Dongchan Lee

QUARTER CAR MODEL STRESS ANALYSIS FOR TERRAIN/ROAD PROFILE RATINGS

The US Army currently uses the root mean square of elevation (RMSE) and power spectral density (PSD) to characterise road/terrain roughness for ground vehicle durability assessment. This paper describes research aimed toward improving these measures. One potential method is running a relatively simple, yet vehicle class specific model over a given terrain and using predicted vehicle response(s) to characterise the terrain. A precedent for this concept is the International Roughness Index (IRI), used in the highway industry. The IRI consists of a simple tyre model and quarter car vehicle model run at a specified speed to estimate suspension velocity over a road profile. Another method of estimating road roughness is fatigue analysis. In this study, a generic specimen was subjected to the quarter car suspension forces. The stresses developed were used to make a fatigue life cycle prediction. This paper presents the key concepts and results from this analysis.

Further Analysis of Potential Road/Terrain Characterization Rating Metrics

The U.S. Army uses the root mean square and power spectral density of elevation to characterize road/terrain (off-road) roughness for durability. This paper describes research aimed toward improving these metrics. The focus is on taking previously developed metrics and applying them to mathematically generated terrains to determine how each metric discerns the relative roughness of the terrains from a vehicle durability perspective. Multiple terrains for each roughness level were evaluated to determine the variability for each terrain rating metric. One method currently under consideration is running a relatively simple, yet vehicle class specific, model over a given terrain and using predicted vehicle response(s) to classify or characterize the terrain.

Analysis of Potential Road/Terrain Characterization Rating Metrics

The U.S. Army uses the root mean square and power spectral density of elevation to characterize road/terrain (off-road) roughness for durability. This paper describes research aimed toward improving these metrics. The focus is on taking previously developed metrics and applying them to mathematically generated terrains to determine how each metric discerns the relative roughness of the terrains from a vehicle durability perspective. Multiple terrains for each roughness level were evaluated to determine the variability for each terrain rating metric. One method currently under consideration is running a relatively simple, yet vehicle class specific, model over a given terrain and using predicted vehicle response(s) to classify or characterize the terrain.

Preliminary Evaluation of the SAFE-Cue Warning Display for Loss of Control Mitigation

In response to the potential for unfavorable pilot-vehicle coupling, including pilotinduced oscillations, between novel adaptive flight control systems designed to safely operate air vehicles in the presence of damage or failures and the pilot flying the vehicle, the Smart Adaptive Flight Effective Cue was developed. The original incarnation of SAFE-Cue features an adaptive command path gain to mitigate oscillation tendencies and an inceptor force feedback cue to alert the pilot that the system is active and to temper inceptor commands as a complimentary oscillation mitigation technique. Following test pilot suggestions during the flight test evaluations of SAFE-Cue, a visual cue has been developed and added to the SAFE-Cue system as the SAFE-Cue warning display. Preliminary evaluations of the SAFE-Cue warning display by a NASA test pilot was conducted in a fixedbase simulator. The resulting pilot opinion ratings and quantitative assessment of performance indicated that the SAFE-Cue warning display both in isolation and in combination with the command path gain and force cue successfully mitigated the oscillation tendencies that can lead to loss of control by visually alerting the pilot of performance limitations caused by the failure or damage.

A Biodynamic Model for the Assessment of Human Operator Performance under Vibration Environment

A combined biodynamic and vehicle model is used to assess the vibration and performance of a human operator performing driving and other tasks. The other tasks include reaching, pointing and tracking by the driver and/or passenger. This analysis requires the coordinated use of separate and mature software programs for anthropometrics, vehicle dynamics, biodynamics, and systems analysis. The total package is called AVB-DYN, an acronym for Anthropometries, Vehicle and Bio-DYNamics. The biodynamic component of AVB-DYN is described, and then compared with an experiment that studied human operator in-vehicle reaching performance using the U.S. Army TACOM Ride Motion Simulator.