# US 10,308,129 B2 · Real-time battery estimation > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,308,129 B2 - Document ID: US10308129B2 - Status: Granted - Kind: B2 - Application number: 15/170,301 - Filed: 2016-06-01 - Published: 2016-09-22 - Granted: 2019-06-04 - Earliest claimed: 2014-07-17 - Assignees: Ford Global Technologies, LLC - Applicants: Ford Global Technologies, LLC - Inventors: Tae-Kyung Lee - Web page: https://patentgrep.com/patent/US10308129B2 ## CPC - B60L 58/12: responding to state of charge [SoC] - B60K 6/28: characterised by the electric energy storing means, e.g. batteries or capacitors - B60K 6/40: characterised by the assembly or relative disposition of components - G01R 31/3648: {comprising digital calculation means, e.g. for performing an algorithm} - G01R 31/389: Measuring internal impedance, internal conductance or related variables - H01M 10/4257: {Smart batteries, e.g. electronic circuits inside the housing of the cells or batteries} - H01M 10/48: Accumulators combined with arrangements for measuring, testing or indicating the condition of cells, e.g. the level or density of the electrolyte (constructional details of current conducting connections for detecting conditions inside cells or batteries, e.g. details of voltage sensing terminals, H01M50/569) - B60L 2260/44: by parameter estimation - B60Y 2200/92: Hybrid vehicles - G01R 31/367: Software therefor, e.g. for battery testing using modelling or look-up tables - H01M 2010/4271: {Battery management systems including electronic circuits, e.g. control of current or voltage to keep battery in healthy state, cell balancing} - H01M 2220/20: Batteries in motive systems, e.g. vehicle, ship, plane - Y02E 60/10: Energy storage using batteries - Y02T 10/70: Energy storage systems for electromobility, e.g. batteries - Y10S 903/907: Electricity storage, e.g. battery, capacitor - B60L: PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES (arrangements or mounting of electrical propulsion units or of plural diverse prime-movers for mutual or common propulsion in vehicles B60K1/00, B60K6/20; arrangements or mounting of electrical gearing in vehicles B60K17/12, B60K17/14; preventing wheel slip by reducing power in rail vehicles B61C15/08; dynamo-electric machines H02K; control or regulation of electric motors H02P); SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES (electric coupling devices combined with mechanical couplings of vehicles B60D1/64; electric heating for vehicles B60H1/00); ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL (control or regulation of electric motors H02P); MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES - B60K: ARRANGEMENT OR MOUNTING OF PROPULSION UNITS OR OF TRANSMISSIONS IN VEHICLES; ARRANGEMENT OR MOUNTING OF PLURAL DIVERSE PRIME-MOVERS IN VEHICLES; AUXILIARY DRIVES FOR VEHICLES; INSTRUMENTATION OR DASHBOARDS FOR VEHICLES; ARRANGEMENTS IN CONNECTION WITH COOLING, AIR INTAKE, GAS EXHAUST OR FUEL SUPPLY OF PROPULSION UNITS IN VEHICLES - G01R: MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES (indicating correct tuning of resonant circuits H03J3/12) - H01M: PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY - B60Y: INDEXING SCHEME RELATING TO ASPECTS CROSS-CUTTING VEHICLE TECHNOLOGY - Y02E: REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION - Y02T: CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION - Y10S: TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS ## Abstract Vehicle systems and methods can include a traction battery and a controller to implement a state estimator configured to output battery state based on internal resistance of the traction battery and a system dynamics estimation of the traction battery using discrete battery measurements of voltage and internal resistance, and operate the traction battery according to output of the state estimator. For example, the controller can identify a system dynamics model of the traction battery using a battery input current profile and a battery output voltage profile measured within a predefined time period, transform the identified system dynamics model to a state-space model having a diagonal system matrix consisting of system Eigenvalues through the Eigendecomposition, estimate battery current limits and available power limits from the transformed system dynamics model, and operate the traction battery according to system dynamics model identified using estimated battery current limits and available power limits. ## Claims ### Claim 1 A vehicle comprising: a traction battery including a plurality of cells; and at least one controller programmed to implement a state estimator configured to output battery state based on internal resistance of the traction battery and a system dynamics estimation of the traction battery that uses discrete battery measurements of voltage and internal resistance, and operate the traction battery according to output of the state estimator. ### Claim 2 (depends on 1) The vehicle of claim 1, wherein the system dynamics estimation applies a subspace identification algorithm to approximate system matrices. ### Claim 3 (depends on 2) The vehicle of claim 2, wherein the controller uses the system matrices