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Journal Article

Iterative Learning Algorithm Design for Variable Admittance Control Tuning of A Robotic Lift Assistant System

2017-03-28
2017-01-0288
The human-robot interaction (HRI) is involved in a lift assistant system of manufacturing assembly line. The admittance model is applied to control the end effector motion by sensing intention from force of applied by a human operator. The variable admittance including virtual damping and virtual mass can improve the performance of the systems. But the tuning process of variable admittance is un-convenient and challenging part during the real test for designers, while the offline simulation is lack of learning process and interaction with human operator. In this paper, the Iterative learning algorithm is proposed to emulate the human learning process and facilitate the variable admittance control design. The relationship between manipulate force and object moving speed is demonstrated from simulation data. The effectiveness of the approach is verified by comparing the simulation results between two admittance control strategies.
Technical Paper

Identification of Organic Acids in Used Engine Oil Residues by Pyrolysis-Comprehensive 2D Gas Chromatography-Time of Flight Mass Spectrometry

2016-10-17
2016-01-2274
The amount of acidic material in used engine oil is considered an indicator of the remaining useful life of the oil. Total acid number, determined by titration, is the most widely accepted method for determining acidic content but the method is not capable of speciation of individual acids. In this work, high molecular weight residue was isolated from used engine oil by dialysis in heptane. This residue was then analyzed using pyrolysis-comprehensive two dimensional gas chromatography with time-of-flight mass spectrometry. Carboxylic acids from C2-C18 were identified in the samples with acetic acid found to be the most abundant. This identification provides new information that may be used to improve the current acid detection methodologies for used engine oils.
Journal Article

General Motors’ New Reduced Scale Wind Tunnel Center

2017-03-28
2017-01-1534
The General Motors Reduced Scale Wind Tunnel Facility, which came into operation in the fall of 2015, is a new state-of-the-art scale model aerodynamic test facility that expands GM’s test capabilities. The new facility also increases GM’s aerodynamic testing through-put and provides the resources needed to achieve the growing demand for higher fuel economy requirements for next generation of vehicles. The wind tunnel was designed for a nominal model scale of 40%. The nozzle and test section were sized to keep wind tunnel interference effects to a minimum. Flow quality and other wind tunnel performance parameters are on par with or better than the latest industry standards. A 5-belt system with a long center belt and boundary layer suction and blowing system are used to model underbody flow conditions. An overhead probe traverse system is installed in the test section along with a model positioning robot used to move the model in an out of the test section.
Technical Paper

Cascaded Dual Extended Kalman Filter for Combined Vehicle State Estimation and Parameter Identification

2013-04-08
2013-01-0691
This paper proposes a model-based “Cascaded Dual Extended Kalman Filter” (CDEKF) for combined vehicle state estimation, namely, tire vertical forces and parameter identification. A sensitivity analysis is first carried out to recognize the vehicle inertial parameters that have significant effects on tire normal forces. Next, the combined estimation process is separated in two components. The first component is designed to identify the vehicle mass and estimate the longitudinal forces while the second component identifies the location of center of gravity and estimates the tire normal forces. A Dual extended Kalman filter is designed for each component for combined state estimation and parameter identification. Simulation results verify that the proposed method can precisely estimate the tire normal forces and accurately identify the inertial parameters.
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