With the advancement of vehicle‐to‐vehicle and vehicle‐to‐infrastructure technologies, more and more real‐time information regarding traffic and transportation system will be available to vehicles. This paper presents the development of a novel algorithm that uses available velocity bounds and powertrain information to generate an optimal velocity trajectory over a prediction horizon. When utilised by a vehicle, this optimal velocity trajectory reduces fuel consumption. The objective of this optimisation problem is to reduce dynamic losses, required tractive force, and completing trip distance with a given travel time. Sequential quadratic programming method is employed for this nonlinearly constrained optimisation problem. When applied to a GM Volt‐2, the generated velocity trajectory saves fuel compared to a real‐world drive cycle. The simulation results confirm the fuel consumption reduction with the rule‐based mode selection and the energy management strategy of a GM Volt 2 model in Autonomie.


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