The Multi-Objective Optimization of Powertrain Design and Energy Management Strategy for Fuel Cell–Battery Electric Vehicle

Considering the limited driving range and inconvenient energy replenishment way of battery electric vehicle, fuel cell electric vehicles (FC EVs) are taken as a promising way to meet the requirements for long-distance low-carbon driving. However, due to the limitation of FC power ability, a battery...

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Bibliographic Details
Published in:Sustainability 2022-05, Vol.14 (10), p.6320
Main Authors: Zhou, Jiaming, Feng, Chunxiao, Su, Qingqing, Jiang, Shangfeng, Fan, Zhixian, Ruan, Jiageng, Sun, Shikai, Hu, Leli
Format: Article
Language:English
Subjects:
Algorithms
Artificial intelligence
Carbon
Climbing
Design optimization
Electric vehicles
Energy consumption
Energy efficiency
Energy management
Fuel cells
Fuel technology
Hybridization
Hydrogen
Lifetime
Multiple objective analysis
Neural networks
Optimization
Power flow
Power management
Power sources
Powertrain
Replenishment
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Summary:Considering the limited driving range and inconvenient energy replenishment way of battery electric vehicle, fuel cell electric vehicles (FC EVs) are taken as a promising way to meet the requirements for long-distance low-carbon driving. However, due to the limitation of FC power ability, a battery is usually adopted as the supplement power source to fill the gap between the requirement of driving and the serviceability of FC. In consequence, energy management is essential and crucial to an efficient power flow to the wheel. In this paper, a self-optimizing power matching strategy is proposed, considering the energy efficiency and battery degradation, via implementing a deep deterministic policy gradient. Based on the proposed strategy, less energy consumption and longer FC and battery life can be expected in FC EV powertrain with optimal hybridization degree.
ISSN:2071-1050
2071-1050
DOI:10.3390/su14106320