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A stochastic energy aware routing framework is proposed for electric vehicles with the goal of enhancing the sustainability of future electrified transportation systems. A stochastic decision making framework is introduced to handle the random effects of environmental factors on transportation energy cost. The problem of optimal routing is formulated as a stochastic programming problem and risk control of the overall energy is applied to find the minimum energy route. The original discrete optimization problem is tackled using convex relaxation and transformation. The optimal path is constructed using a highly efficient primal-dual interior point algorithm for the relaxed problem with a subsequent reconstruction of the solution for the original discrete problem. Two electric drive limitations, i.e., battery capacity and drive line efficiency, are made an integral part of the decision making framework in order to obtain realistic results by incorporating actual vehicle data. Detailed simulations demonstrate the utility of the introduced approach and its superiority to existing, traditional routing engines.
Yi et al. (Tue,) studied this question.
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