Research on multi-energy management system of fuel cell vehicle based on fuzzy control

2020 ◽  
pp. 1-13
Author(s):  
Wenguang Li ◽  
Guosheng Feng ◽  
Sumei Jia
Keyword(s):  
Fuel Cells ◽  
Fuel Cell ◽  
Fuzzy Control ◽  
Energy Management ◽  
Management Strategy ◽  
Fuzzy Controller ◽  
Particle Swarm ◽  
Energy Management Strategy ◽  
Hydrogen Consumption ◽  
Super Capacitors

This paper studies a hybrid power system composed of fuel cells, super capacitors and batteries. Super capacitors are used as auxiliary energy sources to provide the required high power when the car starts and accelerate, while absorbing braking energy when the car is braking. Fuzzy control is used to optimize its energy management strategy. The fuzzy controller of the three-energy source system takes the battery, super capacitor, and bus demand power as the input of the fuzzy controller, and the battery demand power and the fuel cell demand power as the fuzzy controller output. The system realizes the energy distribution of super capacitors, fuel cells and storage batteries according to power requirements, thereby improving the performance of the system and extending the life of components. And with hydrogen consumption as the optimization goal, the particle swarm algorithm is used to optimize the parameters of the fuzzy membership function. Compared with the fuzzy control strategy without particle swarm optimization, the optimized fuzzy energy management strategy reduces the hydrogen consumption of fuel cell vehicles. 10 L/(100 km)-1, which improves the economy of the vehicle.

scholarly journals Multi-objective Parameters Optimization for HEV Based on improved Particle Swarm Algorithm

2019 ◽  
Vol 118 ◽  
pp. 02005
Author(s):  
Ying Ai ◽  
Yuanjie Gao ◽  
dongsheng Liu
Keyword(s):  
Electric Vehicle ◽  
Energy Management ◽  
Fuel Economy ◽  
Management Strategy ◽  
Hybrid Electric Vehicle ◽  
Fuzzy Controller ◽  
Particle Swarm ◽  
Particle Swarm Algorithm ◽  
Energy Management Strategy ◽  
Multi Objective

Hybrid electric vehicle fuel consumption and emissions are closely related to its energy management strategy. A fuzzy controller of energy management using vehicle torque request and battery state of charge (SOC) as inputs, engine torque as output is designed in this paper foe parallel hybrid electric vehicle. And a multi-objective mathematical function which purpose on maximize fuel economy and minimize emissions is also established, in order to improve the adaptive ability and the control precision of basic fuzzy controller, this paper proposed an improved particle swarm algorithm that based on dynamic learning factor and adaptive inertia weight to optimize the control parameters. Simulation results based on ADVISOR software platform show that the optimized energy management strategy has a better distribution of engine and motor torque, which helps to improved the vehicle’s fuel economy and exhaust emission performance.

scholarly journals Optimization Analysis of the Energy Management Strategy of the New Energy Hybrid 100% Low-Floor Tramcar Using a Genetic Algorithm

2018 ◽  
Vol 8 (7) ◽  
pp. 1144 ◽  
Author(s):  
Minggao Li ◽  
Ming Li ◽  
Guopeng Han ◽  
Nan Liu ◽  
Qiumin Zhang ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Fuel Cell ◽  
Energy Management ◽  
Management Strategy ◽  
Maximum Output Power ◽  
Maximum Output ◽  
Energy Management Strategy ◽  
Super Capacitor ◽  
Power Requirement ◽  
Hydrogen Consumption

Performance and economic efficiency of the fuel cell (FC)/battery/super capacitor (SC) hybrid 100% low-floor tramcar is mainly determined by its energy management strategy. In this paper, a train traction model was built to calculate the power output and energy consumption properties of the hybrid tramcar. With the purpose of reducing hydrogen consumption, the genetic algorithm was adopted to optimize the original energy management strategy. The results before and after the optimization show that the power requirement of the tramcar can be satisfied in both situations with the fuel cell (FC) module non-stopped. The maximum output power of the FC is reduced from 170 kW to 101.21 kW. As for the SC, a two-parallel connection module is used instead of the three-parallel one, and the power range changes from −125~250 kW to −67~153 kW. Under the original energy management strategy, the battery cannot be used efficiently with less exporting and absorbent power. Its utilization ratio is improved greatly after optimization. In sum, the equivalent total hydrogen consumption is reduced from 3.3469 kg to 2.8354 kg, dropping by more than 15%.

