Comparison of energy management strategies of a battery/supercapacitors system for electric vehicle under real-time constraints

Castaings, Ali; Lhomme, Walter; Trigui, Rochdi; Bouscayrol, Alain

doi:10.1016/j.apenergy.2015.11.020

Cited by 219 publications

(82 citation statements)

References 38 publications

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“…With the rapid development of smart grids and new energy vehicles, there is an increasing demand for high-efficiency energy storage systems [1][2][3]. Supercapacitors, characterized by high power density and excellent cycling stability, have evolved into an important class of new-type energy storage devices [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Synthesis of hierarchically porous MnO2/rice husks derived carbon composite as high-performance electrode material for supercapacitors

Yuan

Lin

et al. 2016

Applied Energy

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Section: Introductionmentioning

confidence: 99%

Synthesis of hierarchically porous MnO2/rice husks derived carbon composite as high-performance electrode material for supercapacitors

Yuan

Lin

et al. 2016

Applied Energy

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“…Qualitative analysis is not difficult as it can be observed from either experiment or simulation that the battery is protected by the SMES from the high-rate of discharge. In fact, many works [26,39,40] have already studied battery life extension in the HESS scheme. However, in these works, it cannot be found as to what degree the battery lifetime is extended.…”

Section: Battery Lifetime Prediction Methodsmentioning

confidence: 99%

Design and real-time test of a hybrid energy storage system in the microgrid with the benefit of improving the battery lifetime

Xiong

et al. 2018

Applied Energy

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• A new control method of the hybrid energy storage system is introduced.• The battery lifetime has been proved to be extended in the real-time experiment.• A new experiment method is proposed using the RTDS&HIL to give real-time verification.• A battery lifetime prediction method is introduced.• The RTDS&HIL scheme highlights a flexible real-time experimental approach. This study proposes a hybrid energy storage system (HESS) composed of the superconducting energy storage system (SMES) and the battery. The system is designed to compensate power fluctuations within a microgrid. A novel control method is developed to share the instantaneous power between the SMES and the battery. The new control scheme takes into account the characteristics of the components of the HESS, and the battery charges and discharges as a function of the SMES current rather than directly to the power disturbances. In this way, the battery is protected from the abrupt power changes and works as an energy buffer to the SMES. An new hardware-in-loop experiment approach is introduced by integrating a real-time digital simulator (RTDS) with a control circuit to verify the proposed hybrid scheme and the new control method. This paper also presents a battery lifetime prediction method to quantify the benefits of the HESS in the microgrid. A much better power sharing between the SMES and the battery can be observed from the experimental results with the new control method. Moreover, compared to the battery only system the battery lifetime is quantifiably increased from 6.38 years to 9.21 years.

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“…After measuring the terminal voltages of each cell and the pack, the dynamic voltage caused by the impedance can be calculated with Equation (2). Then, with Equation (23) and the identified ohmic resistances of cell 1, cell 2 and the mean cell, the polarization voltages can be obtained.…”

Section: Improved Parameter Identification For Series Connected Battementioning

confidence: 99%

“…in which U d is the dynamic voltage response caused by the impedance, and can be calculated by Equation (2). After measuring the terminal voltages of each cell and the pack, the dynamic voltage caused by the impedance can be calculated with Equation (2).…”

Section: Improved Parameter Identification For Series Connected Battementioning

confidence: 99%

Online Reliable Peak Charge/Discharge Power Estimation of Series-Connected Lithium-Ion Battery Packs

et al. 2017

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Abstract:The accurate peak power estimation of a battery pack is essential to the power-train control of electric vehicles (EVs). It helps to evaluate the maximum charge and discharge capability of the battery system, and thus to optimally control the power-train system to meet the requirement of acceleration, gradient climbing and regenerative braking while achieving a high energy efficiency. A novel online peak power estimation method for series-connected lithium-ion battery packs is proposed, which considers the influence of cell difference on the peak power of the battery packs. A new parameter identification algorithm based on adaptive ratio vectors is designed to online identify the parameters of each individual cell in a series-connected battery pack. The ratio vectors reflecting cell difference are deduced strictly based on the analysis of battery characteristics. Based on the online parameter identification, the peak power estimation considering cell difference is further developed. Some validation experiments in different battery aging conditions and with different current profiles have been implemented to verify the proposed method. The results indicate that the ratio vector-based identification algorithm can achieve the same accuracy as the repetitive RLS (recursive least squares) based identification while evidently reducing the computation cost, and the proposed peak power estimation method is more effective and reliable for series-connected battery packs due to the consideration of cell difference.

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Comparison of energy management strategies of a battery/supercapacitors system for electric vehicle under real-time constraints

Cited by 219 publications

References 38 publications

Synthesis of hierarchically porous MnO2/rice husks derived carbon composite as high-performance electrode material for supercapacitors

Synthesis of hierarchically porous MnO2/rice husks derived carbon composite as high-performance electrode material for supercapacitors

Design and real-time test of a hybrid energy storage system in the microgrid with the benefit of improving the battery lifetime

Online Reliable Peak Charge/Discharge Power Estimation of Series-Connected Lithium-Ion Battery Packs

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