| LDR | | 00000nmm u2200205 4500 |
| 001 | | 000000330155 |
| 005 | | 20241024164202 |
| 008 | | 181129s2018 ||| | | | eng d |
| 020 | |
▼a 9780438017016 |
| 035 | |
▼a (MiAaPQ)AAI10748410 |
| 035 | |
▼a (MiAaPQ)purdue:22363 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
| 049 | 1 |
▼f DP |
| 082 | 0 |
▼a 621 |
| 100 | 1 |
▼a Williams, Kyle R. |
| 245 | 10 |
▼a Real-Time Stochastic Predictive Control for Hybrid Vehicle Energy Management. |
| 260 | |
▼a [S.l.] :
▼b Purdue University.,
▼c 2018 |
| 260 | 1 |
▼a Ann Arbor :
▼b ProQuest Dissertations & Theses,
▼c 2018 |
| 300 | |
▼a 144 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B. |
| 500 | |
▼a Adviser: Monika M. Ivantysynova. |
| 502 | 1 |
▼a Thesis (Ph.D.)--Purdue University, 2018. |
| 520 | |
▼a This work presents three computational methods for real time energy management in a hybrid hydraulic vehicle (HHV) when driver behavior and vehicle route are not known in advance. These methods, implemented in a receding horizon control (aka mod |
| 590 | |
▼a School code: 0183. |
| 650 | 4 |
▼a Mechanical engineering. |
| 690 | |
▼a 0548 |
| 710 | 20 |
▼a Purdue University.
▼b Mechanical Engineering. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 79-10B(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0183 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2018 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T14996984
▼n KERIS |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a 관리자
▼b 관리자 |