The Impact of Driver Behavior on Electric Bus Energy Consumption: Optimizing Driver Performance with Bio-Inspired WUTP Algorithm with Real-Time Big Data

Yunus Emre Ekici; Ozan Akdağ; Nisanur Yildiran; Teoman Karadag

doi:10.30939/ijastech..1789079

The Impact of Driver Behavior on Electric Bus Energy Consumption: Optimizing Driver Performance with Bio-Inspired WUTP Algorithm with Real-Time Big Data

Abstract

The transition toward sustainable urban mobility requires not only technological innovations in electric buses (E-Buses) but also optimization of operational factors such as driver behavior, which significantly influences energy consumption and driving range. This study develops a novel artificial intelligence framework, integrating real-time big data with a bio-inspired Water Uptake and Transport in Plants (WUTP) algorithm, to optimize E-Bus driver performance under real-world conditions. Data were collected from trolleybus-type hybrid electric buses operating in Malatya, Turkey, encompassing nearly 50 million observations across diverse seasonal, topographical, and operational contexts. Through preprocessing and correlation-based feature selection, 14 key parameters—including regenerative braking, auxiliary loads (HVAC and static converters), acceleration, and road slope—were identified as critical determinants of energy consumption. The WUTP algorithm, implemented with 60,000 representative data rows, generated optimized driving profiles and weighting coefficients, enabling precise estimation of optimal operational thresholds. Results reveal that maintaining regenerative braking above 77%, moderating accelerator pedal use at approximately 44%, and stabilizing average vehicle speed significantly extend range and reduce energy demand. Comparative evaluation of six drivers demonstrated efficiency disparities exceeding 30%, underscoring the importance of training and monitoring systems. The proposed model is distinguished by its dynamic treatment of auxiliary loads, scalability across routes and climates, and applicability for fleet planning, battery sizing, and eco-driving assessment. Overall, this research contributes a robust, adaptable, and scalable framework that enhances operational efficiency, reduces environmental impact, and supports the broader deployment of sustainable E-Bus systems in global transit networks.

Keywords

Thanks

We would like to thank Malatya Metropolitan Municipali-ty Transportation Services (MOTAŞ) for sharing trolley-bus data with us under the protocol, thereby enabling aca-demic research to be conducted.

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Details

Primary Language

English

Subjects

Hybrid and Electric Vehicles and Powertrains

Journal Section

Research Article

Authors

Yunus Emre Ekici
0000-0001-7791-0473
Türkiye

Ozan Akdağ
0000-0001-8163-8898
Türkiye

Nisanur Yildiran ^*
0000-0001-6689-7322
Türkiye

Teoman Karadag
0000-0002-7682-7771
Türkiye

Publication Date

December 31, 2025

Submission Date

September 22, 2025

Acceptance Date

November 19, 2025

Published in Issue

Year 2025 Volume: 9 Number: 4

DOI

https://doi.org/10.30939/ijastech..1789079

IZ

https://izlik.org/JA33TT64BL

Cite

RIS / Bibtex

APA

Ekici, Y. E., Akdağ, O., Yildiran, N., & Karadag, T. (2025). The Impact of Driver Behavior on Electric Bus Energy Consumption: Optimizing Driver Performance with Bio-Inspired WUTP Algorithm with Real-Time Big Data. International Journal of Automotive Science And Technology, 9(4), 602-617. https://doi.org/10.30939/ijastech..1789079

AMA

1.Ekici YE, Akdağ O, Yildiran N, Karadag T. The Impact of Driver Behavior on Electric Bus Energy Consumption: Optimizing Driver Performance with Bio-Inspired WUTP Algorithm with Real-Time Big Data. IJASTECH. 2025;9(4):602-617. doi:10.30939/ijastech.1789079

Chicago

Ekici, Yunus Emre, Ozan Akdağ, Nisanur Yildiran, and Teoman Karadag. 2025. “The Impact of Driver Behavior on Electric Bus Energy Consumption: Optimizing Driver Performance With Bio-Inspired WUTP Algorithm With Real-Time Big Data”. International Journal of Automotive Science And Technology 9 (4): 602-17. https://doi.org/10.30939/ijastech. 1789079.

EndNote

Ekici YE, Akdağ O, Yildiran N, Karadag T (December 1, 2025) The Impact of Driver Behavior on Electric Bus Energy Consumption: Optimizing Driver Performance with Bio-Inspired WUTP Algorithm with Real-Time Big Data. International Journal of Automotive Science And Technology 9 4 602–617.

IEEE

[1]Y. E. Ekici, O. Akdağ, N. Yildiran, and T. Karadag, “The Impact of Driver Behavior on Electric Bus Energy Consumption: Optimizing Driver Performance with Bio-Inspired WUTP Algorithm with Real-Time Big Data”, IJASTECH, vol. 9, no. 4, pp. 602–617, Dec. 2025, doi: 10.30939/ijastech..1789079.

ISNAD

Ekici, Yunus Emre - Akdağ, Ozan - Yildiran, Nisanur - Karadag, Teoman. “The Impact of Driver Behavior on Electric Bus Energy Consumption: Optimizing Driver Performance With Bio-Inspired WUTP Algorithm With Real-Time Big Data”. International Journal of Automotive Science And Technology 9/4 (December 1, 2025): 602-617. https://doi.org/10.30939/ijastech. 1789079.

JAMA

1.Ekici YE, Akdağ O, Yildiran N, Karadag T. The Impact of Driver Behavior on Electric Bus Energy Consumption: Optimizing Driver Performance with Bio-Inspired WUTP Algorithm with Real-Time Big Data. IJASTECH. 2025;9:602–617.

MLA

Ekici, Yunus Emre, et al. “The Impact of Driver Behavior on Electric Bus Energy Consumption: Optimizing Driver Performance With Bio-Inspired WUTP Algorithm With Real-Time Big Data”. International Journal of Automotive Science And Technology, vol. 9, no. 4, Dec. 2025, pp. 602-17, doi:10.30939/ijastech. 1789079.

Vancouver

1.Yunus Emre Ekici, Ozan Akdağ, Nisanur Yildiran, Teoman Karadag. The Impact of Driver Behavior on Electric Bus Energy Consumption: Optimizing Driver Performance with Bio-Inspired WUTP Algorithm with Real-Time Big Data. IJASTECH. 2025 Dec. 1;9(4):602-17. doi:10.30939/ijastech. 1789079

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International Journal of Automotive Science And Technology

https://doi.org/10.30939/ijastech..1836826