Energy Management of Hydrogen Hybrid Electric Vehicles—Online-Capable Control
Energies(2024)
摘要
The results shown in this paper extend our research group’s previous work, which presents the theoretically achievable hydrogen engine-out NOxeo (H2-NOxeo) Pareto front of a hydrogen hybrid electric vehicle (H2-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 H2-HEV with explicit consideration of the H2-NOxeo 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 NOxeo. In a case study, it is shown that MPC is able to satisfy user-defined NOxeo 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 NOxeo target on four realistic routes for passenger cars.
更多查看译文
关键词
hydrogen internal combustion engine,hybrid electric vehicles,H<sub>2</sub>-NO<named-content content-type="inline-formula"><inline-formula> <mml:math id="mm10001"> <mml:semantics> <mml:msubsup> <mml:mtext></mml:mtext> <mml:mi mathvariant="normal">x</mml:mi> <mml:mi>eo</mml:mi> </mml:msubsup> </mml:semantics> </mml:math> </inline-formula></named-content> trade-off,extremely low NO<named-content content-type="inline-formula"><inline-formula> <mml:math id="mm10101"> <mml:semantics> <mml:msubsup> <mml:mtext></mml:mtext> <mml:mi mathvariant="normal">x</mml:mi> <mml:mi>eo</mml:mi> </mml:msubsup> </mml:semantics> </mml:math> </inline-formula></named-content>,energy management
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要