Analogue Computers For Vehicles TRIZ Cases

Force-sensor landing perches automate UAV pre-flight checks, charging, and launch approval to improve delivery safety without manual delays.

A pre-opening conditioning pulse frees a stuck fuel vapor retention valve before loading measurement, improving vapor control and reducing emissions.

Time-series pulse wave changes estimate each occupant's thermal sensation, enabling shared-space comfort control despite individual differences.

Multiple torque maps switch by speed, load, slope, and driver mode to curb invalid pedal fluctuation, improve fuel economy, and cut emissions.

Pre-mapped engine noise data guides air-fuel and rpm control to cut vehicle acoustic emissions and give drivers actionable feedback.

Camera and inertial sensor fusion adds context to traffic event detection, helping attribute cause and reinforce safe driving behavior.

ERP-based brain wave monitoring detects unstable driver states and links them to driving data for safer simulation and error-aware models.

Shelf slat sensing lets an autonomous warehouse vehicle verify rack position for accurate case transfer and fewer placement errors.

Baseline changes between a controller and UAV are measured with satnav sensors and mapped into precise motion commands for tight-space maneuvers.

By selecting and combining learning models from sensor-derived state data, this case improves fuel-mix command accuracy without manual map creation.

Hover power, motor speed, and load-cell data reveal unauthorized drone payloads before or during flight to protect safety and certification.

Throttle rate-of-change and RPM thresholds trigger engine sound enhancement only during spirited driving, preserving quiet cruising.

Sequential probe traces are compared with calculated road paths to detect attribute errors faster and keep transportation network data accurate.

Median and standard deviation filtering isolate mechanical vibration from knock signals, enabling more accurate ignition timing control.

Mobile endpoints combine signal readings with location data to map poor coverage regions automatically, cutting survey time and cost.

Noise-robust acoustic signatures and hybrid neural networks separate vehicle sounds from background noise for accurate real-time classification.

Pre-stored correction curves and calibration feedback linearize microwave sweeps, limiting temperature drift in multi-lane traffic sensing.

Corrected fuel rail pressure data removes injector and pumping artefacts, improving injected fuel quantity estimation from PDA.

An electric motor/generator pre-rotates the fueled-off engine with decompression active, enabling stable restart with lower energy use.

Gain-scaled integrative correction smooths handoffs between actuators, stabilizing boost pressure and reducing driver-perceptible jerks.