Real-time battery estimation

Patent metadata

Field	Value
Publication number	US-2016016482-A1
Application number	US-201414334346-A
Country	US
Kind code	A1
Filing date	Jul 17, 2014
Priority date	Jul 17, 2014
Publication date	Jan 21, 2016
Grant date	—

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.

First claim

What is claimed is:

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.

2 . The vehicle of claim 1 wherein the system dynamics estimation applies a subspace identification algorithm to approximate system matrices.

3 . 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.

4 . The vehicle of claim 2 wherein the controller outputs a battery current limit using estimated battery state variables and computed internal resistance.

5 . 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.

6 . 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.

7 . A vehicle comprising:
a traction battery including a plurality of cells; and at least one controller programmed to operate the traction battery according to 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.

8 . The vehicle of claim 7 wherein the system dynamics model comprises a system dynamics matrix, an input matrix and an output matrix.

9 . The vehicle of claim 8 wherein the system dynamics model is updated in real time.

10 . The vehicle of claim 7 wherein the system dynamics model is identified using a subspace identification algorithm.

11 . The vehicle of claim 10 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.

12 . The vehicle of claim 11 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.

13 . A method for vehicle control comprising:
identifying a system dynamics model of a traction battery using a battery input current profile and a battery output voltage profile measured within a time period; transforming the identified system dynamics model to a state-space model having a diagonal system matrix of system Eigenvalues through Eigendecomposition; estimating a battery current limit and an available power limit from the state space model; and operating the traction battery according to the estimated battery current limit and available power limit.

14 . The method of claim 13 wherein identifying the system dynamics model comprises identifying a system dynamics matrix, an input matrix and an output matrix.

15 . The method of claim 13 wherein identifying the system dynamics model includes using a subspace identification algorithm.

16 . The method of claim 15 wherein identifying 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.

17 . The method of claim 16 wherein identifying 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.

18 . The method of claim 13 wherein identifying the system dynamics model includes identifying the system dynamics model in real time.

Assignees

• Ford Global Tech Llc

Inventors

• Lee Tae-Kyung

Classifications

• H01M10/4257

  Smart batteries, e.g. electronic circuits inside the housing of the cells or batteries · CPC title

• B60L2260/44

  by parameter estimation · CPC title

• G01R31/3648

  comprising digital calculation means, e.g. for performing an algorithm · CPC title

• Y10S903/907

  Electricity storage, e.g. battery, capacitor · CPC title

• H01M2010/4271

  Battery management systems including electronic circuits, e.g. control of current or voltage to keep battery in healthy state, cell balancing · CPC title