Method and apparatus for determining the state of health and state of charge of lithium sulfur batteries

Abstract

Systems and methods for accurately determining the state of health (including state of charge and relative age) of a Lithium Sulfur battery, module or cell. The invention uses an operational model of a Lithium Sulfur cell or battery to predict model parameters under a range of conditions related to state of charge and state of health. Operational models include the memory effect due to the unique chemistry of a Lithium Sulfur cell that precludes the user of other methodologies for State of health determination for Lithium Sulfur batteries. Model parameters are identified in real life applications and parameters are compared to those of the operational Lithium Sulfur model employing Kalman filtering. The output includes an estimate of state of health and other key performance indicators. Key performance indicators are compared with measured values of for example resistance to provide feedback to the estimate process in order to improve accuracy. The system can be implemented as software or firmware in an application.

1 - 36 . (canceled) 
     
     
         37 . A method for generating a model of a secondary electrochemical cell in which capacity can be lost due to active reactant species becoming inactive in use, the model being operable to predict the electrical characteristics of the cell in use based on a model representative of the internal state of the cell that correlates a terminal voltage of the cell to an operational condition of the cell for all states of charge, SOC, wherein the model representative of the internal state of the cell is an equivalent circuit network model comprising a number of modelled electrical elements, the equivalent circuit network model being parameterised by the properties of the constituent electrical elements of the equivalent circuit network model, the method comprising:
 generating data representative of the behaviour of the cell in use across the range of operational conditions of the cell for all states of charge, SOC;   identifying, based on the generated data representative of the behaviour of the cell in use, the parameters of the equivalent circuit model as a function of the State of Charge that cause the equivalent circuit to have electrical characteristics that produce a behaviour of the equivalent circuit model that correspond to the generated data representative of the behaviour of the cell in use.   
     
     
         38 . A method as claimed in  claim 37 , wherein the electrochemical cell has a Lithium Sulfur chemistry. 
     
     
         39 . A method as claimed in  claim 37 , wherein the equivalent circuit network model consists of a voltage source in series with an ohmic resistance and one or more diffuse resistances represented as RC pairs, wherein the voltage of the voltage source, and the resistances and capacitances of the ohmic resistance and RC pairs parameterise the equivalent circuit model. 
     
     
         40 . A method as claimed in  claim 37 , wherein the operational condition of the cell includes one or more of: a terminal voltage of the cell; a deemed open circuit voltage of the cell; a current load on the cell; a temperature of the cell; an internal resistance of the cell. 
     
     
         41 . A method as claimed in  claim 37 , wherein generating data representative of the behaviour of the cell in use across the range of operational conditions of the cell for all states of charge, SOC, includes predicting a terminal voltage behaviour of the cell at different states of charge of the cell for different operating conditions using a high fidelity physical model of the cell. 
     
     
         42 . A method as claimed in  claim 37 , wherein generating data representative of the behaviour of the cell in use across the range of operational conditions of the cell for all states of charge, SOC, includes; controlled testing the behaviour of standard cells of the design of the modelled cell under a range of different working conditions including:
 receiving measurements of the cell's terminal voltage at different charge/discharge rates and temperatures and states of charge; and   optionally receiving measurements of the cell's internal resistance at different charge/discharge rates and temperatures and states of charge.   
     
     
         43 . A method as claimed in  claim 42 , wherein controlled testing the behaviour of standard cells of the design of the modelled cell under a range of different working conditions includes applying current pulses to the cell at set discharge rates and leaving a relaxation time between the said pulses sufficient to allow the cell's terminal voltage to revert to an open circuit voltage. 
     
     
         44 . A method as claimed in  claim 43 , wherein controlled testing the behaviour of standard cells of the design of the modelled cell further includes starting from a deemed full state of charge of the test cell and proceeding to apply the current discharge pulses until the cell's terminal voltage drops below a pre-determined level used to calibrate a full state of discharge for the test cell. 
     
     
         45 . A method as claimed in  claim 43 , further comprising:
 taking the cell's terminal voltage at the end of the relaxation phase between each pulse to be the open circuit voltage of the cell at that state of charge.   
     
     
         46 . A method as claimed in  claim 45 , wherein identifying the parameters of the equivalent circuit model as a function of the State of Charge includes using the cell's open circuit voltage at that state of charge to identify the parameter value for the voltage source of the equivalent circuit network model at that state of charge. 
     
     
         47 . A method as claimed in  claim 43 , wherein identifying the parameters of the equivalent circuit model as a function of the State of Charge includes using the instantaneous drop in the cell's terminal voltage at the start of a current pulse to identify the parameter value for the ohmic resistance component of the equivalent circuit network model at that state of charge. 
     
     
         48 . A method as claimed in  claim 43 , wherein identifying the parameters of the equivalent circuit model as a function of the State of Charge comprises includes using the gradual drop in cell's terminal voltage continuing from the instantaneous voltage drop to identify parameter values of the resistances and capacitances of the RC pairs for that state of charge contributing to the diffusion resistance component of the equivalent circuit network model. 
     
     
         49 . A method as claimed in  claim 37 , further comprising using a prediction error minimisation technique to refine the parameter values of the cell model representative of the internal state of the cell in use identified based on the generated data representative of the behaviour of the cell in use. 
     
     
         50 . A method as claimed in  claim 37 , further comprising storing in a parameter value resource the identified parameter values for the equivalent circuit network model for modelling the behaviour of the cell at all States of Charge across the range of operational conditions of the cell, wherein the parameter value resource is optionally a lookup table. 
     
     
         51 . A method as claimed in  claim 37 , further comprising fitting the identified parameter values for the cell model to functions dependent on the state of charge. 
     
     
         52 . A method as claimed in  claim 51 , wherein the parameter values are stored in a parameter value resource as a function of state of charge. 
     
     
         53 . A method of generating a memory model of a secondary electrochemical cell having a Lithium Sulfur chemistry in which capacity can be lost due to active reactant species becoming temporarily inactive in use, the memory model being operable to track, in use, an amount of active reactant in the cell and/or an amount of temporarily inactive reactant in the cell and optionally an amount of permanently inactive reactant in the cell, the method comprising:
 establishing a set of rules relating the different manifestations of the reactant species of the Lithium Sulfur cell chemistry, the amounts of the reactant species in those different manifestations, the reactions in which those different manifestations of reactant species participate during charge and discharge, and the reaction rates thereof;   parameterising the modelled reaction rates by one or more of: the operating conditions of the cell; the modelled amounts of the different manifestations of reactant species; the internal state of the cell; the electrical characteristics of the cell in use; and   identifying the parameterised values for the modelled reaction rates by: theoretical predictions for the cell based on a high fidelity physical model; or fitting or deriving the parameter values empirically or semi-empirically based on tests of standard cells.   
     
     
         54 . A method as claimed in  claim 53 , wherein the memory model representative of the variation in the amount of active reactant species in the cell is a simplified physical model that groups the reactant species of the cell into three groups representing high order manifestations, medium order manifestations and low order manifestations, and wherein the model divides the charge and discharge curves of the cell into a high plateau and low plateau and assumes that reactions between the high-to-medium order manifestations dominate the high plateau and reactions between the medium-to-low order manifestations dominate the low plateau. 
     
     
         55 . A method as claimed in  claim 54 , wherein the memory model assumes that, when the cell terminal voltage falls below a boundary level between the high and low plateaus, the reactions between the high-to-medium order manifestation do not occur, leading to a remaining amount of high order manifestations of reactant becoming deemed temporarily inactive and unable to contribute to the remaining capacity of the cell. 
     
     
         56 - 78 . (canceled)