Browse Topic: Hardware-in-the-loop (HIL)

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WHY DO WE NEED SIMULATIONS? This paper is intended to provide a broad presentation of the simulation techniques focusing on transmission testing touching a bit on power train testing. Often, we do not have the engine or vehicle to run live proving ground tests on the transmission. By simulating the vehicle and engine, we reduce the overall development time of a new transmission design. For HEV transmissions, the battery may not be available. However, the customer may want to run durability tests on the HEV motor and/or the electronic control module for the HEV motor. What-if scenarios that were created using software simulators can be verified on the test stand using the real transmission. NVH applications may prefer to use an electric motor for engine simulation to reduce the engine noise level in the test cell so transmission noise is more easily discernable.
Johnson, Bryce
Abstract Test cycle simulation is an essential part of the vehicle-in-the-loop test, and the deep reinforcement learning algorithm model is able to accurately control the drastic change of speed during the simulated vehicle driving process. In order to conduct a simulated cycle test of the vehicle, a vehicle model including driver, battery, motor, transmission system, and vehicle dynamics is established in MATLAB/Simulink. Additionally, a bench load simulation system based on the speed-tracking algorithm of the forward model is established. Taking the driver model action as input and the vehicle gas/brake pedal opening as the action space, the deep deterministic policy gradient (DDPG) algorithm is used to update the entire model. This process yields the dynamic response of the output end of the bench model, ultimately producing the optimal intelligent driver model to simulate the vehicle’s completion of the World Light Vehicle Test Cycle (WLTC) on the bench. The results indicate that
Gong, XiaohaoLi, XuHu, XiongLi, Wenli
With modern aerospace vehicle configurations, highly-coupled redundant flight control surfaces are becoming standard practice. For such vehicles, traditional System Identification (SID) methods may not accurately capture the individual contributions of effectors to the vehicle bare-airframe response. A Joint Input-Output (JIO) methodology was used to estimate the control power for each highly-correlated roll effector of the Bell V-280 hover configuration. The methodology was demonstrated using flight test data, where the identification results were compared to a high-fidelity hardware-in-the-loop simulation in the V-280 System Integration Lab.
Berrigan, CaitlinJ., MarkPrasad, J.V.R.Ruckel, Paul
A new hardware-in-the-loop (HIL) dynamic wind tunnel setup is used to study the behavior of a slung load at high speeds and methods of stabilizing problematic loads. The main element of the setup is a movable cargo hook. In addition the cable angles, model spatial attitude, and hook force are measured continuously. All the measurements are fed into a computer that calculates the cargo hook resultant motion in real-time by summing the rotorcraft angular motion effects (not used in the current study) and the hook motion relative to the rotorcraft fuselage. The computer output includes motion commands to the hook. The slung loads are two configurations of an M119 howitzer: folded and ready for firing. Initial wind tunnel studies showed that these loads exhibit significant LCO (Limit Cycle Oscillations) and severe instabilities at high speeds. Frequency sweep tests are used to derive dynamic models of the slung loads. These models are used to develop two controllers based on an Active
Rosen, AvivNadell, SamuelChen, ZhouzhouCicolani, LuigiTischler, MarkRaz, ReubenCheung, KennyEnciu, JacobHorn, Joseph
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