bibtype |
J -
Journal Article
|
ARLID |
0427942 |
utime |
20240111140847.0 |
mtime |
20140519235959.9 |
WOS |
000339037100017 |
DOI |
10.1016/j.trc.2014.04.009 |
title
(primary) (eng) |
Data-based Speed-limit-respecting Eco-driving System |
specification |
|
serial |
ARLID |
cav_un_epca*0255260 |
ISSN |
0968-090X |
title
|
Transportation Research. Part C: Emerging Technologies |
volume_id |
44 |
volume |
1 (2014) |
page_num |
253-264 |
publisher |
|
|
keyword |
eco-driving |
keyword |
fuel consumption |
keyword |
recommended speed |
keyword |
recursive estimation |
keyword |
quadratic optimal control |
keyword |
dynamic programming |
author
(primary) |
ARLID |
cav_un_auth*0108105 |
name1 |
Suzdaleva |
name2 |
Evgenia |
full_dept (cz) |
Adaptivní systémy |
full_dept (eng) |
Department of Adaptive Systems |
department (cz) |
AS |
department (eng) |
AS |
institution |
UTIA-B |
full_dept |
Department of Signal Processing |
fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
author
|
ARLID |
cav_un_auth*0101167 |
name1 |
Nagy |
name2 |
Ivan |
full_dept (cz) |
Adaptivní systémy |
full_dept |
Department of Adaptive Systems |
department (cz) |
AS |
department |
AS |
institution |
UTIA-B |
full_dept |
Department of Signal Processing |
fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
source |
|
cas_special |
project |
project_id |
TA01030123 |
agency |
GA TA ČR |
ARLID |
cav_un_auth*0271776 |
|
abstract
(eng) |
The paper describes application of data-based Bayesian approach to model identification and control problems in the field of fuel consumption optimization for conventional vehicles. The main contributions of the presented approach are: (i) analysis of data measured on a driven vehicle; (ii) data-based model construction, its real-time estimation and adaptation; (iii) control criterion using simultaneously setpoints for fuel consumption and speed; (iv) universal recursive Bayesian algorithms of estimation and control implemented as semi-automatic eco-driving system. Experiments with real data report reduction in fuel consumption. |
reportyear |
2015 |
RIV |
BC |
num_of_auth |
2 |
inst_support |
RVO:67985556 |
permalink |
http://hdl.handle.net/11104/0233598 |
confidential |
S |
mrcbT16-e |
TRANSPORTATIONSCIENCETECHNOLOGY |
mrcbT16-j |
1.147 |
mrcbT16-s |
2.045 |
mrcbT16-4 |
Q1 |
mrcbT16-B |
82.155 |
mrcbT16-C |
86.364 |
mrcbT16-D |
Q1 |
mrcbT16-E |
Q1 |
arlyear |
2014 |
mrcbU34 |
000339037100017 WOS |
mrcbU56 |
pdf |
mrcbU63 |
cav_un_epca*0255260 Transportation Research. Part C: Emerging Technologies 0968-090X 1879-2359 Roč. 44 č. 1 2014 253 264 Elsevier |
|