scholarly journals High-Fidelity Transmission Simulation for Hardware-in-the-Loop Applications

Author(s):  
Orang Vahid ◽  
Paul Goossens
2020 ◽  
Vol 67 (8) ◽  
pp. 6835-6844
Author(s):  
Qiteng Hong ◽  
Ibrahim Abdulhadi ◽  
Dimitrios Tzelepis ◽  
Andrew Roscoe ◽  
Ben Marshall ◽  
...  

Author(s):  
Jason Poon ◽  
Elaina Chai ◽  
Ivan Celanovic ◽  
Adrien Genic ◽  
Evgenije Adzic

Author(s):  
Vefa Narli ◽  
Paul Y. Oh

This paper describes a test rig that is used to design and test sensor suites for unmanned air vehicles (UAV) operating in near-earth like environments such as forests, caves and urban canyons. The test rig employs a six degree-of-freedom gantry. Inside its workspace is a full-scale diorama of the environment. Surrounding the gantry are lamps, fans, and generators to reproduce lighting, rain and obscurants typical of such environments. A sensor pod is mounted at the gantry end-effector. The acquired data is fed into a high-fidelity math model of the real UAV. The output is then used to drive the gantry to move the sensor pod in the real world environment. The net effect is a hardware-in-the-loop system that emulates the real UAV’s motions and responses in near-Earth environments. The test rig is important because there is little to no data on sensor performance metrics of UAV in near-Earth environments.


Author(s):  
Tetsuji Kozaki ◽  
Hiroshi Mori ◽  
Hosam K. Fathy ◽  
Swaminathan Gopalswamy

The growing use of model-based engineering for powertrain design and validation imposes conflicting modeling requirements. Vehicle powertrain models must be accurate enough for design optimization, and fast enough for real-time verification on hardware-in-the-loop platforms. Because these two requirements conflict, one finds two families of powertrain models today: high-fidelity models and real-time models. Model surrogation can bridge the gap between these two families by extracting powertrain models accurate enough for optimization and fast enough for real time. This paper systematically derives surrogate torque converter, clutch friction, and clutch hydraulics models. Using these models, the simulation speeds for two automatic transmissions improve significantly without appreciable loss of accuracy.


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