System and method for estimating a state vector associated with a battery

• US 7,800,375 B2
• Filed: 06/29/2009
• Issued: 09/21/2010
• Est. Priority Date: 08/23/2005
• Status: Active Grant

• Current Assignee: LG Energy Solution Limited (LG Corporation)
• Original Assignee: LG Chem Limited (LG Corporation)
• Inventors: Plett, Gregory L.
• Primary Examiner(s): Tso; Edward
• Assistant Examiner(s): WILLIAMS, ARUN C
• Application Number:
  US12/493,787
• Publication Number:
  US 20090261837A1
• Time in Patent Office: 449 Days
• Field of Search: 324/426
• US Class Current: 324/426
• CPC Class Codes: G01R 31/367 Software therefor, e.g. for battery testing using modelling or look-up tables
• CPC Class Codes: G01R 31/3835 involving only voltage measurements
• CPC Class Codes: G01R 31/3842 combining voltage and current measurements

Abstract

A system and a method for estimating a state vector associated with a battery are provided. The method includes determining a time interval that the battery has been electrically decoupled from a load circuit. The time interval starts at a first time. The method further includes obtaining a first state vector associated with the battery from a memory. The first state vector is determined prior to the first time. The method further includes calculating a second predicted state vector associated with the battery based on the first state vector and the time interval.

Claims

1. A method for estimating a state vector associated with a battery, the method comprising:

determining a time interval that the battery has been electrically decoupled from a load circuit utilizing a computer, the time interval starting at a first time;

obtaining a first state vector associated with the battery from a memory device, the first state vector being determined prior to the first time;

calculating a second predicted state vector associated with the battery based on the first state vector and the time interval;

measuring a battery voltage output by the battery to obtain a first battery voltage value after the first time interval when the battery is electrically re-coupled to the load circuit;

estimating a second battery voltage value associated with the battery based on the second predicted state vector;

calculating a voltage error value based on the first battery voltage value and the second battery voltage value;

calculating a third estimated state vector associated with the battery based on the second predicted state vector and the voltage error value; and

storing the third estimated state vector in the memory device.

2. The method of claim 1, further comprising calculating a covariance value associated with the third estimated state vector.

3. The method of claim 1, wherein the step of calculating the second predicted state vector comprises calculating the second predicted state vector associated with the battery based on the first state vector and the time interval utilizing at least one of a Kalman filter, an extended Kalman filter, a sigma-point Kalman filter, a square-root sigma-point Kalman filter, and a particle filter.

4. The method of claim 1, wherein the step of calculating the third estimated state vector comprises calculating the third estimate state vector associated with the battery based on the second predicted state vector and the voltage error value interval utilizing at least one of a Kalman filter, an extended Kalman filter, a sigma-point Kalman filter, a square-root sigma-point Kalman filter, and a particle filter.

5. The method of claim 1, wherein the second predicted state vector is indicative of at least a predicted state-of-charge of the battery.

6. The method of claim 1, wherein the third predicted state vector is indicative of at least a predicted state-of-charge of the battery.