Robust optimization based energy management of a fuel cell/ultra-capacitor hybrid electric vehicle under uncertainty
Mariem Smaoui and
Energy, 2020, vol. 200, issue C
This paper investigates the energy management of a fuel cell/ultra-capacitor hybrid electric vehicle (FCHEV) under uncertainty. In addition to fuel economy and fuel cell (FC) system slow dynamics, solutions’ robustness is also considered as a key performance criterion. As previous studies focus on expected optimal performance under a deterministic framework and ignore possible data ambiguity, this paper considers uncertainties affecting power production, conversion and demand levels. Changing operation conditions, modeling and estimation claim several sources of errors. In practice, ignoring such uncertainties leads to high operation cost, poor overall system efficiency, performance failure and even infeasible solutions due to constraints violation. A robust optimization (RO) based energy management system (EMS) is studied in order to ensure optimal yet robust performance under uncertain parameters. The adopted RO based algorithm includes uncertainty in the cost function and constraints set and thus protects the system performance from feasibility and optimality issues. As RO approach is considered over conservative, conservatism level parameters are introduced to enable more flexible decision making and performance cost. Three different optimization case studies, namely classical deterministic, complete robust and variable conservatism level were investigated in order to assess the performance of the proposed approach.
Keywords: Electric vehicle; Energy management system; Optimization under uncertainty; Robust optimization (search for similar items in EconPapers)
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