Simulation model of an off-road four-wheel-driven electric vehicle
Tomasz Mirosław , Jan Szlagowski , Adam Zawadzki , Zbigniew Żebrowski
Abstractangielskim Electric vehicle gives much more advantages than only less air polluting or less noisy mobility. The current technology enables engineers to better control the electric motor than internal combustion engine. Electronic components like transistors, which can be switched on and off almost anytime, help to control the motor current and indirectly the torque and the speed. The progress in power electronics and motor construction opens new possibilities in vehicle construction and control. The process of wheel rolling can be better controlled which is very important especially on deformed surface of a road. The movement resistance can be reduced by smart power distribution between front and rear wheels in 4 × 4 drive vehicles, where front wheels can compact the ground and rear wheels can move on the rigid road. To reach all the advantages, we need a better understanding of a processes occurring in electric vehicles’ systems, which consist of motors, gears, and wheels reacting with ground. Authors present the model of 4 × 4 drive vehicle focused on this last, but not least, problem—part of an electric vehicle model which is the wheel–ground cooperation. This subsystem decides about power flow from the motor to the wheel and about traction and movement efficiency. This problem is not new, but flexible driving manner going with electric drive makes these analyses more practical and can be used in off-road electric vehicles. The analyses were supported by model and simulation prepared with MATLAB/Simulink software. In conclusion, the comparison of various drive properties and possibilities is presented and recommendations for further development are suggested.
|Journal series||Proceedings of the Institution of Mechanical Engineers Part I-Journal of Systems and Control Engineering, ISSN 0959-6518, (N/A 40 pkt)|
|Publication size in sheets||0.7|
|Keywords in English||Functional modeling, numerical modeling/simulation, physical modeling, process modeling, simulation programs, system simulation, systems identification|
|Score||= 40.0, 30-01-2020, ArticleFromJournal|
|Publication indicators||= 0; : 2016 = 0.743; : 2018 = 1.166 (2) - 2018=1.204 (5)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.