Design and Optimization of Intelligent Electric-Drive-Wheel System with the Self-Sensing Unit of Wheel Load

Abstract:

Wheel load constitutes a critical information source for autonomous driving technology， reflecting the status of load distribution and vehicle motion. Conventional wheel force transducers （WFTs） present significant implementation challenges—including system complexity and spatial incompatibility—restricting their use to specially instrumented test vehicles. This paper introduces an innovative load-sensing unit integrated within an idler-gear speed reducer of an EDW， compatible with standard passenger car wheels. The EDW thereby achieves integration of the sensing and executing units. The research examines extreme vehicle conditions with lateral， longitudinal， and vertical wheel loads， establishing these as the working boundaries of the load-sensing unit. Within these parameters， structural parameters of the load-sensing unit serve as design variables， utilizing optimization algorithms to balance measurement sensitivity and decoupling performance. A virtual prototype facilitates CAE simulation across each signal channel of the dimensional component. Results demonstrate clear linear relationships between main signals while maintaining coupling signals within 15% of main signal amplitude， confirming successful optimization balancing sensitivity and decoupling performance.