Improved estimation of hydrogen storage density in hydrogen-powered vehicles using Kalman filters
TUM.PtX News |
A recent publication from the Institute of Plant and Process Technology (APT) presents a novel approach for accurately estimating hydrogen storage density in cryo‑compressed hydrogen tanks. By applying an unscented Kalman filter, the remaining hydrogen amount can be determined with significantly improved reliability – a key requirement for accurate range prediction in hydrogen‑powered heavy‑duty vehicles.
Cryo‑compressed hydrogen (CcH₂) is considered a highly promising storage technology for long‑haul and heavy‑duty transport applications, as it enables very high storage densities and long driving ranges. At the same time, determining the remaining amount of hydrogen onboard is particularly challenging due to the extreme operating conditions inside the tank, where hydrogen is stored at high pressure and cryogenic temperatures.
In the new publication in Cryogenics, a soft‑sensing approach is introduced that combines pressure, temperature, and mass flow measurements with a detailed thermodynamic model of a cryo‑compressed hydrogen tank. The core of the methodology is a robust square root unscented Kalman filter, which fuses all available information and mitigates the effects of sensor noise, bias, and model uncertainty. The results demonstrate that the Kalman‑filter‑based approach outperforms state‑of‑the‑art estimation methods, especially under challenging operating conditions such as near‑critical thermodynamic states and variable load profiles.
This work makes an important contribution to the development of reliable onboard monitoring systems for cryogenic hydrogen storage in heavy‑duty mobility. Accurate knowledge of the remaining fuel enables optimized driving and refueling strategies. In the long term, the presented approach provides a solid foundation for intelligent state estimation and control concepts in cryo‑compressed hydrogen systems.
Link to the publication: