Browse Topic: Hardware-in-the-loop (HIL)
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.
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 Cargo Hook (ACH) approach. These controllers were implemented, tested, and studied. It was shown that both were able to suppress LCO and stabilize the slung loads along the entire airspeed range.
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.
ABSTRACT Accurate real-time simulation models of small-scale multi-rotor vehicles are desirable for full-mission simulation and flight control evaluations within hardware-in-the-loop simulation. This paper presents the development and verification of a continuous, full-envelope stitched simulation model of a quadcopter using flight-identified models of the 3D Robotics IRIS+ and the newly-developed model stitching simulation software STITCH. Two flight-identified point models (one at hover and one at forward flight), plus some additional trim data, are shown herein to adequately and accurately capture the bare-airframe dynamics of the IRIS+ over its nominal flight envelope. The stitched simulation model is verified in the frequency domain for multiple airspeeds. Additionally, the off-nominal mass-, CG-, and inertia-extrapolation capabilities of STITCH are investigated and the results are verified against flight data for a heavy loading configuration. The overall findings are considered to provide flight-test guidance for the development of stitched simulation models of small-scale multi-rotor vehicles.
]. Traditionally, HIL simulations of hybrid vehicle controls and high-voltage battery controls have been implemented on separate HIL benches which are exclusively targeted for hybrid vehicle controls and battery controls simulations respectively. This research demonstrates an implementation of enhanced fidelity of a power-split hybrid vehicle powertrain controls HIL by integrating it with high-voltage traction battery subsystem HIL by networking the two aforementioned HIL systems together. The power-split hybrid vehicle HIL typically use simplified battery plant and controller models, and therefore, the addition of the high-voltage battery HIL provides a more detailed simulation of the high-voltage battery in which each cell is modeled such that cell voltage varies based on initial State-of-Charge (SOC) and temperature, capacity, fan speed, self-discharge, and other chemistry-based parameters. The integration of the battery HIL also provides the high-voltage interface to the battery controller hardware. The 2017 Ford Fusion Hybrid is used as the platform for this research. The battery subsystem performance of the vehicle is used as the baseline for comparison between the battery subsystem performances of the simplified power-split hybrid vehicle HIL and the networked HIL setup to understand the increased fidelity and accuracy of the latter.
ABSTRACT This paper presents the development of a framework for establishment of virtual environment for testing and tuning of attitude controller for rotary wing Unmanned Aerial Vehicles (UAVs). A flybarless mini-helicopter UAV is used as the platform for exposition of the proposed framework. A hardware-in-the-loop simulation (HILS) framework is established using a physics based flight dynamics simulation to enable controller design for rotary wing UAVs. The HILS setup includes the flight dynamics model, physical servo actuators and actual UAV autopilot. A computationally light real-time flight dynamics simulation is developed by using the properties estimated using series of simple ground-based experiments to simulate the small unmanned helicopter. The simulation is validated by performing flight tests on the actual UAV. It is demonstrated that accurate physics based simulations can be done without performing system-identification experiments, which can be an issue for an unstable rotary-wing vehicles with unknown dynamics. The utility of the HILS setup has been established by using the tuned PI attitude controller developed in the virtual environment for stabilization of the actual UAV under hovering condition. The validated HILS setup obviated the need for carrying out flight testing for system-identification, as all the relevant parameters required for the real-time simulation could be estimated using ground based tests.
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