4.7 Article

A real-time PMP energy management strategy for fuel cell hybrid buses based on driving segment feature recognition

Journal

INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
Volume 46, Issue 80, Pages 39983-40000

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ijhydene.2021.09.204

Keywords

Fuel cells; Fuel cell hybrid bus; Energy management strategy; Pontryagin's minimum principle; Driving feature recognition

Funding

  1. National Natural Science Foundation of China [51775082,61976039]

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This paper proposes an optimal energy distribution solution for a fuel cell hybrid bus using the PMP algorithm, addressing issues with inaccurate motor power estimation and real-time application. Experimental results show that the proposed strategy reduces hydrogen consumption by 20.3% to 28.9% compared to rule-based methods, with excellent real-time performance.
Establishing a reasonable energy management strategy (EMS) is the key to improve the service durability, power performance and fuel economy of the fuel cell hybrid electric vehicle (FCHEV). This paper obtains energy distribution optimal solution for the fuel cell hybrid bus (FCHB) based on Pontryagin's minimum principle (PMP) algorithm, and the problems of inaccurate estimation of motor power and difficult real-time application are solved. Firstly, the driving feature recognition is completed by collecting the motor output power directly when the FCHB stops at the station. On the basis of it, the sub-optimal co-state value is chosen. Secondly, the sub-optimal co-state is used to complete the real-time application of PMP algorithm in the driving segment. The results are acquired through the simulation and the actual comparison experiment, compared with rule-based simulation and rule-based actual experiment, the hydrogen consumption of the proposed strategy decreases by 20.3% and 28.9% on average. Moreover, the online computation time per step of the proposed strategy is 3.64 ms averagely, less than sampling time interval 1s. It is shown that the proposed method has lower hydrogen consumption rate and excellent real-time performance. (c) 2021 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

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