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 language | English |
|---|---|
| Pages (from-to) | 13-18 |
| Number of pages | 6 |
| Journal | IFAC-PapersOnLine |
| Volume | 59 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 2025 |
| Event | 11th 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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