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

• US 8,035,345 B2
• Filed: 06/17/2008
• Issued: 10/11/2011
• Est. Priority Date: 02/09/2006
• 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): DIAO, M BAYE
• Application Number:
  US12/141,020
• Publication Number:
  US 20080249725A1
• Time in Patent Office: 1,211 Days
• Field of Search: 320/132, 324/427, 324/430, 702/63
• US Class Current: 320/132
• CPC Class Codes: G01R 31/367 Software therefor, e.g. for battery testing using modelling or look-up tables

Abstract

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.

Claims

1. A system for determining an estimated combined battery state-parameter vector indicative of both a state and a parameter of a battery at a first predetermined time, the system comprising:

a sensor configured to generate a first signal indicative of an output variable of the battery; and

a computer operably coupled to the sensor, the computer configured to determine a first plurality of estimated augmented combined battery state-parameter vectors that are indicative of both a state and a parameter of the battery, a battery input noise, a sensor noise associated with the sensor, an uncertainty of both the state and parameter of the battery, an uncertainty of the battery input noise, and an uncertainty of the sensor noise, at a second predetermined time prior to the first predetermined time, the computer further configured to determine a second plurality of predicted combined battery state-parameter vectors that are indicative of both the state and the parameter of the battery and an uncertainty of both the state and parameter of the battery at the first predetermined time based on the first plurality of estimated augmented combined battery state-parameter vectors, the computer further configured to determine a third plurality of predicted battery output vectors that are indicative of an at least one output variable of the battery and an uncertainty of the output variable at the first predetermined time based on the first plurality of estimated augmented combined battery state-parameter vectors and the second plurality of predicted combined battery state-parameter vectors, the computer further configured to determine a first battery output vector based on the first signal, the computer further configured to determine a first estimated combined battery state-parameter vector indicative of both the state and the parameter of the battery at the first predetermined time based on the second plurality of predicted combined battery state-parameter vectors, the third plurality of predicted battery output vectors, and the first battery output vector.

2. The system of claim 1, wherein the computer is further configured to retrieve an estimated combined battery state-parameter vector indicative of both the state and the parameter of the battery at the second predetermined time from a memory, the computer further configured to determine a first estimated augmented combined battery state-parameter vector indicative of both the state and the parameter of the battery, the battery input noise and the sensor noise at the second predetermined time, based on the estimated combined battery state-parameter vector, an expected combined battery state-parameter input noise vector, and an expected sensor noise vector, the computer further configured to retrieve an estimated combined battery state-parameter vector covariance matrix indicative of an uncertainty of both the state and parameter of the battery at the second predetermined time from the memory, the computer further configured to determine a first estimated augmented combined battery state-parameter vector covariance matrix indicative of an uncertainty of both the state and the parameter of the battery, the battery input noise, and the sensor noise, based on the estimated combined battery state-parameter vector covariance matrix, a covariance matrix indicative of an uncertainty of the battery input noise and a covariance matrix indicative of an uncertainty of the sensor noise, the computer further configured to determine the first plurality of estimated augmented combined battery state-parameter vectors based on the first estimated augmented combined battery state-parameter vector and the first estimated augmented combined battery state-parameter vector covariance matrix.

3. The system of claim 1, wherein the computer is further configured to determine a first predicted combined battery state-parameter vector indicative of both the state and the parameter of the battery at the first predetermined time based on the second plurality of predicted combined battery state-parameter vectors, the computer further configured to determine a first predicted battery output vector indicative of at least one output variable of the battery at the first predetermined time based on the third plurality of predicted output vectors, the computer further configured to determine a gain matrix based on the first predicted combined battery state-parameter vector, the first predicted battery output vector, the second plurality of predicted combined battery state-parameter vectors, and the third plurality of predicted battery output vectors, the computer further configured to calculate the first estimated combined battery state-parameter vector based on the first predicted combined battery state-parameter vector, the first predicted battery output vector, the gain matrix, and the first battery output vector.