Operating Modes TRIZ Cases
- AI Battery SOH Prediction Using Driving Data and BMS Correction
Driving data, battery information, and optional BMS correction improve battery SOH prediction accuracy beyond battery-only models.
- Vehicle Battery Temperature Control for Timed Charging Readiness
By matching battery thermal adjustment time to predicted arrival time, this case reduces unnecessary heating or cooling before charging.
- Heterogeneous Battery Pack SoC Rescaling for ESS Voltage Control
Rescaled SoC values and joint voltage limits let mixed-generation battery packs operate safely in one ESS without over-charge or under-discharge.
- Heterogeneous Battery Pack SoC Rescaling for ESS Control
Rescaled SoC mapping aligns mixed battery pack voltage limits, enabling safe ESS control without over-charging or under-discharging.
- Battery Management Using Pressure Sensing for SOC Plateau Accuracy
Pressure-based SOC estimation complements OCV and current data to maintain battery charge accuracy when cells remain in the plateau region.
- High-Voltage Battery SoC Window Control for Aging and Range
Predictive SoC window setting matches required capacity before the next charge, extending battery life while preserving vehicle range.
- Vehicle Power Switch Remote Control With Motion-State Lockout
Remote server control lets a vehicle power switch be turned on or off over a network while blocking commands when the vehicle is moving.
- EV Range Determination Using Non-Contact Current Sensing
Non-contact current and voltage sensing improves EV range determination accuracy without modifying vehicle components or relying on faulty sensors.
- Electric Wheelchair Battery Control for Uphill Power Demand
Camera-guided battery selection powers only needed wheelchair components on slopes, reducing drain and extending battery service life.
- EV Battery SOC Monitoring With Gaze-Based Range Anxiety Detection
Driver gaze and SOC check frequency are used to detect range anxiety and trigger route or energy-saving recommendations.
- EV Battery Emergency Mode for Range Extension Under Estimation Error
When range estimation is too optimistic, the control unit lowers the cell-voltage limit to unlock reserve battery capacity and help the EV reach its destination.
- Adaptive Cruise and Battery Cooling for Driver-Specific Vehicle Control
Machine learning uses past driving patterns to adjust battery cooling and cruise control, improving energy use and distance-to-empty prediction.
- Fuel Cell Power Control for Route-Based Work Vehicle Loads
Route-based fuel cell output and battery charge control balance fluctuating work vehicle loads to improve energy distribution efficiency.
- Electric Water Truck Battery Planning for Dynamic Payload Routes
Segmented route energy prediction tracks changing dispense weight so electric water trucks can finish assigned spray routes without SoC shortfall.
- Vehicle Battery Voltage Estimation Without Voltage or Current Sensors
Battery voltage is estimated from desired power and current models, allowing continued vehicle operation and battery protection without sensors.
- Battery Aging Estimation Using State-Dependent Temperature Algorithms
Switching temperature algorithms by battery state duration improves internal resistance estimation and battery aging calculation accuracy.
- Traction Battery Charge Time Estimation for Partial SOC Accuracy
Two charge-time strategies improve traction battery estimates for full and partial SOC targets by accounting for aging and non-linear energy correlation.
- Battery Response Prediction Using Temporal Convolutional Networks
A temporal convolutional neural network predicts battery response from observed values and control profiles, improving BMS accuracy across battery types.
- Vehicle Battery Temperature Control by Driving State
Battery temperature limits are adjusted by driving state and navigation cooperation to curb deterioration and improve vehicle battery durability.