Hybrid Electric Vehicles (HEV) and Electric Vehicles (EV). One charge/discharge power estimating method incorporates voltage, state-of-charge (SOC), power, and current design constraints and works for a user-specified prediction time horizon &#x394;t. At least two cell models are used in calculating maximum charge/discharge power based on voltage limits. The first is a simple cell model that uses a Taylor-series expansion to linearize the equation involved. The second is a more complex and accurate model that models cell dynamics in discrete-time state-space form. The cell model can incorporate a inputs such as temperature, resistance, capacity, etc. One advantage of using model-based approach is that the same model may be used in both Kalman-filtering to produce the SOC and the estimation of maximum charge/discharge current based on voltage limits.

Method for calculating power capability of battery packs using advanced cell model predictive techniques

A system, a method, and an article of manufacture for determining an estimated battery parameter vector indicative of a parameter of a battery are provided. The method determines a first estimated battery parameter vector indicative of a parameter of the battery at a first predetermined time based on a plurality of predicted battery parameter vectors, a plurality of predicted battery output vectors, and a first battery output vector.

System, method, and article of manufacture for determining an estimated battery parameter vector

A system, a method, and an article of manufacture for determining an estimated combined battery state-parameter vector are provided. The method determines the estimated combined battery state-parameter vector based on a plurality of predicted combined battery state-parameter vectors, a plurality of predicted battery output vectors, and a battery output vector.

A system, a method, and an article of manufacture for determining an estimated battery state vector indicative of a state of a battery are provided. The method determines a first estimated battery state vector indicative of the state of the battery at a first predetermined time based on a plurality of predicted battery state vectors, a plurality of predicted battery output vectors, and a first battery output vector.

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Colorado Springs, CO, United States of America

Gregory L Plett