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 the internal combustion engine ones (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 can distort both traffic flow and emissions results. The present work builds on the lightweight microsimulation free-flow acceleration model (MFC) and proposes an extension, marking the first attempt to address the above research gaps. Firstly, a comprehensive review of dynamics-based car-following (including free-flow) models was conducted. Secondly, the methodology in the MFC model to capture the dynamics of electrified vehicles was described. Then, the experimental setup in different dimensions was introduced for the model validation and implementation. Finally, the results of this study indicate that: 1) the acceleration and deceleration potential curves underlying MFC model can accurately represent real dynamics of the electrified vehicle tested on the chassis dynamometer; 2) smooth transitions can be guaranteed after implementing the MFC model in microsimulation; 3) when predicting the on-road driving trajectories, the MFC model can deliver significant reductions in speed (~69 %) and acceleration (~50 %) root-square-mean errors (RMSEs) compared with benchmarks; 4) MFC model can accurately predict the vehicle 0-100 km/h acceleration specifications, where its RMSE is 49.4 % and 56.8 % lower than those of Gipps and IDM models, respectively. ; JRC.C.4-Sustainable Transport


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    Title :

    Introducing Electrified Vehicle Dynamics in Traffic Simulation


    Contributors:

    Publication date :

    2020-05-14


    Type of media :

    Miscellaneous


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    DDC:    629



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