Operating Modes TRIZ Cases

Road-aware power distribution lowers battery charge before low-load zones, keeping the fuel cell running and avoiding wasted energy.

Dynamic discharge-depth modeling improves vehicle battery softening deterioration assessment by matching lifetime discharge estimates to real usage.

A hybrid battery SOH model combines electrochemical aging equations with AI correction to improve health forecasts and charging control.

By estimating route energy demand against combined fuel cell and battery capacity, the controller warns drivers before battery depletion disrupts travel.

Driving-mode-based battery power limits curb temperature rise in autonomous travel while preserving drivability and battery life.

An EPP foam enclosure with external pre-heating keeps UAV batteries warm in sub-zero flight without draining onboard power.

Separate bar-delta filters estimate SOC, SOH, and SOP for mixed-age battery arrays, enabling safer power limits and longer pack life.

A master node broadcasts synchronized control to cell controllers, improving voltage verification and allowing cell disconnection with less pack impact.

Equivalent previous aging time lets battery aging models track changing temperature, state of charge, and charge rates more accurately.

Cell-level voltage monitoring detects imbalance early, enabling charge adjustment or cell isolation to prevent overcharge and extend battery life.

A voltage conversion module lets the vehicle power battery supply low-voltage loads during power-off while maintaining high-low voltage isolation.

Future power prediction sets cathode recirculation in advance to reduce switching transients and stabilize fuel cell output.

Machine-learning combines battery, driving, and environmental data to predict EV battery health for range, warranty, and trade-in decisions.

Sensors mounted across the pantograph detect conductive pathway offset, helping prevent misalignment, power interruption, and line damage.

Dynamic DCDC voltage switching meets low-voltage charging demand while preserving fuel economy during high power and engine flame-out states.

When current charge cannot support the planned trip, the vehicle switches to a power-saving mode to preserve range and reduce travel risk.

Intermittent high-level stimulation with rest periods speeds battery diagnosis while limiting polarization to estimate negative electrode deterioration.

Predicted driving events guide when to keep a vehicle fuel cell running or shut it down, cutting fuel waste while limiting stack aging.

A cost-based target temperature balances battery health, charging time, power delivery, and cooling energy under changing conditions.

Forecast-based battery preheating uses weather arrival and user driving time to prevent freezing damage and hard cold starts.

Accelerometer-based altitude prediction stabilizes FCEV battery SOC on uphill and downhill routes by adjusting fuel cell power without GPS.

An inverted degradation model sets battery core temperature targets to balance lifespan, driving range, and power draw in EV and power wall use.

Standstill duration prediction guides whether a vehicle fuel cell stays active or shuts down to limit degradation while preserving energy supply.

Predictive charging uses driving patterns and charging behavior to set battery SOC for future trips while reducing excessive charging and battery wear.

Future outside temperature forecasts trigger only needed battery heating or cooling, limiting deterioration and standby power use.