Energy Management of Hydrogen Hybrid Electric Vehicles—Online-Capable Control

David Machacek (), Nazim Yasar, Fabio Widmer, Thomas Huber and Christopher Onder ()
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David Machacek: IDSC, ETH Zurich, Sonneggstrasse 3, 8092 Zurich, Switzerland
Nazim Yasar: IDSC, ETH Zurich, Sonneggstrasse 3, 8092 Zurich, Switzerland
Fabio Widmer: IDSC, ETH Zurich, Sonneggstrasse 3, 8092 Zurich, Switzerland
Thomas Huber: Robert Bosch GmbH, 71701 Schwieberdingen, Germany
Christopher Onder: IDSC, ETH Zurich, Sonneggstrasse 3, 8092 Zurich, Switzerland

Energies, 2024, vol. 17, issue 10, 1-25

Abstract: The results shown in this paper extend our research group’s previous work, which presents the theoretically achievable hydrogen engine-out NO ​ x eo (H ​ 2 -NO ​ x eo ) Pareto front of a hydrogen hybrid electric vehicle (H ​ 2 -HEV). While the Pareto front is calculated offline, which requires significant computing power and time, this work presents an online-capable algorithm to tackle the energy management of a H ​ 2 -HEV with explicit consideration of the H ​ 2 -NO ​ x eo trade-off. Through the inclusion of realistic predictive data on the upcoming driving mission, a model predictive control algorithm (MPC) is utilized to effectively tackle the conflicting goal of achieving low hydrogen consumption while simultaneously minimizing NO ​ x eo . In a case study, it is shown that MPC is able to satisfy user-defined NO ​ x eo limits over the course of various driving missions. Moreover, a comparison with the optimal Pareto front highlights MPC’s ability to achieve close-to-optimal fuel performance for any desired cumulated NO ​ x eo target on four realistic routes for passenger cars.

Keywords: hydrogen internal combustion engine; hybrid electric vehicles; H 2 -NO ? x eo trade-off; extremely low NO ? x eo; energy management (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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