The promotion of electric vehicles (EVs) has been regarded as a way to significantly reduce carbon emissions and achieve energy saving. However, the limited cruising mileage of EVs seriously affects the experience of users. Therefore, from the perspective of optimisation, to achieve an optimal route planning for all EVs in a city level based on energy consumption analysis becomes a non‐trivial task. In this study, the authorsoptimise the route planning of EVs driving on green waveband (GWB) with the consideration of energy consumption. Specifically, by analysing the impact of parameters such as phase difference, velocity and green split, a GWB‐based energy consumption model is proposed to improve the energy efficiency of EVs in urban traffic scenarios. On the basis of the model, they then develop a multi‐objective route optimisation algorithm to implement a reliable route‐planning strategy. Using extensive simulations, the performance of their proposal is evaluated. Results show that the proposed energy consumption model can reduce energy consumption of EVs and shorten travel time of drivers. Furthermore, the proposed route‐planning strategy achieves a trade‐off between energy consumption and time cost, which provides feasible route advice for drivers.
Drivingon GWB: energy‐efficiency‐driven route optimisation for EVs
IET Intelligent Transport Systems ; 14 , 1 ; 25-35
2020-01-01
11 pages
Article (Journal)
Electronic Resource
English
telecommunication network routing , energy conservation , energy efficiency , energy‐efficiency‐driven route optimisation , optimal route planning , feasible route advice , energy consumption , road traffic , reliable route‐planning strategy , traffic engineering computing , GWB‐based energy consumption model , electric vehicles , multiobjective route optimisation algorithm , optimisation , energy consumption analysis
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