A Real-Time Energy Management System for Operating Cost Minimization of Fuel Cell/Battery Electric Vehicles

Author(s):  
Alessandro Serpi ◽  
Mario Porru
Energies ◽  
2019 ◽  
Vol 12 (22) ◽  
pp. 4260 ◽  
Author(s):  
Alessandro Serpi ◽  
Mario Porru

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.


2020 ◽  
Vol 53 (2) ◽  
pp. 14167-14172
Author(s):  
Róbinson Medina ◽  
Zjelko Parfant ◽  
Thinh Pham ◽  
Steven Wilkins

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5275
Author(s):  
Aaron Shmaryahu ◽  
Nissim Amar ◽  
Alexander Ivanov ◽  
Ilan Aharon

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.


Energies ◽  
2019 ◽  
Vol 12 (24) ◽  
pp. 4662 ◽  
Author(s):  
Sadam Hussain ◽  
Muhammad Umair Ali ◽  
Gwan-Soo Park ◽  
Sarvar Hussain Nengroo ◽  
Muhammad Adil Khan ◽  
...  

The energy storage system (ESS) is the main issue in traction applications, such as battery electric vehicles (BEVs). To alleviate the shortage of power density in BEVs, a hybrid energy storage system (HESS) can be used as an alternative ESS. HESS has the dynamic features of the battery and a supercapacitor (SC), and it requires an intelligent energy management system (EMS) to operate it effectively. In this study, a real-time EMS is proposed, which is comprised of a fuzzy logic controller-based low-pass filter and an adaptive proportional integrator-based charge controller. The proposed EMS intelligently distributes the required power from the battery and SC during acceleration. It allocates the braking energy to the SC on the basis of the state of charge. A simulation study was conducted for three standard drive cycles (New York City cycle, Artemis urban cycle, and New York composite cycle) using MATLAB Simulink. Comparative analysis of conventional and proposed EMSs was carried out. The results reveal that the proposed EMS reduced the stress, temperature, and power losses of the battery. The steady-state charging performance of the SC was 98%, 95%, and 96% for the mentioned drive cycles.


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