Estimation Equivalent Circuit Battery
Resistor-capacitor (RC) circuit battery that creates lookup tables
Libraries:
Powertrain Blockset /
Energy Storage and Auxiliary Drive /
Network Battery
Description
The Estimation Equivalent Circuit Battery block implements a resistor-capacitor (RC) circuit battery model that you can use to create lookup tables for the Equivalent Circuit Battery block. The lookup tables are functions of the state-of-charge (SOC).
The Estimation Equivalent Circuit Battery block calculates the combined voltage of the network battery using parameter lookup tables. The tables are functions of the SOC. To acquire the SOC, the block integrates the charge and discharge currents.
Specifically, the block implements these parameters as lookup tables that are functions of the SOC:
Series resistance, Ro=ƒ(SOC)
Battery open-circuit voltage, Em=ƒ(SOC)
Network resistance, Rn=ƒ(SOC)
Network capacitance, Cn=ƒ(SOC)
To calculate the combined voltage of the battery network, the block uses these equations.
Positive current indicates battery discharge. Negative current indicates battery charge.
The equations use these variables.
SOC | State-of-charge |
Em | Battery open-circuit voltage |
Ibatt | Per module battery current |
Iin | Combined current flowing from the battery network |
Ro | Series resistance |
n | Number of RC pairs in series |
Vout, VT | Combined voltage of the battery network |
Vn | Voltage for |
Rn | Resistance for |
Cn | Capacitance for |
Cbatt | Battery capacity |
Examples
Ports
Inputs
Output
Parameters
References
[1] Ahmed, Ryan, et al. "Model-Based Parameter Identification of Healthy and Aged Li-ion Batteries for Electric Vehicle Applications." SAE International Journal of Alternative Powertrains. 4, no. 2 (2015): 233 -47. https://doi.org/10.4271/2015-01-0252.
[2] Gazzarri, Javier, Nishant Shrivastava, Robyn Jackey, and Craig Borghesani. "Battery Pack Modeling, Simulation, and Deployment on a Multicore Real Time Target." SAE International Journal of Aerospace. 7, no. 2 (2014): 207–13. https://doi.org/10.4271/2014-01-2217.
[3] Huria, Tarun, Massimo Ceraolo, Javier Gazzarri, and Robyn Jackey. “High Fidelity Electrical Model with Thermal Dependence for Characterization and Simulation of High Power Lithium Battery Cells.” IEEE® International Electric Vehicle Conference, March 2012. https://doi.org/10.1109/ievc.2012.6183271.
[4] Huria, Tarun, Massimo Ceraolo, Javier Gazzarri, and Robyn Jackey. "Simplified Extended Kalman Filter Observer for SOC Estimation of Commercial Power-Oriented LFP Lithium Battery Cells." SAE Technical Paper Series, 2013. https://doi.org/10.4271/2013-01-1544.
[5] Jackey, Robyn A. "A Simple, Effective Lead-Acid Battery Modeling Process for Electrical System Component Selection." SAE Technical Paper Series, 2007. https://doi.org/10.4271/2007-01-0778.
[6] Jackey, Robyn A., Gregory L. Plett, and Martin J. Klein. "Parameterization of a Battery Simulation Model Using Numerical Optimization Methods." SAE Technical Paper Series, 2009. https://doi.org/10.4271/2009-01-1381.
[7] Jackey,Robyn, et al. "Battery Model Parameter Estimation Using a Layered Technique: An Example Using a Lithium Iron Phosphate Cell." SAE Technical Paper Series, 2013. https://doi.org/10.4271/2013-01-1547.
[8] Geng, Zeyang, Jens Groot, and Torbjorn Thiringer. “A Time- and Cost-Effective Method for Entropic Coefficient Determination of a Large Commercial Battery Cell.” IEEE Transactions on Transportation Electrification 6, no. 1 (March 2020): 257–66. https://doi.org/10.1109/TTE.2020.2971454.
Extended Capabilities
Version History
Introduced in R2017a