Integrated fuzzy-based modular cell balancing using mono circuitry for electric vehicle applications

George, Ginu Ann; Chacko, Fossy Mary; Prince, A.; Jayan, M. V.

doi:10.1007/s00202-020-01068-6

Cited by 4 publications

(3 citation statements)

References 35 publications

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“…A fuzzy comprehensive evaluation is based on the single-factor evaluation results of the influencing target to form a matrix and fuzzy transform the weight factors of each factor so as to obtain the fuzzy evaluation results of the total target [18].…”

Section: Fuzzy Integrated Assessmentmentioning

confidence: 99%

Research on the quality control strategy of marine engineering based on big data technology

Yuan,

Yu,

Sun

et al. 2023

Applied Mathematics and Nonlinear Sciences

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The research of quality control strategy of marine engineering using big data technology is to better promote the enterprise to reduce cost and increase efficiency. In this paper, starting from the project quality control system, a quality control risk evaluation model is constructed based on hierarchical analysis and fuzzy comprehensive evaluation by means of the fuzzy comprehensive evaluation of affiliation degree. For the model constructed based on AHP-FCR in this paper, experimental analysis of quality control influencing factors and fuzzy comprehensive evaluation examples were conducted by establishing indicators. From the influence factors, the severity of engineering personnel risk and engineering machine risk are 19.289 and 20.216, respectively, both of which are significant levels of influence. From the fuzzy comprehensive evaluation, 49.09% of the experts voted that the level of quality control risk of S Company’s offshore engineering module oilfield construction project is now low and in an acceptable state. It can be concluded that the AHP-FCR model with big data technology can realize the quality control risk assessment of offshore engineering and also provides theoretical support for companies to solve the risk.

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Section: Fuzzy Integrated Assessmentmentioning

confidence: 99%

Research on the quality control strategy of marine engineering based on big data technology

Yuan,

Yu,

Sun

et al. 2023

Applied Mathematics and Nonlinear Sciences

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“…In the process of BP, the weights and thresholds are repeatedly corrected, so that the target output error is optimized in the required direction. For the error function in the neural network and according to the gradient descent method, the gradient value for the jth node is shown in Equation (15).…”

Section: Update Stagementioning

confidence: 99%

“…However, due to the complex working conditions and the complex internal structure of lithium-ion batteries [9][10][11], the battery often exhibits drastic nonlinear characteristics [12][13][14]. Based on this, a new model needs to be developed to replace the traditional one to describe the operating characteristics of lithium-ion batteries [15,16]. Currently, the commonly used battery models include equivalent circuit models [17], electrochemical models [18,19], and thermal coupling models [20][21][22].…”

Section: Introductionmentioning

confidence: 99%

A Novel Adaptive Back Propagation Neural Network-Unscented Kalman Filtering Algorithm for Accurate Lithium-Ion Battery State of Charge Estimation

Wang

Wang²,

Fan³

et al. 2022

Metals

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Accurate State of Charge (SOC) estimation for lithium-ion batteries has great significance with respect to the correct decision-making and safety control. In this research, an improved second-order-polarization equivalent circuit (SO-PEC) modelling method is proposed. In the process of estimating the SOC, a joint estimation algorithm, the Adaptive Back Propagation Neural Network and Unscented Kalman Filtering algorithm (ABP-UKF), is proposed. It combines the advantages of the robust learning rate in the Back Propagation (BP) neural network and the linearization error reduction in the Unscented Kalman Filtering (UKF) algorithm. In the BP neural network part, the self-adjustment of the learning factor accompanies the whole estimation process, and the improvement of the self-adjustment algorithm corrects the shortcomings of the UKF algorithm. In the verification part, the model is validated using a segmented double-exponential fit. Using the Ampere-hour integration method as the reference value, the estimation results of the UKF algorithm and the Back Propagation Neural Network and Unscented Kalman Filtering (BP-UKF) algorithm are compared, and the estimation accuracy of the proposed method is improved by 1.29% under the Hybrid Pulse Power Characterization (HPPC) working conditions, 1.28% under the Beijing Bus Dynamic Stress Test (BBDST) working conditions, and 2.24% under the Dynamic Stress Test (DST) working conditions. The proposed ABP-UKF algorithm has good results in estimating the SOC of lithium-ion batteries and will play an important role in the high-precision energy management process.

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Study of inductively coupled fuel cell DMPPT converters

Wei,

Sun,

Zhang

et al. 2024

Electr Eng

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Integrated fuzzy-based modular cell balancing using mono circuitry for electric vehicle applications

Cited by 4 publications

References 35 publications

Research on the quality control strategy of marine engineering based on big data technology

Research on the quality control strategy of marine engineering based on big data technology

A Novel Adaptive Back Propagation Neural Network-Unscented Kalman Filtering Algorithm for Accurate Lithium-Ion Battery State of Charge Estimation

Study of inductively coupled fuel cell DMPPT converters

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