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Energy Management Strategy of Fuel Cell/Battery Hybrid Vehicle Based on Series Fuzzy Control

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Abstract

Fuel cell durability and vehicle operating cost are the main optimization goals of energy management strategy (EMS) for fuel cell hybrid electric vehicles (FCHEV). In this paper, a series fuzzy control strategy (SFCS) is proposed to decrease the load changing rate of fuel cell system (FCs). The test bench is used to obtain the output characteristics and load changing capacity of FCs. In order to increase the driving mileage and to eliminate the uncertainty of manual experience in fuzzy controller, particle swarm optimization (PSO) is used to optimize the subjection function distribution and rule weights of fuzzy control, and the evaluation function is constructed by operating cost. Based on the experiment data of FC and battery, the model of the vehicle and strategy are constructed in the software environment, and the optimization result is obtained through simulation. The results show that the FCs load changing rate is reduced and limited to the range of change capacity through the SFCS, while the durability of the fuel cell is optimized. The SFCS optimized by PSO (PSFCS) increases the driving mileage. Under WLTC and UDDS conditions, mileage has been increased by 11.2 % and 8.79 % respectively.

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Abbreviations

A :

windward area

a :

vehicle acceleration rate

C r :

rolling resistance coefficient

C d :

Wind bound coefficient

C bat :

battery capacity

C fc :

the price of fuel cell system

C ele :

the price of electricity

\({C_{{H_2}}}\) :

the price of hydrogen

\(co{n_{{H_2}}}\) :

hydrogen capacity

SFCS:

series fuzzy control strategy

D fc :

the degradation of fuel cell

\(D_{fc}^ \ast \) :

the degradation of fuel cell system in this paper

F t :

traction force

F :

faraday constant

FCS :

fuzzy control strategy

I fc :

the output current of fuel cell system

I cell :

the output current of single cell

I req :

current demand

m fc :

system instantaneous hydrogen consumption rate

\({M_{{H_2}}}\) :

hydrogen molar mass

N :

the number of single cells

N com :

torque command

P req :

power demand

P mec :

mechanical power

P ele :

electric power

P fc :

the output power of fuel cell system

P bat :

the output power of battery

P lost :

the lost power of motor

PSO :

particle swarm optimization

PSFCS :

the SFCS optimized by PSO

Q LHV :

hydrogen low heating value

Q bat :

the capacity of battery

P bat :

the internal resistance of battery

S inl :

the evaluation index of PSO

SOC :

the state of charge of battery

U oc :

the open voltage of battery

V mot :

the rotary velocity of motor

V :

vehicle speed

θ :

road slope

δ m :

rotary mass coefficient

η fc :

the efficiency of fuel cell system

η mat :

the efficiency of motor

ρ :

air density

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Acknowledgement

This work was supported by Senior Talent Fund through the Jiangsu University (20JDG069)

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Authors and Affiliations

  1. School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang, 212013, China

    Hekun Jia, Jiexu Tang, Yingxiao Yu, Yan Sun & Bifeng Yin

  2. Technique Center, Foresight Energy Co., Ltd., Shansong Road, National High-tech Zone, Suzhou, 215000, China

    Chao Zhang

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  1. Hekun Jia
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  2. Jiexu Tang
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  4. Yan Sun
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  5. Bifeng Yin
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Correspondence to Yingxiao Yu.

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Jia, H., Tang, J., Yu, Y. et al. Energy Management Strategy of Fuel Cell/Battery Hybrid Vehicle Based on Series Fuzzy Control. Int.J Automot. Technol. 22, 1545–1556 (2021). https://doi.org/10.1007/s12239-021-0133-0

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  • DOI: https://doi.org/10.1007/s12239-021-0133-0

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