Abstract
Electric vehicles tend to be a great mobility option for the potential benefits in energy consumption and emission reduction. On-way charging (OWC) has been recognized to be a promising solution to extend driving range for electric vehicles. Location of the electrification road (ER) is a critical issue for future urban traffic management to accommodate the new mobility option. This paper proposes a mathematical program with equilibrium constraint (MPEC) approach to solve this problem, which minimizes the total travel time with a limited construction budget. To describe the drivers’ routing choice, a path-constrained network equilibrium model is proposed to minimize their travel time and prevent running out of charge. We develop a modified active set algorithm to solve the MPEC model. Numerical experiments are presented to demonstrate the performance of the model and the solution algorithm and analyze the impact of charging efficiency, battery size, and comfortable range.
Highlights
Electrification systems based on renewable energy power sources are introduced in the urban transportation system for positive environmental effect and carbon reduction [1, 2]
on-way charging (OWC) provides a new mode of charging for electric vehicles (EVs) drivers to extend driving range, who are suffering from range anxiety of running out of power on the way [9, 10] and long charging time ranging from 0.5 to 2 hours for a full charge [11]
Assuming that the energy consumption rate and recharging rate are flow-independent, this paper proposes a path-constrained network equilibrium model (PCNE) considering the routing and recharging behavior of EV drivers as well as the constraint of driving range
Summary
Electrification systems based on renewable energy power sources are introduced in the urban transportation system for positive environmental effect and carbon reduction [1, 2]. Jiang et al [16] first proposed a path-constrained assignment model where lengths of selected routes are within the driving ranges of EVs. e model is further extended to consider mixed gasoline and electric vehicle flows and their combined routing choices under different problem settings [17, 18] He et al investigated the optimal prices of electricity and the integrated prices of electricity and roads based on the multiclass spatial distribution of electric vehicles across the transportation network [19, 20]. Assuming that the energy consumption rate and recharging rate are flow-independent, this paper proposes a path-constrained network equilibrium model (PCNE) considering the routing and recharging behavior of EV drivers as well as the constraint of driving range. Adopting multipliers associated with the constraints forcing nonnegative variables to be zero, the proposed algorithm formulates the binary knapsack problem to solve the zero-value assignments to decrease the total travel time. If the optimal objective value is zero, (Ωη0, Ωη1) is the best solution and the iteration ends; If not, Obtain derive a new (gij, hij)) solution and the objective to (Ωη0+1, Ωη1+1): value
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