Abstract

To mitigate the range anxiety problem of electric bus system, wireless power transfer is regarded as one of the emerging technologies for long-term range extension. Previous studies have discussed the optimization problem of the power track deployment. However, the en-route charging strategy also significantly influences the operation cost besides the power track, which is yet to be investigated sufficiently. To fill this gap, a new wireless charging model for optimizing the energy cost is proposed. In particular, the cost of battery and the time-of-use electricity price are taken into account. Firstly, a microscopic power consumption model considering passenger flows and automobile dynamics is developed to estimate the charging cost. Then, a relaxation approach based on penalty function and grey wolf optimization (GWO) algorithm is developed to solve the non-deterministic polynomial-hard (NP-hard) problem with complex multidimensional variables and multiple inequality constraints. And the performance of the proposed charging strategy is verified in a real-world bus line via numerical simulation. A sensitivity analysis is conducted to quantify the marginal impact of the unit cost of battery capacity on the total energy cost. Finally, the computational performance of the proposed algorithm (GWO) is validated by comparing other outstanding methods such as genetic algorithm (GA), particle swarm optimization (PSO) and CPLEX solvers.

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