Many studies have highlighted the added value of incorporating vehicle dynamics into microsimulation. Such models usually focus on simulation of conventional vehicles, failing to account for the acceleration dynamics of electrified vehicles that have different power characteristics from those of internal combustion engine vehicles (ICEV). In addition, none of them have explicitly dealt with the vehicle’s deceleration characteristics. Although it is not commonly considered critical how a vehicle decelerates, unrealistic behaviors in simulations can distort both traffic flow and emissions results. The present work builds on the lightweight microsimulation free-flow acceleration (MFC) model and proposes an extension, marking the first attempt to address these research gaps. First, a comprehensive review of dynamics-based car-following (including free-flow) models is conducted. Second, the methodology of the MFC model to capture the dynamics of electrified vehicles is described. Then, the experimental setup in different dimensions is introduced for the model validation and implementation. Finally, the results of this study indicate that: (1) the acceleration and deceleration potential curves underlying the MFC model can accurately represent real dynamics of electrified vehicles tested on the chassis dynamometer; (2) smooth transitions can be guaranteed after implementing the MFC model in microsimulation; (3) when reproducing the on-road driving trajectories, the MFC model can deliver significant reductions in root mean square error (RMSE) of speed (by ∼69%) and acceleration (by ∼50%) compared with benchmarks; (4) the MFC model can accurately predict the vehicle 0–100 km/h acceleration specifications, with RMSE 49.4% and 56.8% lower than those of the Gipps model and the intelligent driver model (IDM), respectively.


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    Title :

    Introducing Electrified Vehicle Dynamics in Traffic Simulation


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2020-07-07




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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