Virtual shaft: Robust coupling by bidirectional and distributed prediction of coupling values

Abstract

Shifting automotive powertrain development tasks to earlier phases (frontloading) increases efficiency by utilizingtest-benches as opposed to prototype vehicles (road-to-rig approach). The coupling of distributed test-benches by a virtualized shaft connection is required to reproduce interactions of automotive powertrain components. A coupling algorithm simulates a rigid connection by synchronizing the torque and speed of two distributed test-bench’s electric motors. System dead-times lead to limited stability and reduced bandwidth of the coupling algorithm. In this study, a method for a stable bidirectional coupling of speed and torque of both subsystems is described analytically and verified by simulation. All component models are calibrated based on measurements using state-of-the-art test-bench equipment. A distributed prediction algorithm is proposed for the dead-time compensation. Four Kalman predictors estimate the coupling values of both subsystems at wall-clock-time without measurement and communication latencies. A detailed drive cycle analysis is performed through simulation. This enables a Virtual Shaft Algorithm to achieve a higher bandwidth and an improved coupling robustness.