to derive expressions to estimate current limits from system matrices transformed using Eigendecomposition from the approximated system matrices from the subspace identification algorithm. ### Claim 4 (depends on 2) The vehicle of claim 2, wherein the controller outputs a battery current limit using estimated battery state variables and computed internal resistance. ### Claim 5 (depends on 1) The vehicle of claim 1, wherein the internal resistance is estimated using battery current input during a time period and a computed voltage that is estimated from battery terminal voltage during the time period. ### Claim 6 (depends on 1) The vehicle of claim 1, wherein the time period is 100 microseconds. ### Claim 7 (depends on 1) The vehicle of claim 1 wherein the controller is further programmed to: estimate the internal resistance during a time period; compute projections using a subspace identification algorithm; decompose singular values of the computed projections; identify a discrete state space model from the singular values; convert the discrete state space model to a continuous state space model; perform Eigendecomposition of a system matrix of the continuous state space model to a Eigendecomposed matrix; transform a battery model with the Eigendecomposed matrix to produce transformed matrices; and compute battery current limits based on the transformed matrices. ### Claim 8 A vehicle comprising: a traction battery including a plurality of cells; and at least one controller programmed to implement a state estimator, which is based on an Eigendecomposed system dynamics model of the traction battery, configured to output battery state based on internal resistance of the traction battery and a system dynamics estimation of the traction battery that uses discrete battery measurements of voltage and internal resistance for the plurality of cells, and operate the traction battery according to output of the state estimator. ### Claim 9 (depends on 8) The vehicle of claim 8, wherein the system dynamics model comprises a system dynamics matrix, an input matrix and an output matrix. ### Claim 10 (depends on 9) The vehicle of claim 9, wherein the system dynamics model is updated in real time. ### Claim 11 (depends on 8) The vehicle of claim 8, wherein the system dynamics model is identified using a subspace identification algorithm. ### Claim 12 (depends on 11) The vehicle of claim 11, wherein the subspace identification algorithm uses a voltage profile manipulated by subtracting a voltage drop across a battery internal resistance from the battery output voltage profile. ### Claim 13 (depends on 12) The vehicle of claim 12, wherein a computed internal resistance is estimated using the battery input current profile during a time period and measured battery output voltage profile during the time period. ### Claim 14 A vehicle comprising: a traction battery including a plurality of cells; and at least one controller configured to implement a state estimator configured to output battery state based on internal resistance of the traction battery and a system dynamics estimation of the traction battery that uses discrete battery measurements of voltage and internal resistance of a group of the plurality of cells, and operate the traction battery according to output of the state estimator. ### Claim 15 (depends on 14) The vehicle of claim 14, wherein the at least one controller is configured to estimate battery current and available power limits from a state-space model derived by Eigendecomposing a system dynamics model of the traction battery having a diagonal system matrix of system Eigenvalues and identified via a battery input current profile and a battery output voltage profile measured within a predefined time period. ### Claim 16 (depends on 15) The vehicle of claim 15, wherein the at least one controller is configured to identify the system dynamics model includes using a voltage profile manipulated by subtracting a voltage drop across a battery internal resistance from the battery output voltage profile. ### Claim 17 (depends on 16) The vehicle of claim 16, wherein the at least one controller is configured to identify the system dynamics model includes estimating the internal resistance using the battery current input profile during a time period and measured terminal voltage profile during the time period. ### Claim 18 (depends on 15) The vehicle of claim 15, wherein the at least one controller is configured to identify the system dynamics model includes identifying the system dynamics model in real time. ### Claim 19 (depends on 14) The vehicle of claim 14, wherein the system dynamics estimation applies a subspace identification algorithm to approximate system matrices; and wherein the at least one controller is configured to use the system matrices to derive expressions to estimate current limits from system matrices transformed using Eigendecomposition from the approximated system matrices from the subspace identification algorithm. ### Claim 20 (depends on 18) The vehicle of claim 18, wherein the at least one controller is configured to output a battery current limit using estimated battery state variables and computed internal resistance.