Reliability-Based Robust Design Optimization With Kernel Density Estimation for Electric Power Steering Motor Considering Manufacturing Uncertainties

Abstract

Reliability-based robust design optimization (RBRDO) is a notable method to secure the quality and feasibility of performances from uncertainties. In this paper, geometric uncertainties of a stator sheet that can occur during a stamping process are considered as the uncertainty of controllable variables. Then, as the uncertainty of uncontrollable variables, skew angle due to inexact lamination is considered. No researches on the effect of this uncertainty have been performed. To analyze the effects of the uncertainties, the kernel density estimation (KDE) was employed to estimate the distribution because of its convenience, flexibility, and robustness. Then, RBRDO with the KDE is performed and the optimum results are compared with real data measured from manufactured motors.

Optimal Design of a Surface Permanent Magnet Machine for Electric Power Steering Systems in Electric Vehicle Applications Using a Gaussian Process-Based Approach

“…Addressing specific design goals, such as the reduction of torque ripple and cogging torque, becomes crucial as the rotating movement is converted into the linear movement of the steering rack [2,3]. These factors directly impact the vibration and overall driving comfort of the vehicle.…”

Proposing a BSPID Control Strategy Considering External Disturbances for Electric Power Steering (EPS) Systems

“…In reference [3], Baharom et al pointed out some advantages of the EPS system, such as being less complicated, environmentally friendly, and more energy efficient. According to Jang et al, the EPS system performed better than the hydraulic steering system, while the electric motor was vibrationless and quiet [4]. The EPS system could support the driver in most situations based on extreme dynamics with high precision and comfortable operation, according to Truemmel et al [5].…”