scholarly journals Sizing Procedure for System Hybridization Based on Experimental Source Modeling for Electric Vehicles

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5275
Author(s):  
Aaron Shmaryahu ◽  
Nissim Amar ◽  
Alexander Ivanov ◽  
Ilan Aharon
Keyword(s):  
Fuel Cell ◽  
Real Time ◽  
Energy Management ◽  
Management System ◽  
Target Function ◽  
Proton Exchange ◽  
Energy Management System ◽  
Hydrogen Fuel Cell ◽  
Source Modeling ◽  
Mission Profile

Hybrid vehicles are now more common in response to increasing global warming. The hybridization of energy sources and energy storage units enables improving the sustainability, reliability, and robustness of power systems. To reach the objective of zero emissions, a proton exchange membrane hydrogen fuel-cell was utilized as an energy source. The aim of this research was to create an accurate optimal sizing procedure for determining the nominal rating of the necessary sources. We modeled the fuel cell and the battery pack using data from real experimental results to create the generic database. Then, we added data on the mission profile, system constraints, and the minimization target function. The mission profile was then analyzed by the sizing algorithm to determine optional minimum and maximum fuel cell ratings. Analyzing the optional solutions using the vehicle real time energy management system controller resulted in a set of solutions for each available rated fuel cell, and the optimal compatible battery in the revealed band successfully accomplished the route of the driving cycle within the system limitations. Finally, the Pareto curve represented the optimal finding of the sizing procedure. Ultimately, in contrast to previous works that utilize gross manufacturer data in the sizing procedure, the main research contribution and novelty of this research is the very accurate sizing results, which draw on real experimental-based fuel-cell and battery sizing models. Moreover, the actual vehicle real time energy management system controllers were used in the sizing procedure.

scholarly journals Sizing Procedure for System Hybridization Based on Experimental Source Modeling in Grid Application

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4685
Author(s):  
Nissim Amar ◽  
Arron Shmaryahu ◽  
Michael Kolleti ◽  
Ilan Aharon
Keyword(s):  
Energy Source ◽  
Real Time ◽  
Energy Management ◽  
Management System ◽  
Target Function ◽  
Energy Management System ◽  
Source Modeling ◽  
System Controller ◽  
And Storage ◽  
Mission Profile

Hybridization of sources is spreading worldwide by utilizing renewable sources and storage units as standard parts of every grid. The conjunction of energy source and storage type open the door to reshaping the sustainability and robustness of the mains while improving system parameters such as efficiency and fuel consumption. The solution fits existing networks as well as new ones. The study proposes the creation of an accurate optimal sizing procedure for setting the required rating of each type of source. The first step is to model the storage and energy sources by using real experimental results for creating the generic database. Then, data on the mission profile, system constraints, and the minimization target function are inserted. The mission profile is then analyzed to determine the minimum and maximum energy source rating. Next, the real time energy management system controller is used to find the set of solutions for each available energy source and the optimal compatible storage in the revealed band to fulfil the mission task. A Pareto-curve is then plotted to present the optimal findings of the sizing procedure. Ultimately, the main research contribution is the far more accurate sizing results. A case study shows that relying on the standard method leads to noncompliance of sizing constraints, while the proposed procedure leads to fulfilling the mission successfully. First, by utilizing experimentally based energy and a storage unit. Second, by using the same real time energy management system controller in the sizing procedure.

scholarly journals Modelling and Design of Real-Time Energy Management Systems for Fuel Cell/Battery Electric Vehicles

Energies ◽  
2019 ◽  
Vol 12 (22) ◽  
pp. 4260 ◽  
Author(s):  
Alessandro Serpi ◽  
Mario Porru
Keyword(s):  
Fuel Cell ◽  
Cost Function ◽  
Real Time ◽  
Energy Management ◽  
Management System ◽  
Operating Cost ◽  
Management Systems ◽  
Energy Management System ◽  
Energy Management Systems ◽  
Battery Degradation

Modelling and design of real-time energy management systems for optimising the operating costs of a fuel cell/battery electric vehicle are presented in this paper. The proposed energy management system consists of optimally sharing the propulsion power demand between the fuel cell and battery by enabling them to support each other for operating cost minimisation. The optimisation is achieved through real-time minimisation of a cost function, which accounts for fuel cell and battery degradation, hydrogen consumption and charge sustaining costs. A detailed analysis of each term of the overall cost function is performed and presented, which enables the development of a real-time, advanced energy management system for improving a previously presented simplified version using more accurate modelling and by considering cost function minimisation over a given time horizon. The performance of the proposed advanced energy management system are verified through numerical simulations over different driving cycles; particularly, simulations were performed in MATLAB-Simulink by considering a hysteresis-based energy management system and both simplified and advanced versions of the proposed energy management system for comparison.

scholarly journals Integrated Renewable Energy Management System for Reduced Hydrogen Consumption using Fuel Cell

2021 ◽  
Vol 3 (1) ◽  
pp. 44-54
Author(s):  
Vivekanadam B ◽  
Karuppusamy P.
Keyword(s):  
Fuel Cell ◽  
Energy Management ◽  
Management System ◽  
Power Source ◽  
Proton Exchange ◽  
Energy Management System ◽  
Multiple Control ◽  
Hydrogen Consumption ◽  
Hybrid Power ◽  
Surplus Power

The hybrid energy sources and their behavior may be controlled by monitoring and sensing with the help of a single or multiple control strategies incorporated in the energy management system. Utilization of the battery state of charge (SOC) and reduction in the consumption of hydrogen are the main objectives of battery and fuel cell (FC) based renewable hybrid power systems. The lifespan of the hydrogen storage as well as battery may be improved while improving the cost reduction benefits using these parameters. These objectives are achieved by designing an integrated energy management system (IEMS). A battery, supercapacitor (SC), proton-exchange membrane fuel cell (PEMFC) and Photovoltaic (PV) cell are combined to provide the required power to a predetermined load to form a renewable hybrid power system (RHPS). During daylight, PV is the master power source in RHPS. During the shading or night time, FC is the secondary power source. When high load power is required, the FC is supported by the battery. Load fast change or load transient operation is performed by the SC. Maximum SOC value and minimum hydrogen consumption value is obtained simultaneously based on predetermined functions that aids in switching between the state machine control, frequency decoupling and fuzzy logic based integrated strategies in the proposed energy management model. When compared to the stand-alone strategies, the integrated model achieves increased SOC and reduced hydrogen consumption. When maximum value of PV power is attained, the surplus power is displayed at the load. The battery is charged using this surplus power. The stand-alone strategies and integrated strategy results are compared. The attainment of the goal of IEMS is confirmed from this comparison.

Hybrid Fuel Cell/Battery Intelligent Energy Management system for UAV

2020 ◽  
Author(s):  
Mohamed Sameh Elkerdany ◽  
Ibrahim Mohamed Safwat ◽  
Ahmed Medhat Mohamed Yossef ◽  
Mohamed M. Elkhatib
Keyword(s):  
Fuel Cell ◽  
Energy Management ◽  
Management System ◽  
Energy Management System
Sign in / Sign up

Export Citation Format

Share Document