نوع مقاله : Articles
عنوان مقاله English
نویسندگان English
This paper presents an integrated Electric Power Steering (EPS) framework that combines a two-degree-of-freedom lateral–yaw vehicle model, a detailed steering-column representation with road-torque feedback, and a future-prediction driver steering model. To replace conventional saturated linear assist curves, a compact Sugeno-type fuzzy assist-torque map is developed as a nonlinear and computationally efficient alternative. Using a minimal rule base with Gaussian membership functions, the proposed map ensures smooth, continuous transitions across driver-torque and vehicle-speed inputs while avoiding the discontinuities inherent to piecewise linear formulations. System performance is assessed in a representative driving scenario with realistic road curvature, steering column disturbances, and operating conditions spanning both low-speed maneuvering and higher-speed stability regimes. Simulations show that the fuzzy assist strategy reduces driver workload when additional support is required yet intentionally restrains torque amplification at elevated speeds to preserve stability and driver authority. It also yields smoother steering-column responses and improved motor-energy efficiency compared with the baseline linear assist curve demonstrating its suitability for real-time EPS applications.
کلیدواژهها English
