Intention recognition-based braking strength control of an automotive magnetorheological fluid-based braking system

Braking intention recognition plays a pivotal role in advancing braking assistant systems and enhancing driving safety, and is expected to be an essential component in intelligent automotive brake-by-wire systems. This paper proposes an intention recognition-based braking strength control algorithm that utilizes fuzzy logic to construct a robust control model. In addition, the braking intention parameters are selected according to the classification of braking status. The credibility of the proposed control algorithm is validated through comprehensive simulations, followed by its integration into the flywheel type 1/4 automotive magnetorheological fluid-based braking system test bench, equipped with a brake pedal simulator. Subsequently, braking control experiments are conducted within the established experimental system. Simulation results demonstrate that the braking strength control model realizes effective braking control and braking experiments indicate the accuracy of the braking intention recognition method. Importantly, the vehicle velocity variations under the proposed braking strength control model aligns with the expectation.