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Techno-Economic Analysis of Truck Hybridization

Authors: Subhadyuti Sahoo; Jari Vepsäläinen; Antti Ritari; Raine Viitala; Kari Tammi;

Techno-Economic Analysis of Truck Hybridization

Abstract

Trucks, categorized as heavy-duty vehicles, contribute significantly to global carbon dioxide and greenhouse gas emissions owing to their heavy weight. Studies so far have focused separately on energy management and techno-economic analysis of such vehicles. However, impact of efficient energy management on the economic viability of hybridizing such heavy-duty vehicles remains underexplored. This study, therefore, examines the financial feasibility of hybridizing trucks equipped with a customized rule-based energy management strategy. Mild-hybrid and parallel-hybrid configurations are compared. Downsized electric components are used for the mild-hybrids fitted with electric-axles, an emerging technology which reduces emissions. Operational data from three distinct routes are utilized for techno-economic analysis. Physics-based models assist evaluation of rule-based energy management strategy's impact on pay-back time. Fuel savings and return on investment time are considered as the key performance analysis metrics. Model validation confirms that the physicsbased models accurately represent actual vehicle behavior. Overall, mild-hybrid trucks demonstrate higher fuel savings than the parallel-hybrids, except on one route. Enhanced fuel savings translates to increased monetary savings per trip, resulting in quicker pay-back time. This indicates that truck hybridization is financially attainable with proper powertrain selection for specific routes.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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