Improvement of Lap-Time of a Rear Wheel Drive Electric Racing Vehicle by a Novel Motor Torque Control Strategy

2017 ◽  
Author(s):  
Jyotishman Ghosh ◽  
Andrea Tonoli ◽  
Nicola Amati
Author(s):  
Nathaniel Steinbock ◽  
Laura Prange ◽  
Brian C. Fabien

Emergency lane changes are often the best course of action when avoiding obstacles on the road, but this maneuver has the possibility of sending the vehicle out of control. The University of Washington EcoCAR team has a hybrid-electric vehicle outfitted with an electric drivetrain and variable torque control to each of the rear wheels. Each rear wheel has an electric motor that is independently controlled to provide torque to the wheel. A lateral vehicle dynamics model is used to develop a torque control strategy to improve the safety and maneuverability of a modified hybrid-electric 2016 Camaro as part of the EcoCAR 3 competition. The specific scenario simulated is a two-lane lane change at a speed of 55 mph. We would like to increase the yaw and lateral accelerations that the vehicle can perform safely by controlling differing torques out of the two motors. Regulating these accelerations requires a control strategy over the left and right motor torques. Equal-torque control of the electric motors will be used as a baseline.


Filomat ◽  
2018 ◽  
Vol 32 (5) ◽  
pp. 1953-1963 ◽  
Author(s):  
Pei Li ◽  
Jun Yan ◽  
Qunzhang Tu ◽  
Ming Pan ◽  
Chengming Jiang

A steering control strategy based on bilateral torque fuzzy compensation for dual electric tracked vehicle is proposed in this paper. After the dynamic analysis of tracked vehicles, the mapping relationship between acceleration signal, braking signal, steering signal and bilateral motor torque is established. According to different driving states, the steering wheel real-time rotation angle and its change rate are interpreted as the motor torque compensation coefficients K1 and K2 by fuzzy algorithm to achieve quick response of driving intention. The steering control model of the electric tracked vehicle is built, and the HILS (hardware in loop simulation) platform is constructed with dSPACE. The HILS result shows that, by torque fuzzy compensation strategy, steering sensitivity and controllability could get better improvement compared with direct torque control strategy.


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