Traction control algorithm based on fuzzy PID and PWM modulation

In this paper, a traction control system has been designed in order to improve vehicle traction on slippery roads. First, a nonlinear model has been formulated from the vehicle longitudinal dynamics, the drivetrain model and the wheel motion. Then, a Takagi-Sugeno (TS) fuzzy representation has been proposed in order to take into account the nonlinearities of the obtained model and to simplify the controller design. Based on the obtained TS model, a proportional integral (PI) state feedback controller has been developed. The objective is to compute the optimal engine torque so that the longitudinal slip ratio does not exceed a desired value which is the limit of the optimal traction and the vehicle stability. Lypunov and H ∞ approaches have been used in the controller design and stability conditions are given in terms of Linear Matrix Inequalities (LMI). In order to show the effectiveness of the developed approaches, the vehicle model has been simulated on a slippery road with and without the traction control system.

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“…Using the TS model of the adhesion coefficient given in (13), vehicle model (11) can be represented by the following TS fuzzy model:…”

Section: Ts Model Descriptionmentioning

confidence: 99%

“…Dahmani fuzzy control [8]- [11]. The advantage of the PID controller is the simplicity and its application without a mathematical model, but it is difficult to obtain the control parameters to achieve satisfactory results, especially when the road conditions change.…”

Section: Introductionmentioning

confidence: 99%