Digital Rack Load Estimation Methodology for Electric Power Steering to Optimize Motor Sizing

Electric Power Assisted Steering (EPAS) systems are integral to modern passenger vehicles, contributing to improved steering performance, enhanced safety, and enabling the integration of advanced driver assistance systems (ADAS). A critical aspect of EPAS design is precise motor sizing, which has a direct impact on steering dynamics, driver input effort, and overall system efficiency. The selection of an appropriate motor is governed by several parameters, including peak rack load, maximum steering speed, electrical supply constraints, thermal limitations, and spatial packaging considerations. This study specifically addresses the accurate estimation of rack force, a primary parameter guiding motor selection and assist control calibration. Previous researchers have explored multiple EPAS motor sizing methodologies such as iterative physical testing and simplified analytical modelling. Out of these, iterative physical testing incurs high resource costs and may hamper the development timeline. Whereas, simplified analytical models lacks fidelity in representing the non-linear dynamic behavior of steering systems. This paper presents a multi physics-based methodology for rack force estimation using a 1D system simulation environment. The proposed model incorporates the Dahl friction formulation to represent hysteresis effects in tire-road interaction, and employs rotary stiffness and damping parameters within the ball joint model to accurately characterize torque transmission between the steering arms and tie rods. The simulation results are validated against physical test data, exhibiting good correlation with measured rack forces and confirming model accuracy. The methodology effectively captures the non-linear characteristics of rack load behavior, providing a validated basis for EPAS motor sizing and enabling optimization of assist control strategies early in the design process.