Single-zone AHU · Cooling coil · OA damper · Inject faults · Watch the FDD respond
This simulator injects common HVAC faults into a single-zone AHU model and shows how the fault detection and diagnostics (FDD) system responds, helping engineers and commissioning agents understand FDD rule sets and interpret AHU alarm conditions. It is used for training, sequence verification, and commissioning fault scenario testing.
FDD systems cross-check measured sensor values against the expected behavior derived from an energy balance or control logic model. The sensible heat balance for an AHU cooling coil is: Q = 1.08 × CFM × ΔT, where Q is cooling capacity in BTU/hr, CFM is supply airflow, and ΔT is the temperature rise from supply air to mixed air. If the measured supply air temperature consistently deviates from setpoint, the FDD system flags an alarm.
This simulator models three common fault modes: (1) Stuck OA damper — the outdoor air fraction exceeds the expected minimum, driving up mixed air temperature and cooling load; (2) Fouled cooling coil — coil heat transfer effectiveness is degraded, limiting deliverable cooling capacity; (3) SAT sensor drift — the supply air temperature sensor reads incorrectly, causing the controller to drive the true SAT off setpoint. Each fault is injected at a severity from 0–100% and compared to a healthy baseline.
ASHRAE Guideline 36 (2021) Section 5 defines standardized FDD rule sets for single-zone and multi-zone AHUs, including rules for SAT not meeting setpoint, coil at capacity, excess outdoor air, and sensor inconsistency. California Title 24 Energy Code requires automated FDD for rooftop units above 5 tons and chiller plants above 100 tons in new construction. ASHRAE Guideline 25 (Water-Side Economizer Systems) and Guideline 22 (Instrumentation for Monitoring Central HVAC Plant) provide additional FDD guidance. ASHRAE 100 (Energy Efficiency in Existing Buildings) references FDD as a retro-commissioning tool.
FDD accuracy depends on sensor quality and calibration: a supply air temperature sensor with ±2°F drift will generate false alarms for the SAT-not-meeting-setpoint rule if the alarm threshold is also ±2°F. Temperature sensors in AHU plenums should be calibrated to ±0.5°F for reliable FDD. Airflow measurement accuracy affects the energy balance calculation; flow stations should be calibrated to ±5% of reading. Model-based FDD (comparing measured values against a physics-based AHU model) can detect subtle faults like partial coil fouling or 20% excess OA that rule-based FDD may miss until the fault progresses to a severe state.
Set the operating conditions (outdoor air temp, return air temp, SAT setpoint, airflow, coil capacity) using the sliders, then select a fault type and severity. The comparison chart shows baseline (healthy) versus current (faulted) values for actual SAT, coil load in tons, and percent of rated capacity. The FDD status banner shows whether the fault is within normal tolerance, in warning range, or triggering a fault alarm with a specific diagnostic message. Use this to test how different fault combinations appear in the FDD system before commissioning.
Research from LBNL and PNNL finds that economizer faults (stuck or failed dampers, incorrect high-limit controls) are the most prevalent HVAC fault in commercial buildings, occurring in 50–70% of rooftop units surveyed. Supply air temperature sensor drift and fouled cooling coils are the next most common. Together these three fault types account for 80–90% of HVAC energy waste from mechanical failures.
A fouled coil reduces heat transfer effectiveness, causing the leaving air temperature to be higher than expected for the entering conditions. In FDD terms, the coil is operating at 100% of its degraded capacity while still failing to meet the SAT setpoint, appearing as both "coil at capacity" and "SAT not meeting setpoint" alarms simultaneously — the combination points to capacity degradation rather than control issues.
Rule-based FDD checks measured values against fixed thresholds (e.g., SAT must be within 2°F of setpoint). Model-based FDD compares measured values against predictions from a physics model of the equipment, detecting subtler faults that rule-based systems miss. Model-based FDD can identify a 15% reduction in coil capacity before it manifests as a setpoint deviation.
If a SAT sensor reads 3°F high (drifts positive), the controller drives the cooling coil harder to achieve the apparently-too-warm supply air, overcooling the air and requiring downstream reheat to prevent overcooling zones. This simultaneous cooling and heating is called simultaneous heating and cooling and is a major source of HVAC energy waste identified by FDD systems.
A stuck-open OA damper forces the AHU to condition 100% outdoor air on hot summer days rather than the typical 20–30% minimum. For a 10,000 CFM AHU handling 95°F outdoor air with a 75°F return, this increases the sensible cooling load from approximately 54,000 BTU/hr at minimum OA to 216,000 BTU/hr at full OA — a 4x increase in coil load that overwhelms cooling capacity and drives up chiller energy.
Try our Smart Buildings Studio
More calculators, simulators, and guides for this discipline.