| OPTIMAL ENERGY DISTRIBUTION OF MULTI-ENERGY SOURCES IN
FUEL-CELL ELECTRIC BUS USING LONG SHORT-TERM MEMORY |
| Giyeon Hwang 1, Seunghyup Shin 2, Sangyul Lee 3, Minjae Kim 1 |
1Department of Mechanical Engineering, Myongji University
2Department of Artificial Intelligence, Sejong University
3Division of Mechanical and Electronics Engineering, Hansung University |
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| ABSTRACT |
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ABSTRACT–overcome these
problems, the automobile industry is prioritizing the development of eco-friendly vehicles that reduce greenhouse gas emissions.
Among these, fuel-cell electric vehicles (FCEVs) use hydrogen as a fuel and do not emit exhaust gas and their higher mileage
and shorter fuel charging time compared to electric vehicles make them promising next-generation eco-friendly vehicles.
However, conventional energy management strategies have not effectively implemented both real-time capability and optimal
energy distribution in FCEVs. To address these issues, a powertrain utilizing multi-energy sources is utilized, and a real-time
energy control strategy based on long short-term memory (LSTM) is proposed. The training data for LSTM is obtained from
the results of dynamic programming, utilizing six-city bus driving cycles, and the Braunschweig city driving cycle is chosen
for test simulation. As a result, the LSTM prediction performance is evaluated, resulting in the development of an effective
algorithm for real-time energy management of multi-energy sourced FCEVs. |
| Key Words:
Fuel-cell electric bus, Ultra-capacitor, Dynamic programming, Long short-term memory, Energy
management strategy, Hybrid energy storage system |
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Corresponding Author.
Minjae Kim , Email. 
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