Battery identification, prediction and modelling
| dc.contributor.author | Azam, Syed Mahdi, author | |
| dc.contributor.author | Young, Peter M., advisor | |
| dc.contributor.author | Collins, George, committee member | |
| dc.contributor.author | Zimmerle, Dan, committee member | |
| dc.date.accessioned | 2018-09-10T20:04:30Z | |
| dc.date.available | 2018-09-10T20:04:30Z | |
| dc.date.issued | 2018 | |
| dc.description.abstract | In this paper, a process of modelling batteries for energy management systems has been discussed. With the increasing demand of energy management modelling, it is crucial that modelling of the components in an energy management model be done properly, effectively, and with least amount of time. The process introduced in this paper requires only one discharge data to model a battery. The internal parameters identified focuses on the electrical behavior rather than on electrochemical aspects of the battery. The battery model presented here helps to predict the discharge behavior of the battery in multiple discharging scenarios. In this modelling process, Online Parameter Identification technique has been used to identify the parameters of the battery. The parameters of the battery identified in this paper to predict the discharge behavior of a battery are internal resistance, polarization constant, nominal voltage and the actual capacity of a battery. Shepherd's equation and MATLAB's optimization toolbox was used to identify the parameters. | |
| dc.format.medium | born digital | |
| dc.format.medium | masters theses | |
| dc.identifier | Azam_colostate_0053N_14909.pdf | |
| dc.identifier.uri | https://hdl.handle.net/10217/191324 | |
| dc.language | English | |
| dc.language.iso | eng | |
| dc.publisher | Colorado State University. Libraries | |
| dc.relation.ispartof | 2000-2019 | |
| dc.rights | Copyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright. | |
| dc.subject | battery modelling | |
| dc.subject | control method | |
| dc.subject | microgrid control | |
| dc.subject | battery's internal parameters | |
| dc.subject | battery | |
| dc.subject | mathematical modelling | |
| dc.title | Battery identification, prediction and modelling | |
| dc.type | Text | |
| dcterms.rights.dpla | This Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). | |
| thesis.degree.discipline | Electrical and Computer Engineering | |
| thesis.degree.grantor | Colorado State University | |
| thesis.degree.level | Masters | |
| thesis.degree.name | Master of Science (M.S.) |
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