| 000 | 00959 a2200265 4500 | ||
|---|---|---|---|
| 005 | 20250516231403.0 | ||
| 264 | 0 | _c20150511 | |
| 008 | 201505s 0 0 eng d | ||
| 022 | _a1537-744X | ||
| 024 | 7 |
_a10.1155/2014/176052 _2doi |
|
| 040 |
_aNLM _beng _cNLM |
||
| 100 | 1 | _aTing, T O | |
| 245 | 0 | 0 |
_aTuning of Kalman filter parameters via genetic algorithm for state-of-charge estimation in battery management system. _h[electronic resource] |
| 260 |
_bTheScientificWorldJournal _c2014 |
||
| 300 |
_a176052 p. _bdigital |
||
| 500 | _aPublication Type: Journal Article; Research Support, Non-U.S. Gov't | ||
| 650 | 0 | 4 | _aAlgorithms |
| 650 | 0 | 4 | _aEnergy-Generating Resources |
| 650 | 0 | 4 | _aModels, Theoretical |
| 700 | 1 | _aMan, Ka Lok | |
| 700 | 1 | _aLim, Eng Gee | |
| 700 | 1 | _aLeach, Mark | |
| 773 | 0 |
_tTheScientificWorldJournal _gvol. 2014 _gp. 176052 |
|
| 856 | 4 | 0 |
_uhttps://doi.org/10.1155/2014/176052 _zAvailable from publisher's website |
| 999 |
_c24134872 _d24134872 |
||