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predictive-models-for-hrs-can-drive-consumer-confidence
Photo by Dennis Schroeder, NREL
predictive-models-for-hrs-can-drive-consumer-confidence
Photo by Dennis Schroeder, NREL

Predictive models for HRS can drive consumer confidence

Consumer confidence in driving hydrogen-fuelled vehicles could be improved by having station operators adopt a predictive model that helps them anticipate maintenance needs, according to new US research.

Researchers at the Department of Energy’s National Renewable Energy Laboratory (NREL) and Colorado State University (CSU) found stations shutting down for unscheduled maintenance reduces hydrogen fuelling availability to consumers and may slow adoption of these types of fuel cell electric vehicles.

The use of what is known as a prognostics health monitoring (PHM) model would allow hydrogen stations to reduce these unscheduled events.

Jennifer Kurtz, lead author of the Hydrogen Station Prognostics and Health Monitoring Model paper said, “Motorists expect to be able to fuel their vehicles without any problems. We want to ensure motorists who drive hydrogen-fueled cars have the same experience. This predictive model can let station operators know in advance when a problem might occur and minimise any disruptions that motorists might experience with hydrogen fuelling.”

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