Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Electrical Engineering | en_US |
| dc.creator | Wang, Minghuang | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/13106 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | en_US |
| dc.rights | All rights reserved | en_US |
| dc.title | Modelling of battery storage system | en_US |
| dcterms.abstract | With the rapid development of lithium-ion batteries, more and more energy storage systems are using batteries as carriers. In the last five years in particular, electric vehicles have become a model for the efficient use of energy and the protection of the environment. It is therefore essential that lithium-ion energy storage systems are used in a rational and safe manner. Accidents, led by lithium batteries, have also increased with the popularity of electric vehicles. Therefore, the operating status of the battery system needs to be monitored and predicted in real time. | en_US |
| dcterms.abstract | To solve the problem, various battery models are constructed to serve as a reference for the external characteristics of the battery. The algorithms have been incorporated into the model to enhance the accuracy of the model as an important part of the BMS (Battery Management System). | en_US |
| dcterms.abstract | In this thesis, an Equivalent Circuit Model (ECM) is introduced. To verify the accuracy of the battery electrical system, a Kalman filtering based parameter extraction model is established. The influence of electrical parameters with temperature and operating conditions will be tested and discussed. Two thermal models will be conducted to demonstrate the equivalence of the physical domain. An ideal of the coupled electro-thermal system is introduced and established. Its adaptive capacity will be verified with an example. | en_US |
| dcterms.extent | vii, 67 pages : color illustrations | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2023 | en_US |
| dcterms.educationalLevel | M.Sc. | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.LCSH | Electric vehicles -- Batteries | en_US |
| dcterms.LCSH | Lithium ion batteries | en_US |
| dcterms.LCSH | Battery management system | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.accessRights | restricted access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 7558.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 3.53 MB | Adobe PDF | View/Open |
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