Application of State Transition Energy Management Control Algorithm in Fuel Cell

2021 ◽  
Author(s):  
Zheng Pan ◽  
Qihong Xiao ◽  
Yangliang Chen
Keyword(s):  
Fuel Cell ◽  
Energy Management ◽  
State Transition ◽  
Motor Vehicle ◽  
Transition Energy ◽  
Simulation Software ◽  
Management Control ◽  
Hydrogen Consumption ◽  
Management Algorithm ◽  
Battery Energy

Dynamic programming algorithms are widely used in motor vehicle fuel cells, and can help battery energy management control to perform error analysis. The paper designs the decision-making process of fuel cell charge and discharge management based on the state transition energy management algorithm, which is used to analyse the cumulative causes of errors and the corresponding results. The article uses simulation software to simulate the algorithm proposed in this paper, and finds that the algorithm is an energy management optimization decision, and the error of the hydrogen consumption obtained by the algorithm relative to the theoretical optimal hydrogen consumption is less than 0.25%.

scholarly journals Energy Management Control of Fuel Cell Electric Bus Basing on Fuzzy Rule

2021 ◽  
Vol 2002 (1) ◽  
pp. 012073
Author(s):  
Renguang Wang ◽  
Dong Hao ◽  
Yanyi Zhang ◽  
Xiangfei Meng
Keyword(s):  
Fuel Cell ◽  
Energy Management ◽  
Fuzzy Rule ◽  
Management Control ◽  
Electric Bus

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 An Energy Management System for Residential Autonomous DC Microgrid Using Optimized Fuzzy Logic Controller Considering Economic Dispatch

Energies ◽  
2019 ◽  
Vol 12 (8) ◽  
pp. 1457 ◽  
Author(s):  
Shehab Al-Sakkaf ◽  
Mahmoud Kassas ◽  
Muhammad Khalid ◽  
Mohammad A. Abido
Keyword(s):  
Fuzzy Logic ◽  
Energy Storage ◽  
Fuel Cell ◽  
Wind Turbine ◽  
Energy Management ◽  
Fuzzy Logic Controller ◽  
Economic Dispatch ◽  
Energy Management System ◽  
Battery Energy Storage ◽  
Battery Energy

This work presents the operation of an autonomous direct current (DC) DC microgrid for residential house controlled by an energy management system based on low complexity fuzzy logic controller of only 25-rules to manage the power flow that supply house load demand. The microgrid consists of photovoltaic (PV), wind turbine, fuel cell, battery energy storage and diesel generator. The size of the battery energy storage is determined based on the battery sizing algorithm depending on the generation of renewables during all seasons of the year in the eastern region of Saudi Arabia. Two scenarios are considered in this work. In the first scenario: the microgrid consists of solar PV, wind turbine, battery energy storage and fuel cell. The fuzzy logic controller is optimized using an artificial bee colony technique in order to increase the system energy saving efficiency and to reduce the cost. In the second scenario: wind turbine is replaced by a diesel generator, also the rated power of the fuel cell is reduced. In this scenario, a new method is proposed to reduce the generation cost of the dispatchable sources in the microgrid by considering economic dispatch within the optimized fuzzy logic energy management system. To obtain the most suitable technique for solving the economic dispatch problem, three optimization techniques were used which are particle swarm optimization, genetic algorithm and artificial bee colony based on real environmental data and real house load demand. A comparison in terms of energy saving between the two scenarios and a comparison in terms of cost reduction between conventional economic dispatch method and the proposed method are presented.

scholarly journals Energy Management in Fuel-Cell\/Battery Vehicles: Key Issues Identified in the IEEE Vehicular Technology Society Motor Vehicle Challenge 2017

2018 ◽  
Vol 13 (3) ◽  
pp. 144-151 ◽  
Author(s):  
Clement Depature ◽  
Samir Jemei ◽  
Loic Boulon ◽  
Alain Bouscayrol ◽  
Neigel Marx ◽  
...  
Keyword(s):  
Fuel Cell ◽  
Energy Management ◽  
Motor Vehicle ◽  
Key Issues ◽  
Vehicular Technology

Energy management strategies for a fuel-cell/battery hybrid power system

2020 ◽  
pp. 095965182095851
Author(s):  
Bachir Bendjedia ◽  
Nassim Rizoug ◽  
Moussa Boukhnifer ◽  
Laid Degaa
Keyword(s):  
Energy Storage ◽  
Fuel Cell ◽  
Energy Management ◽  
Storage System ◽  
Management Strategies ◽  
Lithium Ion ◽  
Boost Converters ◽  
Hybrid Energy ◽  
Hydrogen Consumption ◽  
Hybrid Energy Storage

This article presents a comparative study between the performances of different energy management strategies for hybrid energy storage source supplying electric vehicle. In our case, the hybrid supply is composed of fuel cell as an energy source and lithium-ion batteries as a power buffer. The two storage systems are connected to the DC bus via DC/DC boost converters. The used management strategies influence greatly the hybrid energy storage source performances. For this reason, a new online strategy is developed to improve the fuel consumption and the hybrid source lifetime. The performances (hydrogen consumption and applied stress on each source) of this new strategy are compared with those obtained with literature strategies for 700 km of range. Furthermore, an experimental validation of two online energy management strategies is carried out to validate the simulation results using 1-kW test bench. The experimental results prove that the developed strategy improves hydrogen consumption compared to the frequency strategy and it improves also the lifetime of the hybrid storage system.

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