scholarly journals Energy Management of a Multi-Source Vehicle by λ-Control

2020 ◽  
Vol 10 (18) ◽  
pp. 6541
Author(s):  
Ali Castaings ◽  
Walter Lhomme ◽  
Rochdi Trigui ◽  
Alain Bouscayrol
Keyword(s):  
Energy Storage ◽  
Fuel Cell ◽  
Real Time ◽  
Energy Management ◽  
Management Strategy ◽  
Storage System ◽  
Energy Storage System ◽  
Energy Management Strategy ◽  
The Real ◽  
Hydrogen Consumption

This paper deals with the real-time energy management of a fuel cell/battery/supercapacitors energy storage system for electric vehicles. The association of the battery and the supercapacitors with the fuel cell aims to reduce the hydrogen consumption while limiting the constraints on the fuel cell and the battery. In this paper, a real-time optimization-based energy management strategy by λ-control is proposed. Simulation results on a standard driving cycle show that the hydrogen consumption is reduced by 7% in comparison with a fuel-cell-based electric vehicle without any secondary energy storage source. Moreover, the energy management strategy ensures the system safety while preserving the fuel cell and the battery. Experimental results show that the developed energy management strategy is well-suited for the real-time requirements, applicability, and safety.

scholarly journals Novel Fuzzy Control Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles Considering State of Health

Energies ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6481
Author(s):  
Xiao Hu ◽  
Shikun Liu ◽  
Ke Song ◽  
Yuan Gao ◽  
Tong Zhang
Keyword(s):  
Genetic Algorithm ◽  
Fuel Cell ◽  
Fuzzy Control ◽  
Energy Management ◽  
Electric Vehicles ◽  
Cell Hybrid ◽  
Hybrid Electric Vehicles ◽  
Fuzzy Controller ◽  
Rule Based ◽  
Hydrogen Consumption

Due to the low efficiency and high pollution of conventional internal combustion engine vehicles, the fuel cell hybrid electric vehicles are expected to play a key role in the future of clean energy transportation attributed to the long driving range, short hydrogen refueling time and environmental advantages. The development of energy management strategies has an important impact on the economy and durability, but most strategies ignore the aging of fuel cells and the corresponding impact on hydrogen consumption. In this paper, a rule-based fuzzy control strategy is proposed based on the constructed data-driven online estimation model of fuel cell health. Then, a genetic algorithm is used to optimize this fuzzy controller, where the objective function is designed to consider both the economy and durability by combining the hydrogen consumption cost and the degradation cost characterized by the fuel cell health status. Considering that the rule-based strategy is more sensitive to operating conditions, this paper uses an artificial neural network for predictive control. The results are compared with those obtained from the genetic algorithm optimized fuzzy controller and are found to be very similar, where the prediction accuracy is assessed using MAPE, RMSE and 10-fold cross-validation. Experiments show that the developed strategy has a good generalization capability for variable driving cycles.

scholarly journals Energy management strategy based on dynamic programming with durability extension for fuel cell hybrid tramway

2021 ◽  
Vol 29 (3) ◽  
pp. 299-313
Author(s):  
Shiyong Tao ◽  
Weirong Chen ◽  
Rui Gan ◽  
Luoyi Li ◽  
Guorui Zhang ◽  
...  
Keyword(s):  
Dynamic Programming ◽  
Fuel Cell ◽  
Real Time ◽  
Energy Management ◽  
Power Distribution ◽  
Management Strategy ◽  
High Efficiency ◽  
State Machine ◽  
Energy Management Strategy ◽  
Hydrogen Consumption

AbstractThis paper proposes an energy management strategy for a fuel cell (FC) hybrid power system based on dynamic programming and state machine strategy, which takes into account the durability of the FC and the hydrogen consumption of the system. The strategy first uses the principle of dynamic programming to solve the optimal power distribution between the FC and supercapacitor (SC), and then uses the optimization results of dynamic programming to update the threshold values in each state of the finite state machine to realize real-time management of the output power of the FC and SC. An FC/SC hybrid tramway simulation platform is established based on RT-LAB real-time simulator. The compared results verify that the proposed EMS can improve the durability of the FC, increase its working time in the high-efficiency range, effectively reduce the hydrogen consumption, and keep the state of charge in an ideal range.

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

2021 ◽  
Vol 22 (6) ◽  
pp. 1545-1556
Author(s):  
Hekun Jia ◽  
Jiexu Tang ◽  
Yingxiao Yu ◽  
Yan Sun ◽  
Bifeng Yin ◽  
...  
Keyword(s):  
Fuel Cell ◽  
Fuzzy Control ◽  
Energy Management ◽  
Management Strategy ◽  
Hybrid Vehicle ◽  
Energy Management Strategy
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