Hydrogen Fueling Queue Delay Forecaster

Plan hydrogen depot infrastructure without overbuilding or starving routes. Feed in peak vehicle arrivals, dispenser cycle time, uptime expectations, and the share of trucks that must be served inside a target wait window to size dispenser banks and understand the resulting queue metrics.

Expected heavy-duty trucks arriving during the busiest fueling hour after route smoothing.
Average minutes required per fueling event, including connect, fill, vent, and disconnect tasks.
Percentage of dispenser uptime after accounting for maintenance windows, sensor faults, and other downtime.
Share of vehicles that must begin fueling within the target wait time to meet service-level commitments.
Optional — defaults to 10.00 minutes. Set the maximum acceptable queue wait for your fleet contract or grant requirement.

Queue outputs rely on stochastic assumptions. Validate results against site telemetry and safety engineering requirements before final procurement decisions.

Examples

  • Example 1 — Peak hour of 18 vehicles, 12.0 minute fills, 92.00% uptime, 90.00% service within a 10.0 minute target ⇒ Recommended dispensers: 6 | Utilization per dispenser: 0.65 | Service level within 10.0 minutes: 94.67% | Average queue wait: 1.65 minutes | 95th percentile wait: 10.40 minutes
  • Example 2 — Regional hub with 10 vehicles/hour, 15.0 minute fills, 88.00% uptime, 85.00% service within the default 10.0 minutes ⇒ Recommended dispensers: 5 | Utilization per dispenser: 0.57 | Service level within 10.0 minutes: 94.40% | Average queue wait: 1.57 minutes | 95th percentile wait: 10.89 minutes

FAQ

Can I change the acceptable wait threshold?

Yes. Provide a Target Wait Time value or leave it blank to default to 10.00 minutes, which mirrors several public funding benchmarks.

What if utilization exceeds 1.0?

The calculator automatically adds dispensers until utilization drops below 100%, ensuring the queue remains stable for sustained operations.

Does this include priority or dedicated fleet lanes?

No. Model those scenarios by adjusting peak vehicles per hour or by running separate calculations for each priority lane.

How should I treat downtime beyond scheduled maintenance?

Lower the uptime percentage to reflect forced outages so the resulting capacity plan preserves buffer for real-world availability.

Can I estimate hydrogen throughput from the results?

Multiply the recommended dispenser count by the uptime-adjusted service rate (60 ÷ fill time × uptime) to approximate hourly kilograms dispensed alongside the wait-time insights.

Additional Information

  • Queueing model uses an M/M/c approximation with uptime-adjusted service rates to reflect dispenser reliability.
  • Dispenser recommendation returns the smallest dispenser bank that achieves or exceeds the desired service level.
  • Average and 95th percentile waits assume exponential inter-arrival and service distributions consistent with depot telemetry.
  • Service level output expresses the share of vehicles that begin fueling within the chosen wait threshold.
  • Utilization percentages indicate the load on each dispenser, supporting maintenance scheduling and redundancy planning.

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