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access icon free Optimal velocity prediction for fuel economy improvement of connected vehicles

© The Institution of Engineering and Technology
Received 04/04/2018, Accepted 23/07/2018, Revised 19/06/2018, Published 07/09/2018

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.

Inspec keywords: energy management systems; fuel economy; vehicular ad hoc networks; quadratic programming

Other keywords: connected vehicles; optimal velocity prediction; sequential quadratic programming method; powertrain information; Autonomie; velocity bounds; dynamic loss reduction; prediction horizon; energy management; nonlinearly constrained optimisation problem; travel time; vehicle-to-vehicle technology; tractive force requirement; trip distance completion; fuel consumption reduction; vehicle-to-infrastructure technology; rule-based mode selection; traffic system; optimal velocity trajectory generation; transportation system; fuel economy improvement

Subjects: Mobile radio systems; Optimisation techniques; Transportation; Power system management, operation and economics

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