Systems and methods for real-time parameter estimation of a rechargeable battery

Patent metadata

Field	Value
Publication number	US-10367235-B2
Application number	US-201615048691-A
Country	US
Kind code	B2
Filing date	Feb 19, 2016
Priority date	Feb 19, 2016
Publication date	Jul 30, 2019
Grant date	Jul 30, 2019

Abstract

A battery system includes a battery that couples to an electrical system. The battery system also includes a battery control module that electrically couples to the battery. The battery control module monitors at least one monitored parameter of the battery, and the battery control module recursively calculates at least one calculated parameter of the battery based on at least an equivalent circuit model, the at least one monitored parameter, and a Kalman filter.

First claim

The invention claimed is:

1. A battery system, comprising:
a battery configured to be coupled to an electrical system;
one or more sensors configured to measure battery parameters during operation of the battery; and
a control module communicatively coupled to the one or more sensors, wherein the control module is configured to:
determine a first Kalman filter based at least in part on an equivalent circuit model of the battery that describes relationship between the battery parameters and model parameters, wherein:
the model parameters comprise an open circuit voltage of the battery, a current path resistance of the battery, and a charge transfer resistance of the battery; and
the first Kalman is configured to implement the open circuit voltage of the battery as a time-varying parameter, the current path resistance of the battery as a first time invariant parameter, and the charge transfer resistance of the battery as a second time invariant parameter;

execute the first Kalman filter based on a first set of a plurality of battery parameter sets to determine a first estimated model parameter, wherein the first estimated model parameter comprises a first estimated open circuit voltage of the battery, a first estimated current path resistance of the battery, or a first estimated charge transfer resistance of the battery;
determine a first model parameter based at least in part on convergence of a plurality of estimated model parameters each determined based on a different set of the plurality of battery parameter sets; and
control charging, discharging, or both of the battery based at least in part on the first model parameter.

2. The battery system of claim 1 , wherein:
the control module is configured to execute the first Kalman filter based on a second set of the plurality of battery parameter sets to determine a second estimated model parameter; and
the second estimated model parameters comprises a second estimated open circuit voltage of the battery when the first estimated model parameter comprises the first estimated open circuit voltage, a second estimated current path resistance of the battery when the first estimated model parameter comprises the first estimated current path resistance, or a second estimated charge transfer resistance of the battery when the first estimated model parameter comprises the first estimated charge transfer resistance.

3. The battery system of claim 2 , wherein, to determine the first model parameter when the first set is a most recent set of the plurality of battery parameter sets, the control module is configured to:
determine a first estimated model parameter mean based at least in part on the first estimated model parameter determined based on the first set of the plurality of battery parameter sets and the second estimated model parameter determined based on the second set of the plurality of battery parameter sets;
determine a first estimated model parameter variance based at least in part on the first estimated model parameter and the second estimated model parameter;
determine a first ratio of the first estimated model parameter variance to the first estimated model parameter mean squared; and
set the first model parameter as the first estimated model parameter when the first ratio of the first estimated model parameter variance to the first estimated model parameter mean squared is less than a relative error tolerance value squared.

4. The battery system of claim 3 , wherein, to determine the first model parameter when the first set is the most recent set of the plurality of battery parameter sets, the control module is configured to:
determine a second estimated model parameter mean based at least in part on the second estimated model parameter determined based on the second set of the plurality of battery parameter sets before the first estimated model parameter mean is determined;
determine a second estimated model parameter variance based at least in part on the second estimated model parameter before the first estimated model parameter variance is determined;
determine a second ratio of the second estimated model parameter variance to the second estimated model parameter mean squared before the first ratio of the first estimated model parameter variance to the first estimated model parameter mean squared is determined; and
set the first model parameter as the first estimated model parameter when the second ratio of the second estimated model parameter variance to the second estimated model parameter mean squared is also less than the relative error tolerance value squared.

5. The battery system of claim 1 , wherein the control module is configured to:
execute the first Kalman filter based on the first set of the plurality of battery parameter sets to determine a second estimated model parameter, wherein the second estimated model parameter comprises the first estimated current path resistance of the battery and the first estimated model parameter comprises the first estimated charge transfer resistance of the battery; and
determine a second model parameter based at least in part on the convergence of the plurality of estimated model parameters, wherein the second model parameter comprises the current path resistance of the battery and the first model parameter comprises the charge transfer resistance of the battery.

6. The battery system of claim 5 , wherein the control module is configured to test convergence of the plurality of estimated model parameters by:
determining an estimated current path resistance mean and an estimated current path resistance variance based at least in part on the first estimated current path resistance and one or more previously determined estimated current path resistances of the battery;
determining a first ratio of the estimated current path resistance variance to the estimated current path resistance mean squared;
determining an estimated charge transfer resistance mean and an estimated charge transfer resistance variance based at least in part on the first estimated charge transfer resistance and one or more previously determined estimated charge transfer resistances of the battery
determining a second ratio of the estimated charge transfer resistance variance to the estimated charge transfer resistance mean squared; and
compare a larger of the first ratio and the second ratio to a relative error tolerance value squared.

7. The battery system of claim 6 , wherein:
the one or more sensors are configured to measure temperature of the battery during operation; and
the control module is configured to:
determine the second model parameter by setting the first estimated current path resistance as the current path resistance of the battery when the larger of the first ratio and the second ratio is less than the relative error tolerance value squared;
determine the first model parameter by setting the first estimated charge transfer resistance as the charge transfer resistance of the battery when the larger of the first ratio and the second ratio is less than the relative error tolerance value squared; and
store the current path resistance of the battery, the charge transfer resistance of the battery, and the temperature of the battery to facilitate monitoring ohmic growth of the battery.

8. The battery system of claim 1 , wherein the first Kalman filter comprises a process noise matrix configured to:
implement the open circuit voltage of the battery as the time-varying parameter;
implement the current path resistance of the battery as the first time invariant parameter; and
implement the charge transfer resistance of the battery as the second time invariant parameter.

9. The battery system of claim 8 , wherein the pr

Assignees

• Johnson Controls Tech Co
• Cps Tech Holdings Llc

Inventors

• Guo Qingzhi
• Kuper Christian
• Jin Zhihong H

Classifications

• H01M10/0525 Primary

  Rocking-chair batteries, i.e. batteries with lithium insertion or intercalation in both electrodes; Lithium-ion batteries · CPC title

• H01M10/48 Primary

  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) · CPC title

• G01R31/389

  Measuring internal impedance, internal conductance or related variables · CPC title

• H01M2220/20

  Batteries in motive systems, e.g. vehicle, ship, plane · CPC title

• G01R31/382

  Arrangements for monitoring battery or accumulator variables, e.g. SoC · CPC title