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Optimal Energy Distribution of Multi-Energy Sources in Fuel-Cell Electric Bus Using Long Short-Term Memory

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Abstract

Environmental issues such as air pollution and abnormal climate are global concerns. To 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.

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Abbreviations

F t :

tractive resistance, N

P veh :

required vehicle power, W

P mot,mech :

mechanical motor power, W

P mot,elec :

electrical motor power, W

N mot :

rotational speed of the motor, rad/s

T mot :

torque of the motor, Nm

η mot :

efficiency of the motor

i gear :

efficiency of the gear

R tire :

tire radius, m

V b,oc :

open circuit voltage of the battery, V

V b :

terminal voltage of the battery, V

I b :

current of the battery, A

R b,i :

internal resistance of the battery, ohm

P b :

power of the battery, W

SoC b,init :

initial state of charge of the battery, %

C b :

rated capacity of the battery, Wh

Q init :

initial charge of the capacitor, Q

Q max :

maximum charge of the capacitor, Q

C uc :

rated capacitance of the ultra- capacitor, Wh

I uc :

current of the ultra-capacitor, A

V uc,oc :

open circuit voltage of the ultra-capacitor, V

P uc :

power of the ultra-capacitor, W

P fc :

net power of the fuel cell, W

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Acknowledgement

This work was supported by Myongji University Research Year Grant (from Sep 1, 2022 to Aug 31, 2023) and the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. 2019R1A 2C1090927 and No. 2021R1F1A1063048).

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Authors and Affiliations

  1. Department of Mechanical Engineering, Myongji University, Yongin, 17058, Korea

    Giyeon Hwang & Minjae Kim

  2. Department of Artificial Intelligence, Sejong University, Seoul, 05006, Korea

    Seunghyup Shin

  3. Division of Mechanical and Electronics Engineering, Hansung University, Seoul, 02860, Korea

    Sangyul Lee

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  1. Giyeon Hwang
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  2. Seunghyup Shin
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  3. Sangyul Lee
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  4. Minjae Kim
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Correspondence to Minjae Kim.

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Hwang, G., Shin, S., Lee, S. et al. Optimal Energy Distribution of Multi-Energy Sources in Fuel-Cell Electric Bus Using Long Short-Term Memory. Int.J Automot. Technol. 24, 1359–1367 (2023). https://doi.org/10.1007/s12239-023-0110-x

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