Experimental parameter identification of battery-ultracapacitor energy storage system

Michalczuk, Marek; Grzesiak, Lech M.; Ufnalski, Bartłomiej

doi:10.1109/isie.2015.7281653

Cited by 26 publications

(17 citation statements)

References 22 publications

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“…All parameters are state-of-charge dependent. The proposed model applied to a hybrid storage system for an electric vehicle gives a better agreement for a simulated vs. experimental response when 3-branches are used in the model [23]. Figure 6b shows the Simscape implementation.…”

Section: Thevenin Modelmentioning

confidence: 97%

“…All of them are nonlinear models since this kind of models obtains better accuracy. The selected models are the Stern-Tafel Model [18], Zubieta Model [19], Series Model [20], Parallel Model [21], Transmission Line Model [22] and Thevenin Model [23]. In this section, the electrical equivalent circuit and the parameters of each model are reviewed.…”

Section: Supercapacitors Modelsmentioning

confidence: 99%

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A General Parameter Identification Procedure Used for the Comparative Study of Supercapacitors Models

et al. 2019

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Supercapacitors with characteristics such as high power density, long cycling life, fast charge, and discharge response are used in different applications like hybrid and electric vehicles, grid integration of renewable energies, or medical equipment. The parametric identification and the supercapacitor model selection are two complex processes, which have a critical impact on the system design process. This paper shows a comparison of the six commonly used supercapacitor models, as well as a general and straightforward identification parameter procedure based on Simulink or Simscape and the Optimization Toolbox of Matlab®. The proposed procedure allows for estimating the different parameters of every model using a different identification current profile. Once the parameters have been obtained, the performance of each supercapacitor model is evaluated through two current profiles applied to hybrid electric vehicles, the urban driving cycle (ECE-15 or UDC) and the hybrid pulse power characterization (HPPC). The experimental results show that the model accuracy depends on the identification profile, as well as the robustness of each supercapacitor model. Finally, some model and identification current profile recommendations are detailed.

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Section: Thevenin Modelmentioning

confidence: 97%

Section: Supercapacitors Modelsmentioning

confidence: 99%

A General Parameter Identification Procedure Used for the Comparative Study of Supercapacitors Models

et al. 2019

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“…The UC and battery parameters can be assessed using curve fitting techniques for desired cell responses. While designing ESS mechanisms like high temperature, over charge/discharge and under-/overvoltage protection schemes, cell balancing and their redistribution should be considered [122,123]. To split the current between UC and battery, Karush-Kuhn-Tucker (KKT) and the neural network (NN)-based EMS are used in [124].…”

Section: Impedance Source Invertermentioning

confidence: 99%

A comprehensive review on hybrid electric vehicles: architectures and components

2019

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The rapid consumption of fossil fuel and increased environmental damage caused by it have given a strong impetus to the growth and development of fuelefficient vehicles. Hybrid electric vehicles (HEVs) have evolved from their inchoate state and are proving to be a promising solution to the serious existential problem posed to the planet earth. Not only do HEVs provide better fuel economy and lower emissions satisfying environmental legislations, but also they dampen the effect of rising fuel prices on consumers. HEVs combine the drive powers of an internal combustion engine and an electrical machine. The main components of HEVs are energy storage system, motor, bidirectional converter and maximum power point trackers (MPPT, in case of solar-powered HEVs). The performance of HEVs greatly depends on these components and its architecture. This paper presents an extensive review on essential components used in HEVs such as their architectures with advantages and disadvantages, choice of bidirectional converter to obtain high efficiency, combining ultracapacitor with battery to extend the battery life, traction motors' role and their suitability for a particular application. Inclusion of photovoltaic cell in HEVs is a fairly new concept and has been discussed in detail. Various MPPT techniques used for solar-driven HEVs are also discussed in this paper with their suitability. Keywords Hybrid electric vehicle Á Hybrid energy storage system Á Architecture Á Traction motors Á Bidirectional converter Abbreviations and symbols ABS Antilock braking system AC Alternating current ADTR Antidirectional-twin-rotary ADVISOR Advanced vehicle simulator ANN Artificial neural network ASCI Auto-sequential commutated mode singlephase inverter BEV Battery electric vehicle BLDC Brushless DC motor CD Charge depletion CDFIM Cascaded DFIM CF-qZSI Current-fed quasi-ZSI CMPPT Centralized MPPT CS Charge sustaining CSI Current source inverter CS-PMSM Compound-structure PMSM CVT Continuous variable transmission DC Direct current DFIM Doubly fed induction motor DMPPT Distributed MPPT DRM Double-rotor machines DTC Direct torque control e-CVT Electronic continuous variable transmission EM Electric motor EMS Energy management system EREV Extended range electric vehicle ESS Energy storage system EV Electric vehicle FC Fuel cell

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“…Also, charging of these EVs at regular intervals is essential to increase their driving range. 2,3 Charging of EVs and increase in nonlinear load leads to power quality issues and a non-uniform power demand curve. The penetration of EVs also put forth technological challenges, such as building charging infrastructure and its optimal locations.…”

Section: Introductionmentioning

confidence: 99%

Improving power quality and load profile using PV‐Battery‐SAPF system with metaheuristic tuning and its HIL validation

Kumar

Bansal

Kumar

2020

Int Trans Electr Energ Syst

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Summary Nonlinear load results in inferior power quality and a non‐uniform power demand curve. This gets aggravated due to the charging of electric vehicles. This paper presents a new control approach of integrating a photovoltaic (PV) cell with battery storage to a shunt active power filter (SAPF) for electric vehicle (EV) applications. The multifunctional PV‐Battery‐integrated SAPF (PV‐Battery‐SAPF) performs harmonic mitigation along with clean power generation, energy storage, uniform load demand curve, and battery swapping. It is achieved through a two‐stage topology. In the first stage, maximum power point (MPP) of a PV array is robustly tracked using metaheuristic algorithms like cuckoo search algorithm and particle swarm optimization. In the second stage, an ant colony optimization‐tuned controller is developed which adaptively controls the SAPF to improve the power quality. The suggested method provides efficient MPP tracking, lesser total harmonic distortion, better dynamic system performance, and appropriate charging/discharging of battery leading to increased system reliability. The proposed system is validated in real time on a hardware‐in‐the‐loop (HIL) testing platform.

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Experimental parameter identification of battery-ultracapacitor energy storage system

Cited by 26 publications

References 22 publications

A General Parameter Identification Procedure Used for the Comparative Study of Supercapacitors Models

A General Parameter Identification Procedure Used for the Comparative Study of Supercapacitors Models

A comprehensive review on hybrid electric vehicles: architectures and components

Improving power quality and load profile using PV‐Battery‐SAPF system with metaheuristic tuning and its HIL validation

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