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Gear shift optimization for minimizing CO2 emissions of a diesel-hydrogen fueled truck

Research output: Contribution to journal › Conference article › peer-review

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Abstract

This research aims to minimize CO2 emissions of a retro-fitted diesel-hydrogen fueled truck by optimizing the gear shift strategy of its standard sixteen-speed automated manual transmission. The approach involves developing a dynamic programming algorithm aimed at maximizing diesel displacement by hydrogen for a given drive cycle, while taking driveability metrics into account. The developed gear shift strategy controls the gear position and shifts the engine operating region towards a high torque-low engine speed region, more favorable for hydrogen injection. The gear shift optimization is performed for the mono-fuel diesel engine map, serving as a baseline, and for the dual-fuel engine map. The theoretical reduction in CO2 emissions ranged from 1.3% up to 4.6%, depending on the vehicle payload and the drive cycle under consideration. Furthermore, the algorithm is used to generate real-time implementable shift maps designed to maximize dual-fuel efficiency for unknown drive cycles. Implementing the dual-fuel shift maps led to a reduction in CO2 emissions, spanning from 0.8% to 2.6%, in comparison to the mono-fuel optimized shift map. This reduction of 2.6% was observed near the maximum allowable payload of 20 tonnes.
Original languageEnglish
Pages (from-to)13-18
Number of pages6
JournalIFAC-PapersOnLine
Volume59
Issue number5
DOIs
Publication statusPublished - 2025
Event11th IFAC Symposium on Advances in Automotive Control, AAC 2025 - Domus Dela, Eindhoven, Netherlands
Duration: 16 Jun 2025 → 18 Jun 2025
https://aac2025.tue.nl/
https://www.sciencedirect.com/journal/ifac-papersonline/vol/59/issue/5

Keywords

  • Dual-fuel engines
  • drivetrain modeling
  • dynamic programming
  • optimal control

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