Estimation of Optimal Energy Consumption for Fuel Cell Vehicle Based on Macroscopic Traffic Dynamics

This paper addresses the estimation problem of the minimum required energy of fuel cell vehicle (FCV) driving through a road link conditioned on the current and future traffic states. The challenge is to estimate driving profile of individual vehicles and obtain the corresponding optimal energy consumption of powertrain. Combining the powertrain model and macroscopic traffic dynamics, the FCV tank-to-traffic energy dissipation model is established. Based on the optimal energy consumption within each road segment solved by dynamic programming, the optimal demand power field is obtained. According to the estimated driving profile, optimal segmental energy consumption (OSEC) is calculated by interpolation of optimal demand power field, whose summation is utilized as the estimator for global optimal accumulative energy consumption (GOAEC). The validation result indicates that the highest Pearson correlation coefficient between the sequence of OSEC and GOAEC reaches 0.86, while in the case of the poorest estimation performance, the sequences share a similar shape. The effective estimator for GOAEC provides the quantified evidence supporting decisions on route planning and velocity planning.