Low Carbon Hydrogen

Streamlining vehicle calibration with machine learning

THE PROBLEM

In Canada, heavy-duty trucking accounts for 1.37% of all vehicles on the road but disproportionately contribute 30% of all transport related emissions. In BC alone greenhouse gas emissions have grown 27% in the last decade and are forecasted to grow another 17.3% by 2030. Hydra recognizes the sustainability potential for the 489,000 diesel heavy-duty trucks in Canada, and a further 4 million in the US, to be converted to hydrogen-diesel co-combustion.

In order to scale and address the market Hydra needs to simplify its calibration process to allow for a greater number of conversions in a shorter period of time. Currently it can take several months to determine the optimal hydrogen injection rate to convert trucks via manual calibration, a time barrier that results in low conversion rates.

THE SOLUTION

Each heavy-duty trucking fleet has unique needs that require technology tailored to their uses. By taking advantage of new machine learning processes, Hydra will be able to create custom calibrations for each truck/fleet. 

This project supported by CICE focuses on refining Hydra’s machine learning processes that optimize hydrogen injection rates while maintaining diesel-like performance. This will enable rapid, tailored calibration of converted vehicles, enhancing the technology’s scalability and competitive edge.

PROJECT STATUS
Active
PROJECT CATEGORY
Low Carbon Hydrogen
FUNDING RECIPIENT
Hydra Energy Canada
CICE FUNDING AMOUNT
$625,550
PROJECT VALUE
$1,480,623