Feedforward Control of a Hydraulic Clutch Actuation Path

The hydraulics of heavy-duty transmissions typically lack pressure sensors, which implies that the hydraulic actuation system has to be controlled in a feedforward manner. In practical applications, this is often done by numerically inverting a static mapping, leading to undesired pressure errors and inaccurate clutch positioning especially in dynamic situations. This paper therefore investigates two feedforward control strategies for a hydraulic clutch actuation path. The first is a flatness-based feedforward control strategy that relies on a high accuracy model, and additionally accounts for input constraints. The second one is a data-driven neural network-based feedforward control strategy that relies on measurement data. The feedforward controls are first evaluated in simulations and subsequently evaluated experimentally for a real-world transmission that demonstrates the realizability on ECU level as well as the effectiveness of the flatness-based and neural network-based feedforward controls compared to the standard static mapping-based approach.