Showing 4 results for Energy Storage System
M. Masih-Tehrani , M.r. Hairi-Yazdi , V. Esfahanian,
Volume 4, Issue 2 (6-2014)
Abstract
In this paper, the development and optimization of Power Distribution Control Strategy (PDCS) have been
performed for a Hybrid Energy Storage Systems (HESS) of a Series Hybrid Electric Bus (SHEB). A
common PDCS is based on the use of Ultra-Capacitor (UC) pack. A new simple PDCS is developed as a
battery based one. For the battery based PDCS, four parameters are introduced for tuning the PDCS
performance. The Design of Experiment (DoE) method is utilized to optimize the parameters of the battery
based PDCS for the driving cycles and the vehicle controllers. The results show the optimized battery based
PDCS performance for some cases are better than the UC based PDCS performance. Vice versa, for some
cases the performance of the UC based PDCS is better than the battery based PDCS. Finally, the costs
rising from the HESS (about 66%) is reasonable when considering the over double increase in the battery
life-time when using an appropriate PDCS.
M. Masih-Tehrani, V. Esfahanian, M. Esfahanian, H. Nehzati, M.j. Esfandiary,
Volume 5, Issue 2 (6-2015)
Abstract
The Energy Storage System (ESS) is an expensive component of an E-bike. The idea of Hybrid Energy Storage System (HESS), a combination between battery and Ultra-Capacitor (UC), can moderate the cost of E-bike ESS. In this paper, a cost function is developed to use for optimal sizing of a HESS. This cost function is consisted of the HESS (battery, UC and DC/DC converter) cost and the cost of battery replacements during 10 years. The battery lifetime and riding pattern limit the life span of ESS. The “Portuguese standard NP EN 1986-1” riding pattern is used in this research. The Genetic Algorithm (GA) is used to solve the optimization problem. The results show that the cost and weight of HESS are clearly better than optimally sized battery ESS.
Mr Pouriya Rahimirad, Dr. Masoud Masih-Tehrani, Dr. Masoud Dahmardeh,
Volume 9, Issue 2 (6-2019)
Abstract
This paper investigates the effect of temperature on a hybrid energy storage system with various energy management systems. The hybrid energy storage system consists of a fuel cell, ultracapacitor and battery with associated DC/DC and DC/AC converters. The energy management strategies employed are the state machine control strategy, fuzzy frequency/logic decoupling strategy, minimization strategy of equivalent consumption (ECMS) and external energy maximization strategy (EEMS). Initially, a module of 3.3v 2.3Ah LiPo4 batteries consisting of 15 cells in series and 15 rows in parallel are studied without considering the temperature effect. In the next step, the studies are repeated considering the temperature variation effects. The current and SOC associated with the battery, the hydrogen consumption, and battery life are studied for each strategy. The results suggest that the errors associated with the battery life estimation, as well as the battery current are significant with and without considering the temperature effects with the values of 30% and 20%, respectively.
Mr Peyman Bayat, Dr. Hossein Afrakhte,
Volume 9, Issue 3 (9-2019)
Abstract
As an effective means of displacing fossil fuel consumption and reducing greenhouse gas emissions, plug-in electric vehicles (PEVs) and plug-in hybrid electric vehicles (PHEVs) have attracted more and more attentions. From the power grid perspective, PHEVs and PEVs equipped with batteries can also be used as energy storage facilities, due to the fact that, these vehicles are parked most of the time. Since, the temperature has a strong influence on the battery life-time and also the inherent characteristics of PHEV/PEV energy storage systems limit their use as appropriate resources for energy tuning, this paper, at first, presents a detailed model for energy storage systems of PEVs considering the cooling system and set temperature, and then, it proposes a reliable energy management method for scheduling of PEVs in the multi-microgrid (MMG) systems for both faulted and normal operations using parametric multi-objective function. The simulation results indicate that, considering proper energy management of energy storage systems of PEVs has significant influence on energy scheduling of MMG systems. For this investigation, all data analysis and simulations were done and implemented in MATLAB/Simulink environment.
