This study proposes a novel approach to evaluating and controlling the traction force of a wheel directly driven by an electric motor on different road surfaces. Instead of slip ratio measurements, the database of the motor called the current-RPM-torque database can evaluate the traction force of the wheel. The feedback of the measured current and the rotational speed can assist the autonomous traction controller synthesized from this database by the neural network approach when one traction wheel of the vehicle is traveling on different kinds of road surfaces. The adequate gains which are the training data for the neural network control synthesis have to satisfy the assigned specifications in time domain for different slip ratios. This paper also finds that the adequate gains mainly depend on slip ratio slope rather than slip ratio. Based on a scenario similar to real situations, the simulated results in this study show that it is feasible to evaluate and control the traction force through the motor database by the feedback of the current and the RPM.
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering