Adaptive battery parameter extraction and SOC estimation for lithium-ion battery

1. A method for estimating battery parameters of a battery, said method comprising:

reading, using a voltmeter and a current sensor electrically coupled to the battery, a measured battery voltage and a measured battery current, respectively;

calculating, using a controller in communications with the voltmeter and the current sensor, said controller including a processor and a memory, a signal vector based on the measured battery voltage and current and a previous battery voltage and current;

calculating a gain vector using the signal vector and a correlation matrix;

calculating an estimation error using the measured battery voltage and the signal vector;

adapting the battery parameters using the gain vector and the estimation error;

calculating a battery open circuit voltage and a battery resistance using the adapted battery parameters;

determining, using the controller, a battery state-of-charge using the battery open circuit voltage, including combining a voltage based state-of-charge and a current based state-of-charge using an adaptive weighting factor, where the voltage based state-of-charge is determined by a thermodynamic voltage and the current based state-of-charge is determined by Coulomb integration, and the adaptive weighting factor is adapted at each time step by an amount which is based on a validity of the battery open circuit voltage and based on a relationship between the rate of change of the voltage based state-of-charge and the rate of change of the current based state-of-charge; and

using the battery state-of-charge, by the controller, for power management of the battery, including controlling charging and discharging of the battery.

2. The method according to claim 1 wherein the method estimates six battery parameters.

3. The method according to claim 1 wherein the method estimates the battery open circuit voltage, an ohmic resistance, a double layer capacitance, a charge transfer resistance, a diffusion resistance and a diffusion capacitance.

4. The method according to claim 1 wherein the method uses a two RC-pair equivalent battery circuit model to estimate the battery parameters.

5. The method according to claim 1 wherein calculating a gain vector includes using the equation:

G

⁡

(

k

)

=

P

⁡

(

k

-

1

)

⁢

ϕ

⁡

(

k

)

λ

+

ϕ

T

⁡

(

k

)

⁢

P

⁡

(

k

-

1

)

⁢

ϕ

⁡

(

k

)

where G is the gain vector, P is the correlation matrix, Φ is the signal vector and λ is a forgetting factor.

6. The method according to claim 1 wherein calculating an estimation error includes using the equation:

α( k )= V ( k )−θ T φ( k )

where α is the estimation error, V is the measured voltage, θ is the battery parameters and Φ is the signal vector.

7. The method according to claim 1 wherein adapting the battery parameters includes using the equation:

θ( k )=θ( k− 1)+ G ( k )α( k )

where θ are the battery parameters, G is the gain vector and α is the estimation error.

8. The method according to claim 1 wherein the battery is a lithium-ion battery.

9. The method according to claim 1 wherein the battery is a vehicle battery on an electric vehicle and wherein the method is performed during operation of the vehicle.

10. A method for estimating battery parameters of a battery, said method comprising:

defining an equivalent battery circuit model of the battery that includes a battery open circuit voltage, a battery ohmic resistance, a first RC pair including a double layer capacitance and a charge transfer resistance and a second RC pair including a diffusion capacitance and a diffusion resistance;

reading, using a voltmeter and a current sensor electrically coupled to the battery, a measured battery voltage and a measured battery current, respectively;

representing, using a controller in communications with the voltmeter and the current sensor, said controller including a processor and a memory, the battery circuit model as a difference equation that includes the measured battery voltage and current and a plurality of battery parameters;

using the difference equation to determine the battery parameters that include the battery open circuit voltage, the ohmic resistance, a double layer capacitance, a charge transfer resistance, a diffusion resistance and a diffusion capacitance;

determining, using the controller, a battery state-of-charge using the battery open circuit voltage, including combining a voltage based state-of-charge and a current based state-of-charge using an adaptive weighting factor, where the voltage based state-of-charge is determined by a thermodynamic voltage and the current based state-of-charge is determined by Coulomb integration, and the adaptive weighting factor is adapted at each time step by an amount which is based on a validity of the battery open circuit voltage and based on a relationship between the rate of change of the voltage based state-of-charge and the rate of change of the current based state-of-charge; and

using the battery state-of-charge, by the controller, for power management of the battery, including controlling charging and discharging of the battery.

11. The method according to claim 10 wherein representing the battery circuit model as a difference equation includes using the equation:

V ( k )=θ 1 V ( k− 1)+θ 2 V ( k− 2)+θ 3 I ( k )+θ 4 I ( k− 1)+θ 5 I ( k− 2)+θ 6 U ( k )

where V is the measured voltage, I is the measured current, k is a time step and θ 1 , θ 2 , θ 3 , θ 4 , θ 5 and θ 6 are the battery parameters.

12. The method according to claim 10 wherein the battery is a lithium-ion battery.