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

Rack load estimation during the pre-design stages is critical for the calibration of steering systems, particularly in achieving the desired steering feel and optimizing assistance strategies in Electric Power Assisted Steering (EPAS). Conventional approaches often depend on physical vehicle testing or simplified empirical equations, which may be time-consuming or lacks the fidelity required for early-stage analysis. This paper presents a 1D simulation strategy to address limitations from conventional approaches. The proposed rack force estimation model is based on multi-physics analytical equations that calculate tire-road friction forces and the resulting moments about the steering axis, delivering a physics-based yet computationally efficient solution. The rack force estimation model is further extended into EPAS system model by incorporating Direct Current (DC) brushed motor model. The rack force estimation model is validated against physical test data which demonstrates a high level of accuracy. Finally, the EPAS motor sizing strategy is discussed to obtain the optimum motor size. The proposed simulation based approach enables engineering teams to make informed design decisions and optimize steering system behavior before physical prototypes are available.