Browse Publications Technical Papers 2017-01-2460
2017-10-08

A Novel Driver Model for Real-time Simulation on Electric Powertrain Test Bench 2017-01-2460

In this paper, a novel driver model is proposed to track vehicle speed in MIL (Model-in-the-Loop) test system, which has structural consistency with HIL (Hardware-in-the-Loop) test system. First, the MIL test system which contains models of driver, vehicle and test bench is established. Second, according to the connections of the established models in Matlab/Simulink environment, the vehicle speed is calculated in vehicle model. Emphatically, through the deviation between driving cycle speed and calculated vehicle speed, PI controller in driver model adjusts the vehicle speed to ideal point through sending the torque command to drive motor, the ILC (Iterative Learning Control) controller modifies and stores P value of PI controller. Then, in order to obtain the better modification of PI controller, iterative learning control algorithm is deeply researched in term of types and parameters. And the dynamic characteristic of test bench is analyzed through the shaft speed and dynamic torque of test bench. Finally, the performance of the novel driver model has been validated through the MIL test system.
The results show that under a piece of UDDS, the speed tracking accuracy can be increased by 5% on average and 20% under partial condition. The shaft speed of test bench will oscillate with the vehicle accelerated speed changing quickly in driving cycle. Besides, the oscillation period of shaft speed is about 600 ms, which reflects the torsional vibration characteristics of powertrain. The paper exerts a huge application value for further electric powertrain dynamic testing, namely improving the dynamic testing accuracy.

SAE MOBILUS

Subscribers can view annotate, and download all of SAE's content. Learn More »

Access SAE MOBILUS »

Members save up to 16% off list price.
Login to see discount.
Special Offer: Download multiple Technical Papers each year? TechSelect is a cost-effective subscription option to select and download 12-100 full-text Technical Papers per year. Find more information here.
X