Model predictive control and optimization for battery charging and discharging
Abstract
An apparatus for model predictive control (“MPC”) is disclosed. A method and system also perform the functions of the apparatus. The apparatus includes a measurement module that receives battery status information from one or more sensors receiving information from a battery cell, and a Kalman filter module that uses a Kalman filter and the battery status information to provide a state estimate vector. The apparatus includes a battery model module that inputs the state estimate vector and battery status information into a battery model and calculates a battery model output, the battery model representing the battery cell, and an MPC optimization module that inputs one or more battery model outputs and an error signal in a model predictive control algorithm to calculate an optimal response. The optimal response includes a modification of the error signal.
- Inventors:
- Issue Date:
- Research Org.:
- Utah State Univ., Logan, UT (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1568381
- Patent Number(s):
- 10298026
- Application Number:
- 15/224,275
- Assignee:
- Utah State University (Logan, UT)
- Patent Classifications (CPCs):
-
H - ELECTRICITY H02 - GENERATION H02J - CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER
H - ELECTRICITY H02 - GENERATION H02M - APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS
- DOE Contract Number:
- AR0000271
- Resource Type:
- Patent
- Resource Relation:
- Patent File Date: 07/29/2016
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Trimboli, Michael Scott, Plett, Gregory L., Zane, Regan A., Smith, Kandler, Maksimovic, Dragan, Evzelman, Michael, Costinett, Daniel, and Anderson, Richard Dyche. Model predictive control and optimization for battery charging and discharging. United States: N. p., 2019.
Web.
Trimboli, Michael Scott, Plett, Gregory L., Zane, Regan A., Smith, Kandler, Maksimovic, Dragan, Evzelman, Michael, Costinett, Daniel, & Anderson, Richard Dyche. Model predictive control and optimization for battery charging and discharging. United States.
Trimboli, Michael Scott, Plett, Gregory L., Zane, Regan A., Smith, Kandler, Maksimovic, Dragan, Evzelman, Michael, Costinett, Daniel, and Anderson, Richard Dyche. Tue .
"Model predictive control and optimization for battery charging and discharging". United States. https://www.osti.gov/servlets/purl/1568381.
@article{osti_1568381,
title = {Model predictive control and optimization for battery charging and discharging},
author = {Trimboli, Michael Scott and Plett, Gregory L. and Zane, Regan A. and Smith, Kandler and Maksimovic, Dragan and Evzelman, Michael and Costinett, Daniel and Anderson, Richard Dyche},
abstractNote = {An apparatus for model predictive control (“MPC”) is disclosed. A method and system also perform the functions of the apparatus. The apparatus includes a measurement module that receives battery status information from one or more sensors receiving information from a battery cell, and a Kalman filter module that uses a Kalman filter and the battery status information to provide a state estimate vector. The apparatus includes a battery model module that inputs the state estimate vector and battery status information into a battery model and calculates a battery model output, the battery model representing the battery cell, and an MPC optimization module that inputs one or more battery model outputs and an error signal in a model predictive control algorithm to calculate an optimal response. The optimal response includes a modification of the error signal.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {5}
}
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