Contribution management of lead‐acid battery, Li‐ion battery, and supercapacitor to handle different functions in EVs

Farjah, Amin; Ghanbari, Teymoor; Seifi, Ali Reza

doi:10.1002/2050-7038.12155

Cited by 12 publications

(13 citation statements)

References 32 publications

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“…However, the study did not provide a cost analysis of the system compared to a single battery system. In [33], a combination of LIB, LAB, and a supercapacitor is proposed to overcome the short vehicle range and longer charging time challenges in EVs. The authors use a bidirectional cuk converter and an energy management system (EMS) to improve the HESS efficiency by providing efficient power-sharing amongst the ESSs.…”

Section: State-of-the-art Literature Analysismentioning

confidence: 99%

Integrated Fuzzy-Logic and Triple-Loop PI-Based Management Strategy for a Lead-Acid/Lithium-Ion Hybrid Battery Energy Storage System

Lencwe

Zau

Chowdhury³

et al. 2022

Applied Sciences

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The huge success of electric vehicles across the world is challenged by a lack of infrastructure and a major increase in battery material prices. This challenge positions internal combustion engine vehicles (ICEVs) to remain a vehicle of choice. The majority of these vehicles use a lead-acid battery (LAB) for starting, lighting, and ignition (SLI) functions. However, these LABs are faced with challenges of short lifespan and low storage capacity because of improved electronic systems in modern ICEVs. In this manuscript, we propose an extension application of a hybrid LAB and lithium-ion energy storage system (ESS) for a vehicle using a single source of 70 Ah and 90 Ah capacity. Whereas previously, a hybrid energy storage system (HESS) for use in a vehicle using a source of 50 Ah battery capacity was proposed. Hence, the unique contribution of the study is using an integrated fuzzy-logic and triple-loop-proportional-integral-based battery management strategy (BMS) to improve LAB performance in a wide range of vehicles with different battery capacities sizes. The results show that the proposed BMS can help increase LAB lifespan and improve the storage capacity of the system, thus ensuring reliability. Additionally, compared to a single use of LAB, the combined energy storage system shows superior performance.

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Section: State-of-the-art Literature Analysismentioning

confidence: 99%

Integrated Fuzzy-Logic and Triple-Loop PI-Based Management Strategy for a Lead-Acid/Lithium-Ion Hybrid Battery Energy Storage System

Lencwe

Zau

Chowdhury³

et al. 2022

Applied Sciences

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“…Due to the battery is an important part of the utility grid, including EVs, the battery model is briefly introduced before establishing the dynamic model of EVs connected to the utility grid. As shown in Figure 2, the mathematical model of the battery adopts electronic components such as resistance, capacitance, and inductance to equivalent the electrochemical characteristics of the battery 24,25 .

R_{i .0}

and

R_{i .1}

represent the internal equivalent resistance parameter;

C_{i .1}

represents the internal equivalent capacitance parameter;

E_{i . m}

and

i_{i . m}

represent the internal voltage and current of the battery;

u_{i . italicdc}

and

i_{i . italicdc}

represent the output DC voltage and current of the battery;

R_{i}

is the line loss and line resistance;

L_{i}

is the filtering inductors and line inductors.…”

Section: Problem Formulation and Preliminariesmentioning

confidence: 99%

A novel no circulating current cooperative adaptive SoC balancing control for large‐scale grid‐connected electric vehicles

Dai

Liu

Cui

et al. 2021

Int Trans Electr Energ Syst

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Summary In this article, the state of charge (SoC) balancing problem of large‐scale electric vehicles (EVs) connected to the utility grid is addressed by designing a novel no circulating current cooperative adaptive SoC balancing control. First, considering different capacities and initial SoCs, an adaptive power distribution algorithm based on distributed dynamic consistency algorithm is blue developed to achieve the SoC balancing of large‐scale EVs connected to the utility grid. Then, considering the shortage of battery life caused by the circulating current during the long‐term charging and discharging process, an adaptive balance rate factor is designed to effectively avoid the generation of the circulating current. Then, an adaptive cooperative fuzzy terminal sliding mode controller is proposed for grid‐connected EVs to improve power tracking accuracy and enhance robustness. Considering the parameters' uncertainties and unmodeled parts of grid‐connected EVs, parameter adaptive estimation and fuzzy algorithm are used to approximate the unmodeled part. In addition, the boundedness of the adaptive estimation is guaranteed by using the projection operator. Finally, the validity and reliability of the designed control strategy are verified by simulations.

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“…respectively. According to circuit theory, the equations for Two RC-ECM for discharging scenarios under constant current are given by (1)(2)(3)(4)(5)(6).…”

Section: 1mathematical Model Of a Batterymentioning

confidence: 99%

“…Among several batteries, the Li-ion battery is the most suitable one due to its features like high energy density, long life cycle, low self-discharge rate, etc. [3]. Li-ion batteries are dangerous when used outside of their safe operating range, especially when employed in electric vehicles.…”

Section: Introductionmentioning

confidence: 99%

Sunflower Optimization Algorithm Based Filtering Method for State of Charge Estimation of Batteries in Electric Vehicle

Maheshwari¹,

Nageswari²

2021

Preprint

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The main focus of the battery management system is the estimation of the battery’s State of Charge (SOC) which is an indicator to determine the driving range of an electric vehicle. The Extended Kalman Filter (EKF) algorithm is the most promising for SOC estimation when the system is running. The EKF state estimation algorithm is sensitive to the process noise covariance matrix Q and measurement noise covariance matrix R. Inappropriate noise covariance matrices reduce the accuracy and make divergence in state estimation. In this paper, the Sunflower Optimization algorithm (SFO) is used to optimize the noise covariance matrices before applying EKF for online SOC estimation. This simply indicates that the iterative SFO does not affect the instantaneous response of EKF in online estimation because the SFO is only performed once to determine the optimal values. The effectiveness of the proposed identification is examined through the constant discharge rate test and dynamic stress test. As observed, the performance indices such as maximum error, Mean Absolute Error, Mean Square Error and Root Mean Square Error of both SOC and voltage obtained by the proposed SFO-EKF are low compared to the other three methods. Besides accuracy, the proposed method quickly converges even when the initial SOC is inaccurate. The simulation results show that the proposed method has high accuracy and a better convergence rate in terms of estimating SOC under static and dynamic operating conditions.

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Contribution management of lead‐acid battery, Li‐ion battery, and supercapacitor to handle different functions in EVs

Cited by 12 publications

References 32 publications

Integrated Fuzzy-Logic and Triple-Loop PI-Based Management Strategy for a Lead-Acid/Lithium-Ion Hybrid Battery Energy Storage System

Integrated Fuzzy-Logic and Triple-Loop PI-Based Management Strategy for a Lead-Acid/Lithium-Ion Hybrid Battery Energy Storage System

A novel no circulating current cooperative adaptive SoC balancing control for large‐scale grid‐connected electric vehicles

Sunflower Optimization Algorithm Based Filtering Method for State of Charge Estimation of Batteries in Electric Vehicle

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