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Dive into the research topics where Jinghui Wang is active.

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Featured researches published by Jinghui Wang.


Transportation Research Record | 2016

Modeling Fuel Consumption of Hybrid Electric Buses: Model Development and Comparison with Conventional Buses

Jinghui Wang; Hesham Rakha

Electric hybridization technologies appear to be one of the most promising approaches to improving the energy efficiency of buses; however, this improvement has not been systematically quantified. A fuel consumption model is essential for capturing fuel consumption behavior accurately and quantifying the fuel benefits of hybrid buses. Consequently, the objective of this study was to develop a fuel consumption model for hybrid buses on the basis of the framework of the Virginia Tech Transportation Institute’s comprehensive power-based fuel consumption model and then to quantify the benefits associated with hybridization technologies relative to conventional diesel bus operations. The model estimates were demonstrated to be consistent with in-field measurements, and the optimum fuel economy cruise speed was demonstrated to be approximately 50 km/h. The results demonstrate that hybrid buses consumed less fuel overall, while heavier buses and higher passenger loads may have reduced the fuel savings. The results also reveal that more fuel savings could be achieved for cruise and stop-and-go activity compared with idling behavior and that stop-and-go operation generated the highest level of fuel efficiency benefits. The conclusions of this paper can support bus planning applications to achieve fleet fuel savings.


Transportation Research Record | 2017

Convex Fuel Consumption Model for Diesel and Hybrid Buses

Jinghui Wang; Hesham Rakha

The concave fuel consumption model may generate unrealistic driving recommendations in a control system; for instance, the model may recommend higher cruise speed to achieve lower fuel consumption levels on steeper roads. To improve the model performance with regard to driving control, the study developed a convex second-order polynomial fuel consumption model for conventional diesel and hybrid-electric buses. The model simultaneously circumvents the bang-bang type of control that implies that drivers would have to accelerate at full throttle or brake at full braking to minimize their fuel consumption levels. Six bus series (four diesel series and two hybrid series), covering a wide range of bus properties, were modeled. The model was developed on the basis of the Virginia Tech comprehensive power fuel-based model (VT-CPFM) framework and, given a lack of readily available data, calibrated by conducting empirical measurements. The model was validated by comparing its estimates against in-field measurements and predictions from the comprehensive modal emissions model, the Motor Vehicle Emissions Simulator model, and the concave VT-CPFM model. The results demonstrate that the convex model generates estimates consistent with field measurements and the predictions of the other models and can provide realistic driving recommendations without significantly sacrificing accuracy relative to the concave model. Optimum fuel economy cruise speed ranges from 39 to 47 km/h for all tested buses on grades ranging from 0% to 8% and decreases with the increase of grade and vehicle load.


Applied Energy | 2016

Fuel consumption model for conventional diesel buses

Jinghui Wang; Hesham Rakha


Applied Energy | 2017

Electric train energy consumption modeling

Jinghui Wang; Hesham Rakha


Transportation Research Part D-transport and Environment | 2017

Fuel consumption model for heavy duty diesel trucks: Model development and testing

Jinghui Wang; Hesham Rakha


Transportation Research Part D-transport and Environment | 2017

Validation of the Rakha-Pasumarthy-Adjerid car-following model for vehicle fuel consumption and emission estimation applications

Jinghui Wang; Hesham Rakha; Karim Fadhloun


Transportation Research Part C-emerging Technologies | 2018

Longitudinal train dynamics model for a rail transit simulation system

Jinghui Wang; Hesham Rakha


Transportation Research Board 95th Annual MeetingTransportation Research Board | 2016

Heavy-Duty Diesel Truck Fuel Consumption Modeling

Jinghui Wang; Hesham Rakha


Transportation Research Board 94th Annual MeetingTransportation Research Board | 2015

Impact of Dynamic Route Information on Day-to-Day Driver Route Choice Behavior

Jinghui Wang; Hesham A Rakha


Transportation Research Board 97th Annual MeetingTransportation Research Board | 2018

A Simulation-Based Framework for Dynamic Ecorouting System: Model Development and Testing

Jinghui Wang; Ahmed Elbery; Hesham Rakha

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Lei Yu

Rush University Medical Center

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Fengxiang Qiao

Texas Southern University

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