Stringent emissions regulations in cities and the high amount of daily miles driven by taxi vehicles enforce the need to renew these fleets with more efficient and cleaner technologies. Hybrid vehicles are potential candidates due to their enhanced powertrain, and slower battery depletion and fewer lifetime issues, relative to full electric vehicles. This paper proposes a methodology to analyze the best theoretical hybrid powertrain candidate with maximum in-use efficiency, minimum life cycle greenhouse gas emissions, and minimum additional cost, for a Lisbon taxi fleet case study. A multi-objective genetic algorithm integrated with a vehicle simulator is used to achieve several trade-off optimal solutions for different driving patterns. Potential improvements in taxi carbon footprint are discussed as a function of its lifetime, urban/extra-urban driving and maintenance/fuel life cycle uncertainty. Hybrid powertrains reveal to be advantageous comparatively to the conventional vehicle, especially in urban conditions. Specifically optimized solutions could reduce in-use energy consumption by 43%–47% in urban driving, and 27%–34% in extra-urban driving conditions, and reduce life cycle emissions by 47%–49% and 34%–36% respectively, relative to the conventional taxi. A financial gain of 50 $/km/fleet in extra-urban and 226 $/km/fleet in urban routes could be achieved by replacing the taxi fleet with the optimal solutions.
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