Bi-level convex optimization of eco-driving for connected Fuel Cell Hybrid Electric Vehicles through signalized intersections

Bo Liu, Chao Sun, Bo Wang, Weiqiang Liang, Qiang Ren, Junqiu Li and Fengchun Sun

Energy, 2022, vol. 252, issue C

Abstract: Eco-driving for connected Fuel Cell Hybrid Electric Vehicles (FCHEVs) is a coupled problem of speed planning and energy management. To reduce the computational burden, bi-level optimization decouples and hierarchically solves the upper-level and lower-level subproblems. This paper proposes a bi-level convex approach for eco-driving of a connected FCHEV proceeding through multiple signalized intersections. On the upper level, the non-linear traffic light constraints are transformed into time-varying linear state constraints and the cost function becomes quadratic after using the average speed. On the lower level, model convexification is carried out for the fuel cell system and battery. Then the upper-level speed planning and lower-level energy management are sequentially solved by the MOSEK solver and the Alternating Direction Method of Multipliers (ADMM) algorithm. The results show that the proposed bi-level convex approach greatly reduces the computational cost while maintaining high energy efficiency, with only 6.59% computational time and almost the same fuel economy compared to the bi-level Dynamic Programming (DP) method.

Keywords: Eco-driving; Energy management; Bi-level convex optimization; Fuel cell hybrid electric vehicle; Signalized intersection (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:252:y:2022:i:c:s0360544222008593

DOI: 10.1016/j.energy.2022.123956

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