| | SLO | ENG | Cookies and privacy

Bigger font | Smaller font

Show document Help

Title:Uporaba umetne inteligence za ugotavljanje vpliva voznika na porabo energije za pogon osebnega vozila : magistrsko delo
Authors:ID Zorman, Lina (Author)
ID Holobar, Aleš (Mentor) More about this mentor... New window
Files:.pdf MAG_Zorman_Lina_2026.pdf (2,59 MB)
MD5: 61A1E863489EACCD757EBB482E63C0E6
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V magistrskem delu je obravnavano napovedovanje porabe goriva na podlagi podatkov, zbranih med realno vožnjo z vmesnikom OBD-II in senzorji mobilnega telefona. Meritve so bile zbrane z enim voznikom in enim osebnim vozilom z bencinskim motorjem s prisilnim polnjenjem na 29 vožnjah. Podatki so bili predobdelani in uporabljeni za učenje regresijskih modelov strojnega učenja. Najboljše rezultate je dosegel naključni gozd z izborom značilk ElasticNet. Rezultati so pokazali, da so za napoved pomembne predvsem značilke hitrosti, položaja dušilne lopute, obremenitve motorja in pospeševanja. Na osnovi modela je bil izveden osnovni lokalni priporočilni sistem za varčnejšo vožnjo.
Keywords:poraba goriva, OBD-II, strojno učenje, vozni slog, priporočilni sistem
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[L. Zorman]
Year of publishing:2026
Number of pages:1 spletni vir (1 datoteka PDF (IX, 94 str.))
PID:20.500.12556/DKUM-98305 New window
UDC:004.85.021:519.2(043.2)
COBISS.SI-ID:283569923 New window
Publication date in DKUM:29.06.2026
Views:275
Downloads:27
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
:
Copy citation
  
Average score:(0 votes)
Your score:Voting is allowed only for logged in users.
Share:Bookmark and Share



Hover the mouse pointer over a document title to show the abstract or click on the title to get all document metadata.

Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:03.06.2026

Secondary language

Language:English
Title:Using artificial intelligence to determine the driver's impact on energy consumption in personal vehicles
Abstract:This master’s thesis investigates fuel consumption prediction using data collected in real-world driving from an on-board diagnostics interface and smartphone sensors. Measurements were collected over 29 drives by one driver in one passenger vehicle with a forced-induction gasoline engine. The data was cleaned, segmented into time windows, and transformed into driving-related features. Several regression-based machine learning models were evaluated, with the best performance achieved by a Random Forest model combined with ElasticNet feature selection. The results indicate that speed, throttle position, engine load, and acceleration-related features are important predictors. The selected model also supported an offline eco-driving recommendation system.
Keywords:fuel consumption, OBD-II, machine learning, driving style, recommendation system


Comments

Leave comment

You must log in to leave a comment.

Comments (0)
0 - 0 / 0
 
There are no comments!

Back
Logos of partners University of Maribor University of Ljubljana University of Primorska University of Nova Gorica