ABSTRACT
In order to maintain the battery SOC, the fuel cell power will fluctuate dramatically, as well as frequent start-stop, which will greatly increase the life attenuation of the fuel cell and reduce the durability. An optimization-based energy management strategy with a real-time model predictive control and pontryagin’s maximum principle for FCHEV is proposed in this paper, both the fuel economy and the fuel cell durability are considered in the optimization. A novel model predictive control is studied to achieve energy distribution. After the calculation of predicted speed sequence through back propagation neural network, pontryagin’s maximum principle is introduced to solve the optimal control problem in each prediction horizon and obtain the ideal control strategy. In addition, the fuel cell degradation model is introduced in the modeling process, the minimum power point of the fuel cell system is designed to improve the fuel economy and durability of the fuel cell. Compared with the rule-based strategy, the proposed MPC strategy has better performance to reduce the total equivalent hydrogen consumption, which can save up to 8.44% in the test case of the mid-size fuel cell passenger car while maintaining the stability of the battery’s state of charge.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Nomenclature
FCHEV | = | Fuel cell hybrid electric vehicle |
HEV | = | Hybrid electric vehicle |
FCS | = | Fuel cell system |
EMS | = | Energy management strategy |
SOC | = | State of charge |
DP | = | Dynamic programming |
GA | = | Genetic algorithm |
ECMS | = | Equivalent consumption minimum strategy |
PMP | = | Pontryagin’s maximum principle |
MPC | = | Model predictive control |
BPNN | = | Back Propagation Neural Network |
Ftrac | = | The total required vehicle driving force |
g | = | The gravity constant |
f | = | The rolling coefficient |
CD | = | The Aerodynamic coefficient |
A | = | The front surface of the vehicle |
ρ | = | The air density |
Ptrac | = | The total driving power |
Pd | = | The demand power |
ηDC/AC | = | The efficiency of the DC/AC converter |
ηMG | = | The efficiency of the motor system |
Pfc | = | The output power of the fuel cell system |
Pb | = | The output power of the battery |
ηDC/DC | = | The efficiency of the DC/DC converter |
= | The hydrogen consumption rate | |
ηfc | = | The efficiency of the fuel cell system |
LHV | = | The lower heating value of hydrogen (120 kJ/g) |
Lde | = | The fuel cell lifetime degeneration rate |
Con-off | = | The fuel cell degeneration due to start-stop cycle |
Clow | = | The fuel cell degeneration due to low load |
Cch | = | The fuel cell degeneration due to load change |
Chigh | = | The fuel cell degeneration due to heavy load |
Non-off | = | The number of times the fuel cell completes the entire start-stop cycle |
Tlow | = | The length of time the fuel cell is under low load |
Thigh | = | The length of time the fuel cell is under heavy load |
ΔPfc | = | The power change of the fuel cell per second |
Pfc,low | = | The low load power threshold of the fuel cell |
Pfc,high | = | The heavy load power threshold of the fuel cell |
Cb | = | The battery capacity |
Ib | = | The battery current |
R | = | The internal resistance of the battery |
VOC | = | The open-circuit voltage |
ηMG | = | The efficiency of the motor |
TMG | = | The output torque of the motor |
ωMG | = | The output speed |
Hp | = | The length of the prediction horizon |
= | The hydrogen consumption rate | |
p | = | The weighting coefficient for restraining FC power change |
λ(t) | = | The co-state |
Hh | = | The length of the historical velocity sequence |
fN | = | The nonlinear mapping function predicted by the neural network |
mfc | = | The equivalent hydrogen consumption of the fuel cell degradation |
Lde,max | = | The maximum allowable degradation rate of the fuel cell stack |
αfc | = | The price of the fuel cell stack (USD/kw) |
αH2 | = | The price of hydrogen (USD/kg) |
ΔSOC | = | The rate of change of battery SOC |
E | = | The energy capacity of the fuel cell (3.2kwh) |
mfc,ch | = | The equivalent hydrogen consumption of the fuel cell degradation due to load change |
mfc,low | = | The equivalent hydrogen consumption of the fuel cell degradation due to low load |
mfc,high | = | The equivalent hydrogen consumption of the fuel cell degradation due to heavy load |
mfc,on-off | = | The equivalent hydrogen consumption of the fuel cell degradation due to start-stop cycle |