Rear-wheel brake control triggers automatic EV drifting from simple pedal and steering inputs, reducing driver skill demands and kickback.
Rear-wheel brake control automates EV drifting from steering, speed, and pedal inputs, reducing driver skill demands and kickback.
Limits pitch angle control near zero motor torque and smooths torque reversal to suppress kickback, improving vehicle stability and ride comfort.
Partial braking on turn-direction inner wheels with compensating drive maintains steering stability during SBW failure and helps prevent wheel locking.
Real-time wheel speed difference and reducer torque are checked against a differential limit curve to prevent skid-driven overload damage.
By regulating pedal and wheel torque from speed and DC link voltage, this case enables battery-free chainless e-bikes to meet EPAC pedaling requirements.
Linear yaw-rate and sideslip modeling enables real-time additional yaw moment allocation across tires with lower computation demand.
Coordinated modulation of dynamic and service brake torque helps heavy-duty vehicles avoid wheel lockup and shorten stopping distance on slippery roads.
Danger-based jerk adjustment lets adaptive cruise control smooth acceleration in low-risk driving while responding faster in critical situations.
Real-time lateral stability states guide steering and yaw moment control to keep intelligent EVs on track during emergency obstacle avoidance.
By linking ABS activation to assist mode, this e-bike design shares the motor drive source to prevent wheel lock without adding bulk.
AI torque control uses driver propensity, situational data, and external processing to improve EV driving response without redesigning legacy hardware.
Real-time comparison of obstacle and target distances lets a mobile robot stop at a preset safety gap, reducing rear-end collision risk.
A vehicle circuit manages creep mode activation via selector lever signals and brake pedal inputs to enable coasting without constant brake engagement.