Browsing by Author "Zhou, Jue"

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    Development of Surrogate Grass for the Evaluation of Vehicle Road Departure Mitigation Systems
    (IEEE, 2020-09) Chien, Stanley; Zhou, Jue; Yi, Qiang; Pandey, Seeta Ram; Saha, Abir; Lin, Jun; Chen, Yaobin; Sherony, Rini; Electrical and Computer Engineering, School of Engineering and Technology
    Vehicle road departure mitigation system (RDMS), as new active safety technology, has been introduced into the market in recent years. This system can detect roadside objects and road edges to reduce the risk of roadway departure crashes. To evaluate and improve the performance of RDMS, surrogates of roadside objects, which have the same camera, radar, and LiDAR characteristics of the real objects, need to be developed. Grass is the most common road edge in the U.S. as seen from the real road data. This paper describes the development of surrogate grass. The LiDAR (infrared) and radar characteristics of the selected artificial turf (grass) are obtained and compared with those of real grass. In order to make the surrogate grass match the real grass in the view of sensors (LiDAR, radar and camera), a special color coating with high reflectance material is applied to the artificial turf. Both LiDAR and radar measurements confirmed that the surrogate grass closely match the key characteristics of the real grass. Five grass colors and eighteen color patterns were identified based on 1,021 grass road-edge samples from all states of the U.S. 300-meter long surrogate grass was made and successfully used on the test track for the vehicle RDMS evaluation.
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    Two-Stage Method for Optimal Operation of a Distributed Energy System
    (IEEE, 2016-11) Xue, Jie; Zhou, Jue; Chen, Yaobin; Department of Electrical and Computer Engineering, School of Engineering and Technology
    In this paper, a gas turbine-based distributed energy system (DES) model is developed for the design of operation planning. An operation mode aimed to optimize the operation of this DES is proposed. A multi-objective cost function considering the total system efficiency and operational cost is formulated for the optimal design of DES operation and control. A two-stage approach combining the particle swarm algorithm (PSO) with the sequential quadratic programming (SQP) method is employed to solve the nonlinear programming problem. Optimal operation strategies for the DES are investigated using the proposed two-stage method under three different demand loads in terms of weather conditions. The simulation results are compared with those using traditional rule-based operation methods. It is found that under the proposed operation mode, the DES is capable of achieving an improved performance in terms of thermal efficiency and operational cost.