Second-life applications of supercapacitors: Effective capacitance prognosis and aging

Saha, Pankaj; Dey, Satadru; Khanra, Munmun

doi:10.1016/j.jpowsour.2021.229824

Cited by 15 publications

(8 citation statements)

References 35 publications

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“…All the preceding techniques are restricted to the correct characterization of SCs lifespan. The effective capacity maintained in the cell, matching to the load profile of the second life functions after the end of lifetime and/or retirement from the first life, is described as a SC's second‐life capacity 22 . It provides a capacitive health prediction model for a retired SC for second life function in a specific application in this regard.…”

Section: Aging and Estimation State Of Supercapacitorsmentioning

confidence: 99%

“…In, 22 the second‐life application of aged/retired SCs is determined through a novel power‐based capacitance prediction model and identification approach. The model takes use of the real aging mechanism, which results in a longer time constant for the ions to pass through.…”

Section: Aging and Estimation State Of Supercapacitorsmentioning

confidence: 99%

“…Due to physical phenomena in SCs, a quick and massive charge/discharge load profile is impossible to use a significant portion of that energy density 21 . Thus, as the power of the applied load profile grows, the quantity of energy stored or derivable from the SCs decreases 22 …”

Section: Introductionmentioning

confidence: 99%

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A review of supercapacitors modeling, SoH, and SoE estimation methods: Issues and challenges

Laadjal

Cardoso

2021

Int J Energy Res

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Summary Supercapacitors (SCs), or ultracapacitors, due to their attractive features, such as, high power density, long life cycle, etc., have received much attention from the transportation sector. SCs can be used as an additional energy storage system (ESS) in combination with lithium‐ion batteries to enhance the performance of electric vehicles (EVs) in dynamic states, including acceleration and regenerative braking modes of operation. Online accurate estimation of SCs' state of health (SoH) and state of energy (SoE) is essential for an efficient energy management and real‐time condition monitoring in EV applications. The accuracy of the estimation of the SoE and SoH is based on the model's efficiency, which ensures that in order to minimize the impact of aging, model parameters should be defined in real time. Nevertheless, because the SC model is obviously nonlinear and broad in scale, online identification of the parameters estimation is usually difficult. In this paper, a generalized SC model of high accuracy and good robustness is proposed. The classification of the estimation methodologies for SoH and SoE of SC will be very helpful in choosing the appropriate method for the development of reliable and secure ESS and an energy management strategy for EVs.

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Section: Aging and Estimation State Of Supercapacitorsmentioning

confidence: 99%

Section: Aging and Estimation State Of Supercapacitorsmentioning

confidence: 99%

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A review of supercapacitors modeling, SoH, and SoE estimation methods: Issues and challenges

Laadjal

Cardoso

2021

Int J Energy Res

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“…Their results indicated that the proposed approach has high accuracy 32 . Saha et al proposed a capacitance prognosis model to identify the effective capacitance for the second‐life applications of supercapacitors 33 . Wang et al established a circuit model, identified the model parameters using recursive least square, and estimated the SOC of supercapacitors and batteries 34 .…”

Section: Introductionmentioning

confidence: 99%

“…32 Saha et al proposed a capacitance prognosis model to identify the effective capacitance for the secondlife applications of supercapacitors. 33 Wang et al established a circuit model, identified the model parameters using recursive least square, and estimated the SOC of supercapacitors and batteries. 34 Briat et al investigated the effects of cut-off voltage and temperature on the capacitance recovery during cycling aging tests.…”

mentioning

confidence: 99%

State of charge estimation of supercapacitors based on multi‐innovation unscented Kalman filter under a wide temperature range

Zhang

Yang

et al. 2022

Intl J of Energy Research

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Supercapacitors are characterized by a long service lifetime and high power density, which can meet the instantaneous high-power demand during the acceleration of electric vehicles. In this study, a fractional-order model is developed to simulate the polarization effect and charging/discharging characteristics of supercapacitors, considering the precision of the electrochemical model and the amount of calculation of the equivalent circuit model and using the adaptive genetic algorithm to identify the parameters. The accurate prediction of the state of charge (SOC) can improve efficiency, prolong the service lifetime, and ensure the safety of supercapacitors. This study proposes a multiinnovation unscented Kalman filter algorithm based on the fractional-order model to improve the SOC estimation accuracy. The proposed algorithm is compared with other algorithms and analyzed under different temperatures and operating conditions to verify the accuracy and effectiveness of the proposed algorithm in estimating the SOC and tracking the terminal voltage.Experimental results show that the root mean squared error and mean absolute error of the proposed algorithm are less than those of the other algorithms. The proposed algorithm accurately estimates the SOC and tracks the terminal voltage. The maximum root mean squared error and mean absolute error of SOC estimation error are 1.8% and 1.78%, respectively.

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Energy Management Optimization of Master–Slave Hybrid Electric Vehicle under Rule‐Based Control Strategy

Zhang

Hong

et al. 2022

Energy Tech

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In response to the imperfections and issues with conventional fuel vehicles and electric vehicles (EVs), this article proposes a master–slave hybrid electric vehicle (MSHEV) with multiple energy sources. The research team establishes the rule‐based control strategy for MSHEV with the aid of reviewing existing theories. The control strategy enables the MSHEV to transition between several working modes. The simulation consequence verifies that the MSHEV has lower power consumption and energy loss than the EV under actual vehicle driving cycle. One of most critical initial steps in ameliorating a vehicle's performance is parameter optimization. This article selects the battery state of charge of MSHEV as the optimization objective and optimizes applicable parameters. Thereafter, an approximate model is constructed based on the Response Surface Model, and an optimization model is built based on the Multi‐Island Genetic Algorithm. The energy management of the optimized MSHEV is more reasonable and the state of charge is further enhanced. The accomplishment of this article is of considerable significance and reference value in the optimization of energy management of hybrid electric vehicles.

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Second-life applications of supercapacitors: Effective capacitance prognosis and aging

Cited by 15 publications

References 35 publications

A review of supercapacitors modeling, SoH, and SoE estimation methods: Issues and challenges

A review of supercapacitors modeling, SoH, and SoE estimation methods: Issues and challenges

State of charge estimation of supercapacitors based on multi‐innovation unscented Kalman filter under a wide temperature range

Energy Management Optimization of Master–Slave Hybrid Electric Vehicle under Rule‐Based Control Strategy

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