Antilock Braking System (ABS) is designed to prevent wheels from locking, in order to enhance vehicle directional stability during braking manoeuvres. Basically, ABS closed-loop control logic uses tyres slip as control variable. Slip is estimated by comparing vehicle reference speed with the angular speed of each wheel. Thus it is crucial to correctly estimate the longitudinal vehicle speed, in order to get a control system capable of good performance. The control is also affected by road condition; since vehicles are not equipped with sensors able to measure the tyre/road friction coefficient, an other estimation has to be performed.
The paper presents an algorithm for the estimation of longitudinal speed, based on the measurements of the four wheel angular speed. A method to assess the road friction, commonly known as “learning phase” is also described: it is carried out during the early stage of the active control intervention and relies on the wheel rotation sensors as well.
At first the algorithms are tested through simulation, using a validated 14 degrees of freedom vehicle model. The hydraulic components of the ABS control unit are characterized through experimental tests and then modelled using transfer functions in order to correctly simulate the brake circuit pressure gradient during braking manoeuvres. The influence of different logic updating frequencies over the estimation error is investigated, as well as the sensitivity to several control parameters. The algorithms are then tested through a Hardware in the Loop (HiL) test bench in order to verify their compatibility with real time working conditions. Estimation outputs are compared with analogous values calculated by a commercial control logic.