Battery state-of-charge estimation for hybrid and electric vehicles using extended kalman filter techniques

Patent metadata

Field	Value
Publication number	US-9575128-B2
Application number	US-201313795813-A
Country	US
Kind code	B2
Filing date	Mar 12, 2013
Priority date	Mar 12, 2013
Publication date	Feb 21, 2017
Grant date	Feb 21, 2017

Abstract

Adaptive estimation techniques to create a battery state estimator to estimate power capabilities of the battery pack in a vehicle. The estimator adaptively updates circuit model parameters used to calculate the voltage states of the ECM of a battery pack. The adaptive estimation techniques may also be used to calculate a solid-state diffusion voltage effects within the battery pack. The adaptive estimator is used to increase robustness of the calculation to sensor noise, modeling error, and battery pack degradation.

First claim

What is claimed is:

1. A method for managing a battery in a vehicle, wherein the vehicle includes a battery management controller including a processor and a computer-readable medium containing computer readable and executable instructions, the method comprising:
in response to detecting a predetermined state in the vehicle:
sensing, with at least one sensor electrically coupled to the battery, a voltage and a current of the battery;
executing, in the battery management controller, an instruction to cause the battery management controller to:
determine a solid-state diffusion voltage effect employing a solid-state diffusion effects model based upon the sensed voltage of the battery,
determine an observed output by subtracting the solid-state diffusion voltage effect from the sensed voltage of the battery,
determine double-layer voltage and circuit parameter estimates and an associated covariance based upon the observed output employing an adaptive estimation technique,
determine a Kalman gain based upon the double-layer voltage and circuit parameter estimates and the associated covariance, and simultaneously calculate a modeled output of terminal voltage based upon the double-layer voltage and the circuit parameter estimates,
sense, with the at least one sensor electrically coupled to the battery, a voltage and a current of the battery,
determine an output model error based upon the sensed voltage of the battery,
update the double-layer voltage and the circuit parameter estimates based upon the Kalman gain and the output model error,
determine an open-circuit voltage of the battery based upon the double-layer voltage, and
determine a state of charge for the battery based upon the open-circuit voltage; and

managing the power output of the battery using the state of charge for the battery.

2. The method of claim 1 , wherein a start-up temperature and a shut-down temperature are recorded in the computer-readable medium and used to vary the solid-state diffusion effects model upon start-up.

3. The method of claim 1 , wherein an off-time is recorded in the computer-readable medium and used to compensate the solid-state diffusion effects model upon start-up.

4. The method of claim 1 , wherein the solid-state diffusion effects model comprises an equivalent circuit of the battery, at least one state of the battery and a diffusion circuit element of the battery.

5. The method of claim 1 , wherein the adaptive estimation technique comprises an extended Kalman filter.

Assignees

• Gm Global Tech Operations Llc

Inventors

• Frost Patrick
• Koch Brian J
• Frisch Damon R
• Stawinski Brett B
• Laskowsky Patricia M
• Johnson Kurt M
• Baraszu Robert C

Classifications

• H01M10/486

  for measuring temperature · CPC title

• G01R31/3606 Primary

  Physics · mapped topic

• B60L11/1861

  Operations & Transport · mapped topic

• B60L11/1857

  Operations & Transport · mapped topic

• B60L2240/549

  Current · CPC title