Sustainable driving operations of urban plugin hybrid buses considering restricted emission mapping zones

Battery management; Genetic algorithms; Multi-objective optimization; Plug-in electric hybrid vehicles; Sustainable transport; Urban mapping; Urban public transport; Battery Management; Electric hybrid vehicles; Electric range; Emission zone; Multi-objectives optimization; Plug-ins; Urban Public Transport; Zero emission; Control and Systems Engineering; Artificial Intelligence; Electrical and Electronic Engineering

Abstract :

[en] Road traffic is the major source of air and noise pollution. It is also one of the largest contributors to anthropogenic greenhouse gas emissions. Transport electrification can significantly reduce these negative externalities. However, electric buses do not often meet public transport requirements, due to their limited battery capacity. In contrast, plug-in hybrid electric buses offer a versatile alternative, providing zero-emission capabilities that depend on battery capacity, charging frequency, and the distribution of electric drive along a route. However, current electric drive assignment systems are oversimplified, thus not fully leveraging their potential. This work extends our previous research, which introduced a novel combinatorial optimization problem aimed at determining optimal electric drive assignment strategies for Plugin Electric Hybrid (PEH) buses. A large number of bus lines as well as zero-emission and restricted-emission zones are considered. The objectives are to maximize the buses’ electric range and minimize the overall pollution while adhering to mandatory zero-emission and restricted-emission zones. In this study, we analyze seventy bus lines from Barcelona's urban public bus network (Spain), and tackled this large problem with two parallel implementations of the Cooperative Co-evolutionary Multi-objective Cellular Genetic Algorithm (CCMOCell). The strategies provided by both CCMOCell versions are validated against GreenK, a state of the art heuristic that only focuses on the electric range. Results demonstrate that the obtained solutions achieve up to 7.67% reduction in carbon dioxide (CO2) emissions, compared to GreenK, at the cost of a slight decrease in terms of electric range, i.e. 2.28%. However, the strategy found by GreenK is unfeasible, because it exceeds the pollution threshold established for one restricted-emission zone by 635 CO2 kilograms per day.

Disciplines :

Computer science

Author, co-author :

Díaz-Jiménez, Marina ; School of Engineering, University of Cadiz, Puerto Real, Spain

Aragón-Jurado, José Miguel ; School of Engineering, University of Cadiz, Puerto Real, Spain

Dorronsoro, Bernabé ; School of Engineering, University of Cadiz, Puerto Real, Spain

Pavón-Domínguez, Pablo ; School of Engineering, University of Cadiz, Puerto Real, Spain

SEREDYNSKI, Marcin ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SNT Office > Project Coordination

Ruiz, Patricia ; School of Engineering, University of Cadiz, Puerto Real, Spain

External co-authors :

Language :

English

Title :

Sustainable driving operations of urban plugin hybrid buses considering restricted emission mapping zones

Publication date :

01 October 2025

Journal title :

Engineering Applications of Artificial Intelligence

ISSN :

0952-1976

Publisher :

Elsevier Ltd

Volume :

157

Pages :

111179

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

https://api.elsevier.com/content/article/PII:S0952197625011807?httpAccept=text/xml

Funders :

Ministerio de Ciencia, Innovación y Universidades
Agencia Estatal de Investigación
Ministerio de Ciencia e Innovación
European Commission
European Regional Development Fund

Funding text :

This publication is part of PID2022-137858OB-I00 project (eMob), funded by Spanish Ministerio de Ciencia, Innovaci\u00F3n y Universidades , the AEI and the ERDF on MCIN/AEI/10.1309/5011 00011033/FEDER , UE and project eFracWare ( TED2021-131880B-I00 ) funded by MCIN/AEI/10.13039/501100011033 and the European Union \u201CNextGenerationEU\u201D/PRTR . M. D\u00EDaz-Jim\u00E9nez would like to acknowledge the Spanish Ministerio de Ciencia, Innovaci\u00F3n y Universidades for the support through PREP2022-000333 grant. J.M. Arag\u00F3n-Jurado would like to acknowledge the Spanish Ministerio de Ciencia, Innovaci\u00F3n y Universidades for the support through FPU21/02026 grant.

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since 19 December 2025

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